Lend Academy's Lending and Fintech Podcast

PODCAST TRANSCRIPTION SESSION NO. 194 / LENDIT FINTECH USA 2019 PREVIEW SHOW (WITH TODD ANDERSON AND RYAN LICHTENWALD)

Welcome to the Lend Academy Podcast, Episode No. 194. This is your host, Peter Renton, Founder of Lend Academy and Co-Founder of the LendIt Fintech Conference.

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Today’s episode is sponsored by LendIt Fintech USA 2019, the world’s leading event in financial services innovation. It’s going to be happening April 8th thru 9th, at Moscone West in San Francisco. We’re going to be covering digital banking, Blockchain, financial health and, of course, online lending, as well as other areas of fintech. There will be over 5,000 attendees, over 250 sponsors and registration is now open. Just go to lendit.com to register.

Peter Renton: We’re doing something a little bit different on the show today, this is annual LendIt Fintech USA Preview Show. I’m bringing on by colleagues, Todd Anderson and Ryan Lichtenwald. these are the people who also bring you LendIt News.

The three of us are focusing on producing the agenda for LendIt, we also write news articles and features on lendacademy.com, but today, we are talking all about LendIt where we’re going to firstly start with the trends in the industry and then go through how to get the most out of the show, what are some of the features of the show so if you’re coming to LendIt, this will make your experience much more efficient by getting a good flavor for the show to help you navigate what is really a whirlwind couple of days. I hope you enjoy the show.

Welcome back to the podcast, Todd and Ryan.

Todd Anderson: Thanks for having us, Peter.

Ryan Lichtenwald: Thanks, Peter.

Peter: Okay, of course. So this is a LendIt Preview episode, but before we get right into the nitty-gritty of the event, I wanted to take a step back and maybe talk about what are some of the trends we’re seeing in the broader fintech space today. Maybe I’ll start off with you, Todd, what are you seeing?

Todd: Thanks, Peter, I think, overall, I’d say the biggest trend has to do with the banking market in a couple of different areas. So I think, first, when you look at bank partnership thinking of just a few short years ago, there was a lot of talk amongst banks and fintechs as if they were competitors with one another and I think that’s really been the biggest shift. Now you talk to banks and fintechs and both see each other as partners and so I think really that shift that’s happened the last couple of years has really changed the market.

So you’re seeing bank partnership deals for lending, bank partnership deals for investing, bank partnership deals for other areas in fintech; for AI in conversational bots or potentially fraud-related technologies to help catch anti-money laundering or have to comply with the Bank Secrecy Act. So I think, overall, bank partnerships have really shifted into this place where it’s a bigger, better, safer environment where banks and fintechs are really playing with each other, you know, pretty much consistently and there’s a lot less talk about animosity.

The one area, though, where there’s still, I’d say, a bit of competition moving to that second big area of banking is the growth of these digital banks. First, you’ve seen a big growth in some of the firms in Europe like OakNorth who just raised a significant round, hundreds of millions of dollars. You have Monzo, N26 who’s soon going to be launching in the US as well as Revolut, who’s launched internationally is looking at the US. So I think where there’s still that competitive juices flowing is probably more in digital banking so the fintechs are trying to become banks or alternative to banks with either cross-border payments that are very cheap or checking or current accounts as many people are calling them these days.

And so I think those offerings put a little of that competitive edge to a limit, but I think when you look at banking overall, the market really shifted in the last couple of years to see a lot more collaboration and a lot more deals getting done between banks and fintechs than you might have seen a few years ago.

And then one more area, I’d say, is Blockchain. While there’s been a lot of talk of the crypto space, especially going from where it was in the end of 2017 to where it is now, I think the big thing you’ve seen recently is that financial firms are really starting to put some of these projects into production. Firms like Fidelity are coming up with COfTI solutions  so I think you’re really started to see banks, in particular big multinational banks, look at Blockchain solutions so they can see how they can save money and also deal with many of the different parties such as the supply chain finance or syndicated lending that it’s easier to handle those types of transactions when you’re on the Blockchain. So I think you’re seeing a few different trends and so I think it’s been an interesting, I’d say, 18 months and those are just some of the things that I’ve seen.

Peter: Right, right. Okay then, so what about you, Ryan, what are you seeing, what sticks out for you these days?

Ryan: I think the number one thing to me is just the amount of capital coming into fintech so coming into 2019, you know, everyone was reflecting on 2018 and it ended up being the largest year for fintech funding. And so coming into 2019, only just a few months in here now, but, collectively as a team have noticed all these fintech funding rounds, massive funding rounds and I think that’s one of the big trends today.

We created this pulse and decided to start tracking some of these large funding rounds and I was just looking back and we’re just focused on rounds that are $10 Million plus globally. Now just looking at our list and as we’re recording this on March 28th, we almost have 50 firms that have raised over $10 Million, many names that folks are familiar with. Some of these are large rounds for, I guess, you can call them later stage fintechs, still some new names in there. For me, that’s the number one trend that I’ve been seeing.

Peter: Right, right and it’s fascinating to see, particularly in the digital banking space that Todd was talking about, I mean, some of the rounds are monstrously large. It almost feels to me….like we go back to early 2015 in the lending space where there was just capital being thrown around. I wouldn’t say willy-nilly, but if you had a half decent idea and a half decent team you got money thrown at you. I don’t know if it’s quite the same, but, boy, in the digital banking space we are really….just that there’s so much capital being attracted because there’s plenty of good companies in the US, in Europe and all over the place actually that are attracting these amounts of capital.

I don’t want to neglect the lending space because I feel like the lending space is no longer the flavor of the month that’s been so for some time, but there’s still good companies as to attracting capital and there’s plenty of innovation that’s happening. I think you really are seeing, particularly on the underwriting side, fraud detection, there’s a lot happening in the lending space when it comes to bringing a better user experience to the customers. You’ve got companies that are now adding multiple products into their offerings and we are certainly seeing some interesting innovations happening there as well.

So anyway, let’s talk about the event itself. We’re recording this 11 days before we kick it off. Maybe, Todd, I can start with you, just tell us a little bit about the structure of the event, what people can expect.

Todd: Sure, so what you’ll see this year at the Moscone West Center in San Francisco is the event, from the majority, takes place on Level 1 and Level 2. So if you look at Level 1, you have the Expo Floor. On the Expo Floor, you’ll have food and beverage, you’ll have all of our sponsors, who without them we probably could not do this event, and so the Expo Floor is where a lot of the commotion will be going on, a lot of meetings, you’ll have the Brella networking area, you’ll have food and beverage so the first floor will be very, very exciting and a lot happening during the course of the event.

When you look at the second floor, that’s what we call the Content Floor. On the second floor, we’ll have our Keynote Hall, as well as our six simultaneous tracks that will occur after the Keynote Hall and we’ll also have some private lunch areas, but really, the second level you’re looking at it and it’s all content.

The third level, which we still have part of this year, is really focused on some private parties, some meeting rooms, but really, when you’re coming to the event, you’re looking at Level 1 and Level 2, that’s where the event is going to be happening this year so Expo Hall Level 1, Content Level 2.

Moving on to the Awards Show which is something that we’re going to have for the 3rd year in a row, the Awards Show is going to be on the night of April 9th and this is our 3rd Annual LendIt Fintech Awards. It’s going to be taking place at the Julia Morgan Ballroom, and this is also in San Francisco. The Awards Show brings together over 400 fintech influencers and innovators and they’re celebrating more than 20 awards of the biggest names in fintech. So this year we’ll be very excited to have the Awards Show again and so when coming to the event, think Expo Hall, Content and Awards Show or three of the most important things to know when coming to LendIt Fintech USA.

Peter: Unfortunately, the Awards are sold out so if you’re listening to this and you haven’t got a ticket, I’m sorry, you can find out what happened after the event. Okay, so let’s move on to some of the other things that we have going on. Ryan, why don’t you tell us about some of the things that you’re focusing on.

Ryan: Sure, happy to. So if you’ve already been to LendIt before, you’re familiar with our On-Floor Theater in the middle of the Expo Hall. This is the Innovation Zone and there’s a few types of content taking place here right in the middle of the Expo Floor, kind of all around the sponsors, all of the networking so we’ll have a few different companies presenting company demos. These are short, 10-minute demos that will take place on Day 1 for companies to really showcase all the things that they’re working on, some interesting innovations, etc.

Moving into the afternoons on both days, we’re actually going to feature some podcasts, including the Lend Academy podcast that you can listen to Peter record a couple of shows live. We also have the rebank podcast as well as the Wharton Fintech podcast, which I’m really excited to have them.

And taking place on Day 2, we will have our annual PitchIt competition so this is where startups compete and we’ll have VC’s judging them and so excited to see what happens there on our PitchIt at LendIt stage.

Moving on to more on the networking side of things, so last year we had two mobile apps, this year we are moving to just one to avoid some confusion and kind of streamline the networking process at LendIt so everyone who is attending to download Brella. Within Brella, you’ll get a join code that will have them e-mailed to you, you can join Brella and this basically will give you all the information that you need about the event so this includes the agenda and more importantly, our one-to-one meeting tool and so you can view all the attendees, what types of folks you may want to be meeting with and set up short meetings with them right on the Expo Floor, there’s an area dedicated to that.

Peter: Okay, okay. I want to highlight the Women in Fintech initiative that we have. This is the 3rd year we’ve really focused on this and we’ll have a 3rd Annual Women in Fintech luncheon sponsored by Deloitte on April 8th. New this year, we have a Speed Networking Program, we have Women in Fintech Mentoring Program and also culminates in the Fintech Women of the Year which will be announced at the Awards Show on the evening of April 9th, as mentioned.

I want to just re-emphasize that at the Expo Hall we have over 200 exhibitors down there and I highly recommend everybody spend a little bit of time down there. We’ve got some of the leading companies in the industry providing all kinds of different services and I encourage everybody to at least spend a little bit of time wandering around getting to know what are the latest offerings in the fintech space. I often find that I’m like a kid in a candy store when I’m walking through the Expo Hall.

Of course, like we have every year, we also have plenty of media there, there will be some of the media that will be actually interviewing different speakers. There’ll also be plenty of media there just covering the event and I highly recommend you basically find out what’s going on and you should all check it out.

So then let’s move on to the nitty-gritty here, let’s move on to the agenda itself and just so everybody knows, Todd, Ryan and myself put together pretty much the entire agenda and we’ve all taken various different pieces. Maybe, Todd, I can start with you and you can talk through some of the structure of the agenda.

Todd: Sure, so as we talked about before, there is content mainly on Level 2, but there is a piece on Level 1 so in coming to the event the content is structured really in a couple of different ways.

First and foremost is our Keynote Hall, this is going to be on Level 2, it’s our biggest stage that features the biggest names and so each day, both on April 8th and April 9th, we start off at the Keynote Hall and nothing, no other content goes against it. So these are the biggest names in fintech who get the stage to themselves, talk about the hottest topics, fireside chats, presentations so this is really where the highlight of our content starts.

After each Keynote Hall session ends in the morning that’s where we move to our tracks. So our tracks, there’s six simultaneous rooms, it’s right across the hall from the Keynote Hall so you can’t miss it. We put most of the content on Level 2 to make it easy to transition from the Keynote to the tracks and so after the Keynote Hall ends in the morning, you can go ahead to the tracks.

Additionally, down on the Expo Floor, as Ryan was talking about, we have our Innovation Zone. This will feature podcasts, this will feature demos and on Day 2 will also feature PitchIt. So in total, when looking at the structure of the agenda, there’s eight simultaneous tracks or rooms; Keynotes which will kick off each day and they go, first and foremost, by themselves, then we’ll go to tracks and Innovation Zone, then we go to lunch.

Coming back from lunch, the structure stays the same; we do keynotes by themselves and then move on to the tracks in the Innovation Zone. So the majority of the content starts on Level 2 with the Innovation Zone on Level 1 supplementing it, but, overall, that’s how the content is structured at LendIt.

Peter: Okay, great. And then, of course, we have all the different tracks. We’re covering…….I can’t remember how many topics we’re covering, I don’t know whether you guys remember that at the top of your head, but there’s a lot of different topics.

Certainly where we are strongest and where we will continue to really lead the industry is in the lending content and we have a dedicated consumer lending track, small business lending track, we have a track focused just on financial inclusion again, we’re covering policy and regulation and a lot more, but that’s part of what I’ve been focusing on developing personally over the last like six months. Ryan, why don’t you tell us about some of the things that you’ve been focusing on?

Ryan: Sure, so first off, we have the paperless mortgages and real estate innovations sessions. This really focuses on both the bank partnership angle with mortgages, we’re going to talk about, you know, making home purchases and selling. There’s some really interesting platforms that have huge traction here. We’re going to talk about bank connectivity and how that improves the mortgage process, tokenized real estate, non-bank lending and, of course, the hillock (?).

We also have the credit and underwriting track, here we’ll talk about some of our topics around customer acquisition, automated loan underwriting, kind of go into depth on identity and sort of those topics, including AI, some of the benefits there and also dig into kind of what the credit market is looking like today.

And then, finally, the session, the last track that I worked on was niche lending and here we’re just covering a wide variety of verticals so we’re going to cover the gig economy, we’re going to cover some of the opportunities in the Hispanic market and some of the lenders there; we’re going to talk about auto finance and we’re also going to cover patient lending. So those are some of the topics that we’re covering in that track.

Peter: Okay, Todd, what have you been working on?

Todd: So to go back to some of the stuff I was mentioning in our top stories, I’ve really been focused on bank partnerships, digital banking and, you know, one thing that you’ll see this year, before getting into some of the specifics of the tracks I worked on, is you’ll see more banks on the agenda than you’ve ever seen before.

There’ll be banks in not only the digital banking and community banks and credit union tracks, but you’ll also see banks in our lending track, you’ll see banks on our international track, you’ll see banks on our credit track, our real estate track so really what we’ve seen the shift has been that banks are working with fintechs a lot more. And so we’re covering bank partnerships on our digital banking innovation and partnership tracks, we’re covering bank partnerships from a couple of different angles, how companies can launch products quickly, how there’s various bank partnerships from chat, to AI, to lending so we’re really taking a look at how banks and fintech are really working together in a really in-depth way.

For the first time this year, we’re also going to be featuring a track of community banks and credit unions. The main difference between those two tracks is community banks and credit unions, they have to operate differently, they’re not able to do proof of concepts that cost billions of dollars; they need to be smart, they need to be strategic so we’re covering that angle for those types of banks and credit unions that come to the show.

So if you’re a little bit bigger of a bank, you would go the digital banking and innovation partnership track, if you’re on the smaller scale or if you’re a credit union, you would go to the community banking credit union track. So we’re really trying to specify different types of content for the different attendees that join us.

We’ll also be covering Blockchain, as we have the last few years, and we put a little bit of a different spin on this year. We have really focused on Blockchain for financial services so what we like to call Enterprise Blockchain. Talking about payments, talking about supply chain…is Blockchain really ready to move to production in terms of scale in financial services.

We’ll be talking about providences, Blockchain from Figure Technologies and so we’re really looking at Blockchain from the enterprise side and then, last but not least, of course, is the international track where we cover different markets around the world; Latin America, the Middle East, China so we really want to hit on various different areas of the world and that’s something that has always been core to LendIt is that this is our global event.

Peter: Right, right, and I also do want to mention a couple of other topics that we will be covering. You know, there’s been a bit of a merging of the sort of the payment space and the lending space with payment providers going to the lending space and lending providers going to the payment space so we are going to be covering some payments innovation and, of course, as we do every year, we have an investing track which is focused on all the investors in the space, whether you’re a VC investor or a debt investor or hedge fund, what have you, we’ve got a whole range of different topics focused just on that audience.

Anyway, I want to move on and talk about keynotes because that’s…obviously we’ve got some really big names on the stage this year, many new names to LendIt and wanted to just talk about that briefly. Maybe, Todd, start with you and talk about who are the keynotes that you’re most interested in this year.

Todd: Sure, there were a few that really caught my eye. I’d say first is having Sallie Krawcheck join us this year. Sallie’s, obviously, well known in the banking community, she also started her firm, Ellevest, and she’s going to be talking about how financial services firms, banks or fintechs, are really missing out on a potential opportunity of not targeting women investors. These, by some estimates, over 700 billion on the sidelines that could be put into different parts of the financial system, if financial firms were just more targeted towards products that would be speaking to women investors. So she’s going to be talking about that which I think will be a fascinating discussion as well as Green Dot and Stash.

This is the first year that we have Green Dot on the agenda. The partnership between them and Stash is very interesting, they just recently released more information about the partnership so I think what you’ll see is that the Keynote Stage features some innovation in a variety of different ways and those are just two of the many keynotes that really stood out to me.

Peter: Ryan, what about you, what stood out for you?

Ryan: Yeah, so I’m really excited to hear from Boe Hartman, who’s the Head of Consumer Technology and a Co-CIO at Goldman Sachs Bank. You know, my perspective is Marcus has really moved from kind of being a new entrant to being kind of one of the leaders in consumer finance so very interested to hear what they have to say and some of the things that they’re working on.

Secondly, I would have to say Mike Cagney from Figure. I think getting beyond all the capital that they raised, this is a company that is still relatively new, but is originating all of their home equity lines of credit on the Blockchain and they’ve done so at incredible speed and it’s just…..really impressive to me is that they’ve gone from idea to execution. I’ve already received a mailer from them which is kind of funny, but, yeah, I just think it’s going to be very interesting to hear what Mike has to say. They’re really differentiated from a lot of other players in the space.

Peter: Right, right, for sure. Well there are so many great ones here. I want to give a plug to our Opening Keynote which is …we have the CEO of Discover, Roger Hochschild, and Douglas Merrill, CEO of Zest Finance. I think this has been a really important partnership that was announced just a couple of weeks ago and we will have them on stage together talking about how…you know how a pretty significant bank is using machine learning to really totally revamp how they are sort of expanding their credit box and I think it’s going to be fascinating to see and hear what they talk about.

Of course, we have some of the lending leaders; we’ve got Max Levchin from Affirm, Ron Frohwein from Kabbage, you know, Renaud Laplanche from Upgrade, all giving keynotes.

We have Karen Mills talking about small business lending, in fact, she has just written a book. I’ll be interviewing her on stage and she obviously was a guest on the podcast just pretty recently.

We’ve got FICO and Experian on stage together for the first time at LendIt talking about consumer permission data and we’ve got Yihan Fang from Yirendai. I’m fascinated to hear what she has to say, there’s a lot going on in China right now and it will be interesting to hear her thoughts about what’s going on there.

I’m really excited about the keynote program, I think we’ve got a fantastic line-up and I’m just as excited as anybody else to hear what they will have to say. So we’re just about running out of time here, but before we sign off, let’s talk about something that I think most people come to these events to do and that is to network and I think it is extremely important and maybe, Ryan, you can tell us a little bit about how people can network, how people can get the most out of the event when it comes to networking.

Ryan: Yeah, so if you haven’t already and you’re coming to LendIt, I highly recommend you get on your phone right now and go to the App Store and download Brella. As I mentioned earlier, that’s our app for one-on-one meetings and it is sponsored by Marqeta this year.

What they’ve done is they’ve created this very simplistic way of scheduling one-on-one meetings with folks who have joined Brella and so you can schedule it with your calendar and just set-up the short little meetings which tend to be great. The way it works is you’re assigned a table and there’s an area at our Expo Floor that has numbers on them so you know where to meet. It makes the networking process extremely easy and efficient so you kind of get the most  out of networking at LendIt so highly recommend that.

In addition, I will also just mention that on our website we also have our company list and attendee list so you can always view that to see some of the folks that are attending. And then moving on to some of our networking events so we have our Art of Innovation Happy Hour that’s taking place on April 8th at the end of the first day.

We also have our Wine Tour which unfortunately now is sold out, but that’s the first time doing that this year so kind of interested to hear how that works and some of the more unique opportunities. And then, of course, we also have outside parties that are organized by other sponsors or companies that are kind of having an event outside of LendIt to draw kind of all the folks coming to LendIt Fintech.

Peter: Okay, well we’re pretty much out of time so maybe…we’ve been working very hard for the past several months and let’s just finish off by sharing, what are your guys planning on doing right after LendIt.

Todd: I would say, I probably would sleep a little bit, but, overall, I do have a 5-month old so I will be spending plenty of time with him and if the weather gets nice, maybe I’ll begin to play some golf. I know I’ll be watching the Masters since it’s the week after LendIt or just at the end of the week that LendIt happens. So those are just the couple of things I’ll be doing once we finish.

Peter: Yes, that has been great news for the last two years. I have not been able to watch much of the Masters because it’s been on the weekend before LendIt and we’ve been working so hard so I’m very much looking forward to seeing that and watching the Masters as well. Anyway, Ryan, what about you, what are you up to?

Ryan: Yeah, so I’m actually coming back for a few days back to Wisconsin and then we head out to Puerto Rico to seek warmer climate and kind of relax after LendIt. So that’s our plan.

Peter: Good for you. Well, I’m actually staying in the Bay Area, I’m heading down to Half Moon Bay. My wife is coming out and I will be closing my laptop and sort of enjoying just all the natural beauty of that part of the world. Anyway, so I think it’s going to be a fantastic show, this is our 7th annual and I think it’s going to be the best one we’ve ever had. So really want to thank you guys for coming on and giving everybody some help with the LendIt Preview Show, thanks very much, guys.

Todd: Thanks, Peter.

Ryan: Thanks for having me.

Peter: Okay, see you.

Well there you have it. I hope to see many Lend Academy podcast listeners at the show. If you do listen to the show, please come up and say hi, I’d love to have a quick chat, and if you are still on the fence, time is running out, but if you’re still on the fence as you’re listening to this, tickets will be available right up to the morning of April 8th so you will be able to buy tickets at the door and I hope to see many of you in San Francisco.

We will be off next week, I’m taking the week off. There will be no podcast next week, we’ll be back in two weeks and hope you have a great show. Thanks, bye.

Today’s episode was sponsored by LendIt Fintech USA 2019, the world’s leading event in financial services innovation. It’s happening April 8th thru 9th, at Moscone West in San Francisco. It’s going to be the largest fintech event held in the Bay Area in 2019. We’ll be covering online lending, Blockchain, digital banking and much more. You can find out all about it and register at lendit.com.

PODCAST TRANSCRIPTION SESSION NO. 193 / ANTHONY NOTO

Welcome to the Lend Academy Podcast, Episode No. 193. This is your host, Peter Renton, Founder of Lend Academy and Co-Founder of the LendIt Fintech Conference.

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Today’s episode is sponsored by LendIt Fintech USA 2019, the world’s leading event in financial services innovation. It’s going to be happening April 8th thru 9th, at Moscone West in San Francisco. We’re going to be covering digital banking, blockchain, financial health and, of course, online lending, as well as other areas of fintech. There will be over 5,000 attendees, over 250 sponsors and registration is now open. Just go to lendit.com to register.

Peter Renton: Today on the show, I’m delighted to welcome Anthony Noto, he is the CEO of SoFi. Now I think pretty much every listener has heard of SoFi, they really are one of the highest profile companies in all of fintech, they seem to have more news than pretty much any other company, I see them in the news pretty much every week, it seems like, these days and they’re really pushing the envelope.

They’re moving from just focusing on the lending side of the business to a really fully diversified financial services company. Now I wanted to get Anthony on the show, he’s been in the job now for over a year and I wanted to talk about, you know, how the last year has been, where the focus is today, what are some of the things that he’s excited about, what are some of the things they’re working on and we go through all the various different pieces of the SoFi business. It was a fascinating interview. I hope you enjoy the show.

Welcome to the podcast, Anthony!

Anthony Noto: Thank you for having me.

Peter: Okay, so I’d like to get this thing started by giving the listeners a little bit of background about yourself. You’ve certainly had an interesting career with some pretty high profile positions so why don’t you give us some of the highlights.

Anthony: I’ve been fortunate to be part of some great organizations with, you know, phenomenal cultures and really well known brands or products. I spent just about four years at Twitter prior to coming to SoFi first as a Chief Financial Officer and then as the Chief Operating Officer. We accomplished a lot of great things at Twitter and really restructured them and turned around the company and really proud of what the team was able to accomplish there and be a part of that team.

Prior to being at Twitter, I spent two different distinct tours at Goldman Sachs, four years from 2010 to 2014 in banking as the Head of Global Technology Media & Telecom Banking and the first nine years in banking, 1999 to 2007, as an Equity Research Analyst focused on technology and media companies, initially just on the Internet and then adding entertainment companies and then distribution companies like Satellite and Cable.

In between those two experiences, I was fortunate to spend three years at the National Football League as the Chief Financial Officer.

Peter: Okay, so you’ve been at SoFi now for just a bit over a year and I’m curious to sort of get your take on how it’s been and how has SoFi changed over the last 12 months.

Anthony: Sure, I’m really proud of the fact that we’ve made, since we spoke last year, and where we are now and having a couple of important things that tied back to our 2018 priorities and what we’re focused on in 2019, if I could. The number one priority when I arrived at the company was to ensure that we stabilized the core lending products in anticipation of an interest rate environment that would be quite (garbled) over the coming years and we focused on per loan economics, variable profitability so that the loans can be durable as interest rates increase and the economy slowed.

We meaningfully improved the approval and economics on a variable profit basis over the course of the year focusing on better efficient pricing, a tighter credit model focus and then really fine tuning our marketing initiatives to ensure that we’re getting high quality credit, but also managing customer acquisition cost.

On the operation side, there is an opportunity, not just to drive up efficiency in our operational co-spaces, but also to improve the value to our members that were applying for loans and shortening the time to fund and really drive meaningful increases in time to fund across personal loans and student loans in the order of magnitude on personal loans of 50% and about 30% on student loans.

In addition to that, we made a really tough decision to pull back a little bit on our home loan business or mortgage business as the experience that we were operating under wasn’t up to what we thought was adequate for our members, and so we’ve made a number of different decisions that put us in a great position now in 2019 to really step on the gas and double that business. So that was the number one priority and I feel like the team had to cover up the ball.

Number two was really accelerating our path to providing a border array of products. Our Mission is to help people achieve financial independence and realize their ambitions and we think in order to do that, we have to help our members, current members and new members, get their money right across borrowing, saving, spending, investing and protecting.

We’ve primarily been a lending business up until the point when I arrived in March and I really wanted to ensure that by the end of the year we are in a position to be able to offer SoFi Money which is now available to everyone to help on spending, saving and paying and also launch SoFi Invest which delivers on the investing component of getting your money right and they were also able to integrate in on the insurance side and to protect some partners. So we now have SoFi Money that’s available to everyone through the mobile application. SoFi Invest is available to everyone through the mobile application, in addition to insurance.

The team did a phenomenal job of not just building the right roadmaps to get us to this point, but actually, you know, building the code, deploying it and really building an integrated mobile experience. Our mobile application has been re-launched, the rating had been a 2.8 in the IOS Store when I started; it’s now a healthy 4.9 and 5.0 scale in the IOS Store. The mobile app is ranked in the top 80 under finance category and in the Google Play Store it’s ranked on the top 60.

We’re really proud of that and we’re seeing meaningful downloads per day organically on the mobile application which is helping fuel the demand for SoFi Money and SoFi Invest and ironically, even for our loan business so we’re really excited about that. And then our third priority, just to hit on very quickly, was to build the foundation of what the membership experience will be like and to build the principles of what we mean by member experience and we were able to do that in the first half of our position and we will start to see that unfold in the mobile app throughout the year, as well as behind the scenes in how we approach pricing, customer service, member events and member services & benefits.

The last thing, which, you know, was probably the most critical to the company’s long term success was working out our culture and making sure this was the place that people really wanted to work. We feel passionate about our Mission, we established 11 Core Values, they’ve been shared throughout the company, they’re integrated into our day-to-day functions and business, as well as evaluation of talent and retention of talent and promotions and we just scratched the service on the possibilities, but I’m really proud of what we have accomplished on the cultural side as well.

Peter: Okay, okay. So there’s a lot there to unpack and I want to actually spend a little bit of time on the different segments here. Starting off with student loans, because that’s really still been….I imagine it’s still sort of the biggest part of your business, but you guys invented student loan re-financing and, you know, you guys are, by far, the largest In think in the entire country, banks and non-banks, as far as everybody goes. Is this still the main engine of your growth as far as revenue goes and if so, like how do you continue to grow, you know, to what’s becoming a fairly mature segment.

Anthony: Yeah, I’d made a couple of points. We are more diversified on student loan re-financing from a member activity standpoint. It’s going to be the case that will have more members and SoFi Money and more members in SoFi Invest and SoFi Advice than we have them either student loan re-financing or personal loan re-financing. We’re not there yet, but by the end of the year we’re going to be pretty diversified across all over those different products.

Quite frankly, I anticipate that we’ll be relatively even across all those products by the end of the year and as 2020 unfolds, it’s likely going to be the case that we’ll see SoFi Money and SoFi investing larger than the number of members in student loan re-financing as well as personal loan financing. But, today, student loan re-financing is still a significant percentage of our overall revenue. I was referring before to the number of members that we have and that and personal loans are the two biggest drivers of revenue in totality. They’re both expected to grow quite meaningfully in 2019.

We expect to see an acceleration in our revenue growth given that we focused on quality in 2018 over quantity to ensure that our loans are durable. Now that we have that right quality measured by variable profitability and return on equity, we can really step on the gas within the credit and quality box that we’ve created. So, we expect decent growth from both those businesses today and an acceleration overall in revenue because of the opportunity we have to grow each of those businesses.

Peter: Right, and then you said….you mentioned before with mortgages, obviously mortgages….the loan sizes are much larger, is this something you’re also going to be trying to grow significantly in 2019?

Anthony: We think we have an opportunity to double the loan volume within home loans or mortgages and that will be a nice increase in revenue relative to 2018. Our members really want to have a relationship with us beyond one product; we’re seeing the cross buying already happen. On average, it’s been the case historically that about 40 to 50% overall mortgages are actually taken out by existing members. We’re seeing some really interesting trends of cross buying in our other products that we’re excited about and I think we’ll create a competitive advantage for us over time.

Peter: Okay, so let’s switch to SoFi Money and full disclosure, actually, I am a SoFi Money customer, I joined the waiting list as soon as I could and I opened my account, I think it was in January and I do….I think you’ve done a really nice job there and having a pretty compelling offering.

But, what I do want to know is like obviously this is a product that is competitive out there, but you’ve got a lot of competitors as well. Two questions, one, how are you actually going to make money on this product because you are giving very high interest rates and you’re can’t hold deposits yourself, as least as of yet. I guess maybe we’ll start there, how are you planning on making money on this product?

Anthony: Yeah, I’d make a couple of points. First, I’d say we’re looking at all of our products holistically, our products are member relationship and how those relationships translate into our overall business model and putting revenue and cost. So there’s an inter-relationship between all of our products that we’ll focus on over the long term.

But just to answer your specific question, SoFi Money, there are two primary revenue streams that we generate from SoFi Money today and there could be more in the future. The first primary revenue stream is the interest that we make on your deposits through a partnership that we have and that’s pretty common of both existing banks and new bank competitors, and the second revenue stream we generate is an exchange rate on your debit transactions. We do not charge any other fees from an account fee standpoint. ATM’s are rebated so you have complete access to your money to spend where you want and to be able to spend as much as you want.

The important thing about our product is that we’re giving you a really high interest rate at 2.25% and no requirements on direct deposit or advance minimums and you have access to that cash when you need it, where you need it to be able to pay, whether it’s person-to-person payments, Bill Pay electronically, Bill Pay…we’ll send a check for you, you can transfer money in and out of the account to your other accounts and you have the functionality of a debit card, ATM card and, of course, the integration with Apple Pay and Samsung and Google Pay. So we’re trying to give you the best of both worlds as it relates to how to manage your money and spending, saving and paying.

Peter: Okay, okay, that makes sense. So when I…I opened up my SoFi Money account which I have right now and you can see you’re pushing other products here. Right underneath it is SoFi Invest and I want to get to that in a second….like obviously the student loan product/personal loan product, they’re fairly high margin products and you talked about it yourself and you already said that you expect large numbers of people signing up here, do you expect significant cross sell between SoFi Money and then your loan products?

Anthony: Yes, absolutely, we’re already observing…today, we’re not trying to bring any new product marketing in the app to a SoFi Money member or SoFi Invest member and people are using the application assigned for those products by using those products. They’re becoming aware of other products and then they’re using a second product. So it’s very small numbers in total, but the observation on a percentage basis is much better than we thought it would be and it’s very encouraging.

So our strategy is to really put the member at the center of what we’re building and deliver to them the best borrowing or saving or spending or investing or protecting experience that we can. Our hope is that as we do that and they become comfortable with the brand and they trust the brand, they’ll be aware of the other services that we’re offering across those five activities and then they’ll consider those brands when they’re making that choice and they’re really signs that that’s working.

Peter: Okay, so then with SoFi Invest….actually, I can see there’s a button on your Home Page with SoFi Invest so it’s clearly something you’re also pushing hard and it seems like…..you know, you’ve launched a brokerage business. I mean, I feel like in the last month there’s been news coming out of your page almost every week pretty much where you’ve got the brokerage business, you’re talking about zero fee ETF’s, you’re talking about crypto trading in partnering with Coinbase.

So maybe let’s take a step back and say, what is SoFi Invest kind of ….what are you trying to achieve? Are you trying to be the one-stop shop so no one ever has to go to Schwab or Fidelity or Vanguard, whatever, what are you trying to achieve with SoFi Invest?

 

Anthony: Yeah, so I tie it back to our overall job to be done and then our Mission. When I mention job to be done, I’m really applying to our differentiation the concept that Clayton Christensen used in his book, Competing Against Luck, in that we ask ourselves, why will a member hire us versus others and we think our job to be done in that hiring decision by a member is to help them get their money right. If we help them get their money right they’ll reach financial independence and realize their ambitions.

In order to help them get their money right, we’re focused on all the activities that you do with the money as opposed to products or businesses and those activities are borrowing, saving, investing, spending and protecting. So our initiative behind SoFi Invest is to help people invest better and get the money right because they’re investing better in addition to their other activities. We think about within that category of SoFi Invest we want to offer a fast, easy to use solution; the fastest place to open an account, the fastest place to fund, the fastest place to buy a stock or an ETF or to invest in a Robo strategy, the fastest place to sell, the fastest place to do research; always accessible, always convenient.

Second is selection and so we’re focused not on just offering Robo advisory strategies, but also offering single stocks, ETF’s and our own ETF’s, for that matter, to fill-in a void where our direct target of millennials and Gen Z may have an area or pick an interest that’s not been met by this selection that’s being offered by others across the investing universe. So the first is fast; the second is selection; the third is content and the fourth is convenience.

As we release the content which are broad strategies; everything from education to helping for planning and so we do provide on the platform, on the mobile app articles and blogs about investing, about dollar cost averaging and to educate our members. In addition to that, within the app, you can click on the Membership tab which is right on the Home toolbar in the bottom next to the Home tab and choose to sign-up for a certified financial planning session with one of our certified financial planners.

You can schedule that right in the app and use your phone to conduct that conversation and so it’s not just the products that we’re offering in a fast way, but also supplementing the content across the spectrum of everything from quotes and news about companies, the news about business, to regional content to also live on planners.

And then last, convenience, we want people to be able to access their accounts from any device at any time. There are a number of other convenience factors that we’ll add-in over time in addition to the other four differentiators that I mentioned.

Peter: Right, right. So I want to switch gears a little bit and talk about regulation, you know, you guys…it was before your time at SoFi, but you had an ILC application out there which you guys pulled and clearly, you’re sort of ….you are entering into so many different areas of financial services and I’m sure it would be nice to have access to the banking system directly. So where are you at with bank charters today?

 

Anthony: Sure, 2019, and we have five priorities. The first is to build a mobile first/member first experience and drive the penetration of SoFi Money, SoFi Invest and SoFi Advice. Our second key priority in 2019 is to build out a membership experience more broadly and more overtly to members as they come on the platform. Our third is to continue to drive efficiency and effectiveness of our lending platform and as we relate to that, we will evaluate different ways to lower our cost of funding and financing.

We’re really fortunate today in that we have a three-layered approach to financing the loans. We have our own capital which is, as it has been publicly reported, $2 Billion of equity has been raised. In addition to that, we have partnerships with a number of banks, over 20 banks that provide us nearly $6 Billion of warehouse facilities and we also have a very important unsecured line of credit that’s over $500 Million. There is an opportunity for us to lower our cost of funding by building a deposit business and having the company as a whole being an IDI, insured deposit institution.

There are a couple of paths to go down to relate to that. we’ve evaluating those paths, whether it’s national banking charter or an ILC and the team is in the process of really thinking through all the strategic implications of either one. We haven’t made any decisions either on either one or actually going forward to try to become an IDI type of company, but it’s clearly an opportunity for us to meaningfully lower our cost of funding by 50%.

Peter: Sure, sure. Okay so then, when you look at the broader market today you’ve got all these different….you know, challenger banks, neo banks I guess you call them, like Chime, Stash, Varo and many others coming; Europeans coming, Revolut, Monzo and N26 and then you’ve also got the big banks. Many of them are putting out digital offerings directly to sort of the target market of millennials and Gen Z. So who do you see as your main competitor today and how are you differentiating?

Anthony: Yeah, I don’t think about it in that construct. I think about it in the construct of who provides better borrowing, who provides competitive abilities to spend to be able to invest, to be able to protect. So we think about those activities because those activities are trying to help our members do better and, as you can imagine, there’s a long list of companies under each one of those five activities. So there’s no one competitor, it’s we’re competing against that activity which is offered not just by traditional banks, also fintech companies and then what I’d say is increasingly and probably non-fintech companies.

Peter: Okay, okay. So basically then if you look at obviously the SoFi Invest, you’ve got to make something really compelling because you’ve got people offering free stock trading now, there’s free mutual funds, I know you guys have the free ETF’s so we’re looking at that specifically then and it’s a very sophisticated space already with many homely entrenched players.

I mean, like the zero fee ETF, you know, got a lot of publicity, I’m just curious about how you sort of make a dent in the millions and millions of customers out there. As you know, it’s not easy to get people to switch, are you focused primarily then, with this particular product, on people starting like an investment program for the very first time, are you trying to get people to switch, or both?

Anthony: They are core target and I use the word core purposely. Our core target for SoFi Invest is a new or beginning investor. And our goal, our goal is to help educate them on the benefits of investing to get their money right, our goal is to help educate them on how to actually invest and to, over time, become more confident in what they’re investing in and what they expect from a performance and a risk standpoint.

One of the reasons why we’re offering, you know, we’re in the path of offering stocks and fractional shares and one of the reasons why we’re offering unique ETF’s and one of the reasons what we’re not charging for trades or charging on the ETF’s that we’ve announced and also offering Robo advisory is to make sure that as we start to drive a connectivity point between us and a potential investor, new or beginning, that they have the broad selection they would consider.

Some want to buy stocks, some would prefer to start with the Robo account, some would prefer to buy a small amount of something that they already buy as a consumer, but actually the cost of one share is too high relative to what they would like to pay. As an example, Amazon is a company that has stock priced for one share is a really meaningful amount of investment and so being able to buy that in a fractional share is unique.

So we want to help these new and beginning investors, take the money that’s sitting in their cash account or their money account that’s not earning interest, that’s not really compounding over time and solely educate them on buying things that they like and being confident in what investing really means and taking them from some that’s very familiar like in the case of a consumer that spends a lot of money on an Amazon and having them become an owner of one of those companies that they spend a lot of money on and then over time as they get confident and understand what investing means, bringing them along the path of a more diversified portfolio and at a risk adjusted return that meets their individual long term financial goals.

The fact that we have stocks or we have fractional shares, we have ETF’s, we’ll soon have our own ETF’s and we have Robo and there’s no charging for trading or commissions is actually very unique, reduces the friction and gives them the assortment they would consider across the range of things that they would do first.

Peter: Okay, so I want to get back to the lending business for a second and talk about securitization. You know, I went back and looked at some of the numbers from PeerIQ last year and you guys were more than 50% of the total volume that went through in the online lending space in the securitization markets in the….you know, talking about consumers and student loans. So do you still look at securitization as really the absolutely critical funding source as you thought when you look at expanding and increasing the volume of the loans you put through?

 

Anthony: You know, we’re evaluating the varied different types of financing sources for the loans. You know, we obviously cannot use SoFi Money deposits or SoFi Invest deposits for financing source without a bank license at SoFi, either an ILC or a national charter so at some point, if we have an IDI organizational structure and a charter we could consider that, but until we do, it’s really not even a question.

Peter: Okay, okay, fair enough. So then you haven’t mentioned it…I presume this is not on the horizon, but I know the listeners will want me to ask this question, IPO plans for 2019, anything, where are you at with potential future IPO?

Anthony: It’s not a priority and we have no plans as it relates to that.

Peter: Okay, okay, fair enough. So then I feel like you’ve got so much that you’re trying to do here, you know, it feels to me, the news comes out all the time, I’m curious to see….like as you’re managing the different areas of your business, I mean, where do you spend your time personally? Are you really…..and obviously you’ve got a strong investment background with Goldman Sachs, obviously you spent time at Twitter, but like what areas of the business are you most connected to right now?

Anthony: I don’t think I would highlight one area as it relates to the businesses or being more connected than the others. They’re all in different stages of business formation so I’m spending  equal parts on all the five different areas that I mentioned. Outside of the day-to-day running of those businesses, I’m spending a significant amount of my time on recruiting great talent. We’re hiring a significant number of people in 2019 and one of the major areas of focus within is we’re re-hiring these great product engineering and design people.

We’ve launched a lot in a year and we have very ambitious clients that continue to shift more and more innovation every week and so that’s the area of the company that I’m most focused on, attracting and retaining great talent. I‘d say the second area outside of the businesses and attracting and retaining great talent is on partnerships. We teach you partnerships as they can accelerate the path for and making sure that we have the right top-to-top relationships with key partners, both current partners and future partners.

And then, last, really focused on building out the best culture in the world, our goal is to have the best culture in the world and we do not believe it takes any special type of innovation or technology or access to capital to get there. It really requires leadership, alignment and accountability and we’re committed to having the best culture in the world and making sure those three things are true and so I spend a lot of time on that as well.

Peter: Okay, so then where are you hiring people? I mean, I know you’ve got the San Francisco office, Healdsburg, I think there’s something in Montana, I think from memory, or Idaho, where are you hiring people today?

Anthony: Yeah, geographically, we’re hiring from all of our current locations across the eight different cities that we have physical locations in, we’ve had a small office in Seattle in addition to what we have already. As it relates to people, we’ve been really fortunate to be able to hire really experienced people from leading technology companies in the United States and the leading financial companies. I’ve been quite pleased with our ability to attract some people that have achieved significant things from the consumer Internet and technology world, in addition to getting some really experienced executives from the traditional financial world.

Rich Garside is the Head of Global Operations, thirty plus-year veteran from Citi; Assaf Ronen is our Head of Product who came from Amazon where he was a key leader driving the growth of Alexa Shopping; Tony Donohoe who came from Expedia as the Head of the Expedia brand CTO, he is our CTO; Michelle Gill is our CFO who was a Partner at Goldman Sachs and then was an investor in Structured Products at TPG.

We’ve also been able to hire great business unit leaders in each one of our business units from the walks of the financial services industry so I have been really pleased with our ability to find really talented experienced people across the big diverse area of industries.

Peter: Okay, okay, we’re almost out of time, but what is the total head count today?

Anthony: We’re about 1,400 people.

Peter: Okay, okay. Two more questions before I go, one real quick, are the challenges of SoFi had in 2017, do you feel like….obviously, it’s well behind you now, are you still asked about that when you’re talking to new hires, when you’re talking to reporters or do you feel like it’s now ancient history?

Anthony: I’m definitely not asked about that. I’m more asked about how do you build a culture, are you committed to build any culture, what’s the mission of the company, is the company, as whole, passionate about that mission, where do you want to take the business over the next five to ten years as opposed to the next year.

I would say those are the three biggest focus areas for the people we’re trying to hire, generally, and then when we get into specific cross functional areas and expertise like technology, there’s definitely a focus on innovation and using new technologies and how to think about the impacts of those technologies over the long term.

And then on the financial side, without a doubt, there’s questions about regulation and our ability to operate in a regulatory environment and as a regulated entity, which we already are, given that we have loan licenses by state, in addition to really understanding the amount of impact there’s in the business because of regulation, all of which we think is reasonable and has allowed us to operate at a really high pace of growth.

Peter: Okay, so last question, I’m sure you’re going to tell me anything that hasn’t been announced yet, but what part of your business should we expect the most future announcements this year? Where are you really focusing on innovating the most?

Anthony: I tie back to our priorities so number one is continue to innovate on being a mobile member first company with leading products in SoFi Money, SoFi Invest and SoFi Advice and so that’s the number one priority and I would put that at the top of the list, but right behind it is building out the member experience in a transparent and more over way to the outside world. Third is our focus on ensuring that we continue to drive really fast, efficient and effective lending with our existing and new members. So those would be the three key business focus areas.

Peter: Okay, Anthony, let’s leave it there. I appreciate your coming on the show today.

Anthony: Thank you very much for having me, really appreciate it.

Peter: Okay, see you.

SoFi is such a fascinating case study to me, you know, starting out as really a monoline lender in student loan re-financing and not just going into other areas of lending, but other completely different areas of finance. You know, I always thought that the secret to SoFi success was the fact that they were able to execute so well, particularly on the lending side of the business.

After talking with Anthony, you can really see sort of that military background which he didn’t talk about, but you see that sort of no nonsense execution type mentality that Anthony is bringing to the table here. I think it is going to be one of the most fascinating things to watch over the next few years…is to see how SoFi evolves, can they be a success in all these different areas of their company. I’m certainly not betting against them, it’s going to be interesting and I will be following along like everybody else.

Anyway on that note, I will sign off. I very much appreciate you listening and I’ll catch you next time. Bye.

Today’s episode was sponsored by LendIt Fintech USA 2019, the world’s leading event in financial services innovation. It’s happening April 8th thru 9th, at Moscone West in San Francisco. It’s going to be the largest fintech event held in the Bay Area in 2019. We’ll be covering online lending, blockchain, digital banking and much more. You can find out all about it and register at lendit.com.

PODCAST TRANSCRIPTION SESSION NO. 192 / DOUGLAS MERRILL

Welcome to the Lend Academy Podcast, Episode No. 192. This is your host, Peter Renton, Founder of Lend Academy and Co-Founder of the LendIt Fintech Conference.

(music))

Today’s episode is sponsored by LendIt Fintech USA 2019, the world’s leading event in financial services innovation. It’s going to be happening April 8th through 9th, at Moscone West in San Francisco. We’re going to be covering digital banking, blockchain, financial health and of course, online lending, as well as other areas of fintech. There will be over 5,000 attendees, over 250 sponsors and registration is now open. Just go to lendit.com to register.

Peter Renton: Today on the show, I am delighted to welcome Douglas Merrill, he is the CEO and Founder of ZestFinance. Now ZestFinance has been around for a few years now and in that time they have really built a reputation as one of the world leaders when it comes to the development and deployment of AI tools in the credit and underwriting space and their ZAML software, which we talk about, has really created some breakthroughs around explainable AI.

We go into that in some depth, we talk about some of the implementations that they’ve done, we talk about the data that goes into some of these models which makes it more predictive and we also talk about Douglas’ relationship with regulators and much more. It was a fascinating interview, I hope you enjoy the show.

Welcome to the podcast, Douglas!

Douglas Merrill: Thanks so much for having me.

Peter: Okay, so I like to get these things started by giving the listeners a little bit of background about yourself. You have had an interesting career so could you give us some of the highlights.

Douglas: Yeah, I think most people would describe me as having a somewhat random career. (Peter laughs)  I’ve got a PhD from Princeton, Princeton gave me a PhD in AI a long time ago, then I worked at a place called the RAND Corporation which is a think tank in Santa Monica, California where I did a lot of fun work, but notably it’s on the beach so you could walk out the back door and go on to the sand to go swimming and I spent a lot of time that I should have been in meetings out that door. (Peter laughs)

Peter: That must have been fun.

Douglas: Yeah, it was great fun, it just maybe wasn’t great for my productivity.

Peter: Right.

Douglas: Ultimately, I ended up at Google where I was Chief Information Officer for several years, but probably my most random job in my background was I was the Head of EMI Records, which was the fourth largest record company in the world when I was there. It has since gone bankrupt, but it went bankrupt well after I left; I want to make sure that’s very clear. (Peter laughs) After EMI, I founded Zest, I’ve had a fun career doing all kinds of interesting things with all kinds of smart and fun people.

Peter: Then so tell us a little bit about ZestFinance and…maybe start with how you got the idea for the company.

Douglas: I founded Zest in about 2009 or so, with a mission to make fair and transparent credit available to everyone. The operating idea was credit underwriting was a (inaudible) of modern life and yet about 80 million Americans either have no relationship with a bank or a poor relationship with a bank, 800 million Chinese are in the same situation, the numbers are similar for the EU and even more so for Africa, and I was interested in a world where so much has changed in the last couple of years in technology, particularly. How is it the case that underwriting hasn’t changed since 1950?

Before 1950, to get a loan you basically would go to a bank and you’d sit across the big mahogany table from a man and they were always men and they were always men wearing blue suits and red ties and you say, hey, I want a loan. And that man would say, oh, you know what, my kids played basketball with your kids, you’re a good person, I’ll give you a loan. That worked great unless your kids didn’t play basketball with his kids in which case you didn’t get a loan, that’s kind of unfair. Two gentlemen, one named Fair and one named Isaac, whose names later came together as Fair Isaac had a brilliant idea of using logistic regression and credit bureaus to come with a standardized credit score and that just changed the world.

I think it’s one of the most important innovations of the 20th century and credit availability went up markedly, losses went down markedly. It created this amazing, amazing positive outcome and I think everyone should thank FICO for the structure of the world today, but FICO has some weaknesses and the primary weakness is in the math itself. Logistic regression works well if you have every piece of data that you need and it’s all correct. In the event you have missing data or it’s incorrect, logistic regression fails in a kind of unpredictable manner.

I believed when I founded Zest that the primary reason that 80 million Americans were having trouble getting credit is that in many cases, on their credit bureau, the information was either missing, this is sometimes called a thin file problem, or there were errors. And so some number of them were actually good credit, they just didn’t have good FICO scores and we could use the math that we built at Google to do a better job of finding that and that turns out to be true.

In the last ten years, our clients have used our software to make material improvements in credit availability. This is not a ding against FICO, I still think FICO is the most important company in credit today, but I also think that lenders have more options because of machine learning.

Peter: Okay, so then…I guess you started obviously doing this. This was before really anyone was really talking about, you know, machine learning and certainly it wasn’t top of mind of many people in the credit space. So how did you kind of start the company? I think I read somewhere that you actually made loans yourself initially so tell us a little bit about those early days.

Douglas: Yeah I mean, I think people who came out of the machine learning companies, you know, places like Google or Amazon, would have recognized my company as another ML company so I feel like I came out with the notion that I wanted to build an ML company in credit. However, I needed to demonstrate to the world that that made sense so the way we did that is for a couple of years we actually made loans using our algorithmic structures and our tools and, you know, they worked pretty well and then we ultimately stopped but the problem with being a lender is it’s capital inefficient, it takes a lot of capital and the capital is expensive.

Peter: Right.

Douglas: The reason that banks make loans is they have very cheap capital so I didn’t really want to do that long term. I did it long enough to demonstrate our tools and then we ended up serving a couple of clients who themselves made loans and we did that in a fairly bespoke manner for quite a while and then when we moved to our broader product which was the same across the broader market and you can kind of see the trend there as the financial world caught up with, oh, I understand machine learning, I understand how these tools might work, we progressively got more and more towards the SaaS model that I actually wanted to start when I founded Zest.

Peter: Okay, so then, I’m just still curious about those early days, I mean, how were you able to convince other lenders that your solution was better than what they were currently doing?

Douglas: Ultimately, that’s just math. So you give me a sample of loans that you’ve made, whether it was a good loan or a bad loan, and we’ll build a model for that. And then you give us a set of loans and you don’t flag them, so you don’t tell me whether they’re good or bad, and I just predict whether they’re good or bad and then you go count…

Peter: Right.

Douglas: …tell me how many the model was right with, how many was it wrong with, ultimately that’s just math and it’s pretty well understood math. Our tools, we do that computation automatically, we do a bunch of economic parsing automatically so you can say, oh, if we had done this model we would have saved $100 million in losses, or would have gained $40 million because of increased approval rates. Those things are just math.

I think harder than that is getting people to sort of think through, wow, you’re going to use 500 variables instead of 20, we all understand 20 variables; 500 variables, hey that’s a little scary. It just turns out to really help in those cases where you have thin files or you have erroneous data. Having more signals, more variables helps reduce the impact of those incorrect things.

Peter: So then let’s talk about that for a second. What are some of the data points that you’re using today, or maybe even back then, what were the data points that you used, I mean, maybe just give me some examples. I know it’s not just one data point, there’s hundreds, as you say, but what are some of the examples of that that you found really helped lift the performance of the model?

Douglas: So one of the things which is true when you have 500 signals is that really, really good signals, still don’t matter all that much because every signal is worth, you know, 1/5 of 1% so a great signal is worth a very small amount. Early on, we discovered that people who put their name in in all uppercase were substantially riskier than people who put their name in correct case. So for example, if I put my name capital D O U G L A S, I’m much higher risk than if I put capital D lowercase… o u g l a s, I just misspelled my own name which is fairly funny (Peter laughs).

So if I fix that, I don’t exactly know why that’s true. I can make up a story that oh, maybe people who are putting their name in proper are better rule followers but your applying kind of post hoc reasoning to something you don’t know why it is, but that’s a real signal in a real model. Similarly, one of our recent clients discovered that if you put in the company name that you work for, including the company type so instead of putting in ZestFinance, you put in ZestFinance, Inc., you’re a higher risk. So being more correct in the company name increases your risk, well, why is that? Well, you don’t really know, but maybe that increases the likelihood that you’re a bot because no human uses “, Inc.”

Peter: Right, right, yeah, that makes sense and as you say, it’s not like someone…obviously there are many, many good people will actually put that in like that, but it’s just, as you say, it’s one of 500 signals. If the other 499 signals or 498 signals are good, it won’t make any difference, right.

Douglas: That’s correct because you end up adding them all up so if that one is a little bit wrong, well, alright the others are probably a little bit right and ultimately, it gets zeroed out in some sense.

Peter: So then one of the big things today that is talked about a lot when it comes to AI is this thing about explainability and you know it’s something that I know has made many banks and actually many lenders, in general, reticent to embrace this fully because you’ve got to be able to provide a reason to the borrower why he was declined. So tell us about a little bit about the advances that you guys have made in explainability.

Douglas: So first of all, it’s a valid worry because the banks in the US are required to give adverse action notices. If they decline you, they have to tell you here are the top five reasons why we declined you and it turns out that process is not ideal, but it’s still required. Also, you’re required to periodically demonstrate that you don’t have a disparate impact problem where you don’t tend to give loans more to men than women or any other of the protected classes.

Doing those things requires understanding what’s in your model. Understanding what’s inside that logistic regression model is trivial, you just read the coefficients. Understanding what’s inside a score picker machine or a massive gradient boosting machine, those are hard so we really did need some big improvements in understanding how to describe what’s in the model. There have been over the last few years, some improvements.

For example, there’s some really simple technique called permutation impact where you just bury stuff and see what happens; it’s like when you bury one thing and it doesn’t matter, it’s probably not important. That turns out to be a pretty, you know, gross view of the model, it doesn’t have much kind of fine grain and it’s pretty hard just to run against big models, but that was a really big step forward where someone realized, oh, let me just pull on some strings and see what happened, good insight.

I think that increasingly the world is demanding a much finer grain understanding of what’s in a model because we’re increasingly caring about implicit bias and other topics around there where you could, from a potentially regulatory problem and from a moral problem, back into something where you might be disadvantaging groups that you don’t want to do and that requires a more fine grained approach. Arguably, a much more fine grained approach, and there’s some other things to it as well, but ultimately, you need to be able to use a tool better, you need to look across the table at your financial services client and and say, yes, I guarantee you will understand what’s in your model, you’ll understand how it works and that will be able to work within a real-time.

Let me give you an example about what I mean by real-time. So there were two amazing basketball players kind of in the 1980’s, one named Michael Jordan and one named Scottie Pippin, they played for the Chicago Bulls together. When they played with the Bulls together, they won, I think, six league championships, I think Michael Jordan got three or four MVP’s, he was the shooting lead for many years, he was just a star on those teams. So I often like to ask the people I’m speaking to, for a show of hands, who is the better player, Michael Jordan or Scottie Pippin, nobody ever chooses Scottie. That poor guy gets no respect. But if you look at what happens after they’ve played together it’s kind of interesting.

So after they play together, Michael Jordan goes to Washington Wizards and proceeds to have two massively losing seasons where nothing good happens to the poor guy and he retires. Scottie Pippin goes to the Trailblazers where he proceeds to have three seasons where they make it to the finals every year, they don’t win, but they make it a long way, Pippin’s got an MVP, Pippin has a great career.

Now you’ve got to ask the question, oh, hang on, who’s better, is it Scottie Pippin or Michael Jordan? It made a lot of sense in one context, the answer was obvious when they were together. In the other context when they’re apart, the answer is also obvious, but they’re different and really thinking through in a complicated machine learning model how to handle that difference is the core of the explainability problem.

Peter: Okay, so I guess say more on that like put it into a credit example. A customer can send an adverse action letter to their borrower declining them, how does that sort of translate?

Douglas: So today when banks send adverse action letters or send these decline notices they more or less take the reasons from one of the credit bureaus and they just sort of package them up into a physical letter and send it off. Some banks do a much more thoughtful job of this, but some banks, if they’re a little bit rote or whatever, that credit bureau said, I’m just going to pass on. In machine learning, it’s hard to figure out what those things should be, right, you’ve got 500 signals and they’re all relatively unimportant. How do you find the five that are most important?

So that involves using the permutation impact idea, taking 500 signals and randomly permute them against each other which requires something like 500 factorial computations which is a number larger than the number of atoms in the universe. It’s a very hard problem to solve that way. Then you look at the ones that bubble to the top that say, oh, if this number had been higher or that number had been lower, your score would have been high enough that we would have granted your loan and then you’ve got the five approval reasons. The problem with that approach is that you don’t have enough time to have more computations than there are atoms in the universe…

Peter: Right:

Douglas: That’s just hard and where I come from just hard is the problem you don’t want to solve. So there are optimizations, as you can do, that yield both fine-grained, better fine-grained solutions and are more computationally trackable, but that’s a silly thing for a problem of how do you understand high level interactions between signals, between variables to know which of the five that are more important.

It always comes back to the same question, but if you look at variables alone, i.e. you look at Scottie and Michael together, you see one picture of the world. If you look at variables together, like maybe not just signal one, but signal one and 100 together, you get a different picture, i.e. when Scottie and Michael played apart. Our position is you have to compute and use as many different, conjoined probabilities or if you will combinations, as you can, to try and make the best possible list to borrowers of what they need to improve to get a loan in the future.

Peter: Okay, so something that you would do is say, right, you don’t just improve these one/two things, you maybe improve these six or eight things because they’re in combination. I guess maybe we can…maybe that is part of what you’re offering and I want to get into this in a little bit, your Zest Automated Machine Learning product, but is it part of the output or part of the offering to be able to create these adverse action letters that make more sense or that make sense based on what the borrower wants to actually hear?

Douglas: Yeah, that’s a great question. Maybe just for clarity, I’ll take a step back and say what do the demo tools actually offer and once I get you that maybe it’ll be a little bit easier to talk about…

Peter: Yeah, sure.

Douglas: So there are basically three kinds of steps in modeling. There is the actual math itself, there is convincing yourself and those around you that the math is actually correct and there is putting it into production where it lives for however long you are comfortable with it living. You can get from Zest, if you want, a modeling environment in which you build models, but you can also use your own modeling environment or any number of other tools out there.

We do sell some AI little probes, little kinds of measuring things that pay attention to your model build and we use that AI to help you do something which is super hard which is convincing regulators of what you’re doing and why you’re doing it. After that process we build a model for you, an AI model to look at your AI model, they help you understand and build the model that for any individual applicant will yield the adverse action letters. You’ve got this AI running to look at AI and the AI and the AI that is looking, is what you ask for help when you deny an applicant. And then we built a bunch of technology when you put your model into production to use other kinds of AI to notice if your model is consistent and [inaudible].

One of the things which is true about many large machine learning models in production is that they’re a little bit kitschy, their answers switch a little bit and sometimes kind of for no reason they go running for a cliff and throw themselves off (Peter laughs) and people who haven’t read a lot on machine learning models might sometimes forget that and your model runs off a cliff and crashes to the rocks below and you’re still counting on it giving you loans.

Our clients get a set of tools that maybe can’t prevent the model from trying to throw itself off a cliff, but they tell you, hey, something bad is happening, stop making loans before the model goes south. And also allows you to track things like monthly economic impact and return, lots of sort of useful stuff to the business folks so ultimately, what we’re trying to do is build ML-based tools that are invisible generally, they’re sort of half in the background, but yield all this stuff that business and audit and regulators can use to run the business and not care anymore that the technology underneath has changed.

Peter: Right, right, got it. Okay, so let’s talk a bit about business cases. It would be great to hear maybe a couple of examples of…there was a big name that came out, I think it was just a few days ago, with you guys in the Wall Street Journal, but just maybe take us through a couple of examples of implementations that you’ve done with names we’d recognize.

Douglas: Sure, so I think the Wall Street Journal, a while ago, outed Synchrony as a client of ours, so that’s an old one from like 18 months ago, 24 months ago and in that they described a very large amount on the order of several tens of millions of savings so that’s like a name you’d recognize and it’s the same process, right, the model was really good, their models were amazingly good and then this kind of monitoring stuff that we did.

The announcement you were referring to a few days ago was with Discover, obviously again, an amazingly talented organization. We’re super proud to be their partner and they’re using our tools to basically, their goal was to get a handle on increasing losses and our tools have helped them get a handle on that and also helped them interact with the regulators on that point and they’re in production or moving to production to do the same thing, around like is my model okay, is it healthy, etc.

So you get this case where they’re obviously quite talented modelers. The business case they were focused on was, hang on, we’re seeing some…a little bit erratic increase in losses, certainly not disastrous, but not the trend you like. So they built models on our tools, we helped them build the regulatory and audit documents for those models. When I say we, I say like this AI, which was monitoring their model build, built these things for audit and regulatory and then the model is in production with our other AI kind of bounding it to keep it away from the cliff and the rocks below.

Peter: Okay, so then when you’re going into these companies, is it…someone like Discover, do they already have like AI models in place, or they’re just sort of using…I imagine there’s still plenty of financial institutions using sort of more of a linear regression type models even today, I would suspect, so what is the process like when you go in and I presume you can work with someone who’s got a very advanced model and somebody who’s got a very rudimentary model, is that correct?

Douglas: That’s true, and lots of financial institutions still use a linear regression or logistic regression, some actually just use a score from a credit bureau so that’s sort of like the minimalist approach. We find that across the spectrum, from there all the way up to financial institutions that are actually working on machine learning themselves that the tools that we provide add a lot of value; we’re just describing them in a different way. So if you’re a financial institution that’s just using a score, you don’t have a lot of data lying around because you’re just using a score and so we might not be able to build a model or you might not be able to build a model day 1 because, you don’t have the data.

You might need to do what’s called a retro and get data from a credit bureau, or you might need to do a testing plan to generate some future loans and allow a model to be built so that might be a different process. If you are using a logistic regression you’ve got data lying around and some companies that use logistic regression for underwriting also have other interesting data like…maybe they have phone call data, maybe they have collections data that isn’t currently being used in their underwriting because it’s very hard to use that data in underwriting. But, machine learning models and the models that people build with our tools can use that kind of data.

So for those folks who might say, yup, give us your underwriting data and oh by the way, let’s get some of this data from underwriting, excuse me, from collections, let’s get some over here from call data and let’s use all of that stuff to build a model,  which gives us much more information, much more signals; the models are better.

Finally, the organizations that are building their models today, often have really, really great sets of data and sometimes they’ve got data lying around that isn’t used, etc. and where our tools add value. It’s helping them get that out of the research lab through the regulatory folks and in the production. So if you think about it we’re sort of adding three different kinds of value which map roughly to the three parts of our software.

Peter: Okay, so then just on that, someone comes to you and they’re just using a FICO score and that’s pretty much it…so you don’t have like an off the shelf model that you can provide them or do you? You said they need to go out and sort of get data from credit bureaus, whatever, so you can build the model. So you don’t have something off the shelf that you can just provide them?

Douglas: No, we don’t provide generic scores, it’s one of the powers of places like FICO that they have these really pretty generic scores. We don’t have generic scores or generic models, what we have are the tools to help financial institutions move into the machine learning future. Where presumably they’re going to use scores from great places, but they’re also going to have more complicated models around those scores.

Peter: So then are you finding more and more institutions already have decent machine learning models in place that you can certainly improve upon, but they’re already doing things reasonably well, or in the financial space are people still pretty backward for the most part?

Douglas: I think almost all banks have at least one person or one group doing research on machine learning, but they’re mostly focused on the math today so getting from that research to production is quite hard. That said, a huge number of financial institutions have, high quality fraud institutions notably like FICO’s Falcon which are machine learning products, they just don’t look like it to the banks. So in the underwriting space there has been not a lot of progress in figuring out how to get the mathematics from the laboratory all the way into production.

Peter: Right, right, that makes sense. So you see a lot of partnerships now that are going on between banks and fintech platforms, whether you’ve got Avant or Amount now doing…they’ve announced a couple of decent sized banks that they’re working with…there’s obviously Upstart and others that are coming in as well. How do you sort of play into this shift that we’re seeing between fintechs and banks, the partnership model that we’re seeing?

Douglas: I think it’s important to differentiate kind of a white label kind of approach with a tools based approach so you look at what some of the great partnerships have been. Both Avant and Upstart are really great companies, Upstart founded by Dave Girouard, who I was privileged to work with at Google for many years. So those guys tend to focus more on a white label approach that says, hey, come over here, write me a check and I will put up an underwriting engine for you and that serves certain kinds of needs extremely well, that’s not what we do.

What we do is give you the tools to build your own models so in some sense, if you want to think about it in, you know, aphorism terms, a white label partnership is I’m giving you a fish. What we do is we’re teaching you how to fish. Each one has really big advantages and really big disadvantages. We’ve proposed that we want to create organizations, develop an organization, grow from a handle on the side of a financial institution and the easiest way to do that is to actually provide tools. Now we have to provide training and support and a bunch of other stuff as well which is the downside, but that’s why we’ve chosen the way we’ve done deals so our partnerships don’t look like the kind of white label deals that you’ve seen a lot in the press.

Peter: Right, right, got it. So we’re almost out of time, but a couple of things I want to hit on before I let you go. I’m curious about how you interface with the regulators. You know, there was certainly…a lot of attention was paid when Upstart got their no-action letter from the CFPB because that sort of was the first movement by a regulator saying that, hey, this is…we’re interested in actually, you know, exploring and accepting some of these new changes, but some of the things that you’re talking about…I’m curious, it seems like it’s beyond some of the things that the no-action letter talked about so tell us about your relationship with regulators, how you’re engaging with them.

Douglas: So we spend a lot of time with the regulators because ultimately, our clients need assurance that the regulators understand and I’ve done things like…I’ve done machine learning training for all of the members of the CFPB, I did ML training for the examiners of the OCC, same in the Fed, same in the FDIC so I spend a lot of time with the regulators. In fact, we drafted a set of, you know, addenda to the FAQ used by the examiners of all three of the major bureaus to sort of make it a little bit more possible for them to ask the right questions about machine learning and get the right answers.

The short answer is everyone believes that ML is the future, and everyone we’ve talked to believe that ML could be the present, but they don’t view themselves as the (inaudible). There are some things that we have to work through. My perspective is that people who say that the regulators are inherently blocky and they’re really retrograde actually aren’t spending any time talking to them. There are amazing folks who are working at the regulatory agencies because they believe serving the US government is an honor and that protecting consumers is an important moral duty. These folks are not trying to take us back to the 70’s, they’re hoping to prevent 2008 again. So my experience has been actually quite positive and quite frequent, I’m in DC a lot.

Peter: Right, right. Okay, so last question then, I’m really curious about where you think this is going, I mean, obviously, things have changed a lot in the last five years and I think in the next five years, I imagine, it’s going to change even faster so take us through where…how good can these models get? Where will Zest be and sort of your abilities be in five years time?

Douglas: Five years to a startup is an infinite window (Peter laughs) so it’s quite hard to predict five years in advance. I think it is hugely indicative that Discover went out with their press release saying, hey we’re partnering with Zest. I’d say that the classic big monster dominant quality institutions are starting to pay attention and I expect more of those and for various reasons I expect there will be more of those.

So I think the next thing that happens is how does mass adoption happen, mass adoption for scores took about 20 years. I don’t think it’s going to take that long for machine learning because the process of actually adding the systems and the skills is easier now than it was then so some amount farther. My hope is just that in five years I have a pool table at my office that works (Peter laughs) so that’s my big goal. (Peter laughs)

Peter: Okay, well on that note, we’ll leave it there, Douglas. I really appreciate you coming on the show today.

Douglas: Hey, thanks so much for having me.

Peter: Okay, see you.

You know, I think most people in credit today recognize the importance of AI tools and how it can really help increase loan performance, it can help expand the credit box and, you know, can bring credit to more creditworthy individuals. It’s a testimony, I think, to the work that Douglas and his team have done at Zest Finance that they were able to bring in such large financial institutions such as Discover.

A quick plug, if I may, we have the CEO of Discover and Douglas on stage at LendIt Fintech USA in a couple of weeks. If you’re listening to this after April 9th, you’ll be able to watch the video on our website, it’s going to be one of our featured keynotes of the entire event.

Regardless, I think, more and more of these large financial institutions are going to be deploying these sophisticated AI tools and I think that will be a great thing as we continue to expand access to credit to the underserved.

Anyway on that note, I will sign off. I very much appreciate your listening and I’ll catch you next time. Bye.

Today’s episode was sponsored by LendIt Fintech USA 2019, the world’s leading event in financial services innovation. It’s happening April 8th through 9th, at Moscone West in San Francisco. It’s going to be the largest fintech event held in the Bay Area in 2019. We’ll be covering online lending, blockchain, digital banking and much more. You can find out all about it and register at lendit.com.

PODCAST TRANSCRIPTION SESSION NO. 191 / JOHNNY REINSCH

Welcome to the Lend Academy Podcast, Episode No. 191. This is your host, Peter Renton, Founder of Lend Academy and Co-Founder of the LendIt Fintech Conference.

(music)

Today’s episode is sponsored by LendIt Fintech USA 2019, the world’s leading event in financial services innovation. It’s going to be happening April 8th through 9th, at Moscone West in San Francisco. We’re going to be covering digital banking, blockchain, financial health and of course, online lending, as well as other areas of fintech. There will be over 5,000 attendees, over 250 sponsors and registration is now open. Just go to lendit.com to register.

Peter Renton: Today on the show, I am delighted to welcome Johnny Reinsch, he is the CEO and Co-Founder of Qwil. Now Qwil is a fascinating company, they haven’t been around that long, but they’re starting to get traction and their business is all around providing advances for gig economy workers, typically freelancers, small businesses.

They provide an advance so these people and companies can get paid immediately so we go into that process in some depth and we talk about how they underwrite, the kinds of markets they’re in, we talk about the performance of the advances and we talk also about the challenges that gig economy workers face in today’s economy, in today’s financial system. It was a fascinating interview. I hope you enjoy the show.

Welcome to the podcast, Johnny!

Johnny Reinsch: Thanks, Peter, it’s wonderful to be here. Thanks for having me.

Peter: My pleasure. So I like to get these things started by giving the listeners a little bit of background about yourself and what you’ve done in your career to date.

Johnny: Awesome, yeah, let’s see, I grew up in a town called Fresno, in the middle of California. I went to UCLA for undergrad and then UC Davis for law school and took my first legal job in San Francisco. This was at a firm called Kirkland and Ellis in 2008 or so, 2008 was my summer associate job and 2009 was when I started, but got to see a lot of really interesting things happen at that time as you can imagine, especially centered around the financial markets. It was a really interesting way to get exposure to finance, in general.

We were sort of helping unwind a lot of some of the issues that had happened in the market around derivatives. I was an M&A lawyer, but there wasn’t a lot of deal flow so I was helping out with a lot of bankruptcies and the like and really got to see, you know, what things about the market had precipitated the decline and ultimate crash and what factors kind of led to that.

So I did M&A for about five years and then I decided that my heart wasn’t in it and part of this was from working on a deal where I really worked with and advised on some phenomenal founder teams, both sell-side and buy-side M&A. I always gravitated towards the mission of the companies and in one deal, in particular, you know, the founders were so passionate about what they were building that they walked away from a very significant amount of money to go with a lower bidder on the deal because they didn’t agree with the deal terms, solely on the basis of a disagreement with the deal terms.

That was kind of a formative moment for me in realizing that I was looking for a similar path where I felt so strongly about something that I could sacrifice a pretty significant amount of personal wealth in furtherance of my ideal. I think I spent about another four months as an M&A attorney at that point before I landed a job at a client actually which was in the bitcoin space, a company called Xapo, run by a phenomenal fintech entrepreneur, Wences Casares, and that’s where I really got my exposure to how the credit system works, aside from what happened in 2008/2009, but how the credit system works in markets where there aren’t stable banking systems or stable payment rails and payroll departments and all the things that we kind of take for granted here in the US which worked pretty well.

I was fortunate for that experience because, you know, I’d found a founder that was very passionate about what he was doing because he was trying to solve his own problem. His problem was that while growing up in Argentina Wences had encountered numerous points in time where currency controls and the devaluation of the peso essentially meant that he and his family, friends, etc. lost all their wealth, all their money really because of the doings of a central government.

And so I got the bug on financial inclusion through Wences and Xapo and then ultimately helped build, you know, the early days of the bitcoin ecosystem with some strategic initiatives and some regulatory outreach before encountering the pain point that Qwil currency solves which was my own run in with our financial system in the US.

So I like to call myself a “recovering M&A attorney” that learned about the credit system by seeing it essentially at its worst and then coming in from the disruptor side with a bitcoin angle.

Peter: Right, so let’s go back then and talk…I’ve read about this before, tell us a little bit about the moment that led to the idea for Qwil.

Johnny: Absolutely. This is, you know, really it’s fear, I felt visceral, palpable fear and I’ll talk about what I mean by that in a second.

Going through my professional career as an M&A attorney, growing up…my parents were not wealthy, but we never had concerns about, you know, could we afford our house payment and the like. I was very insulated, frankly, but when I left M&A and when I was making far less money, I ended freelancing quite a bit to help supplement my income.

There was one month where a client of mine didn’t pay on time and as a result I was going to be…you know, I had a mortgage payment due and not enough cash in my bank account so I had five days or so before I was basically going to default on my mortgage and I didn’t really know what that meant. I never had anything like that happen, I just knew it was really bad and as sort of the days go by and no payments coming in, this level of fear and anxiety continues to rise. It’s a very physical sensation that you get when you’re nervous, anxious, whether, you know, you’re about to jump out of the plane skydiving or you’re walking in a bad neighborhood late at night. We all know what that feeling feels like and this feeling that I have as I got closer and closer to that date where my mortgage was about to be…you know, the payment was going to be auto debited from my account, I was just living with that feeling constantly.

And so I finally went to my bank and I go to speak with the….you know, I have relationships with these people, they’ve known me and helped me with financial products for, you know, basically from when I graduated law school and I go to speak to my team over there, told them the situation, great client, you know, they’re going to pay, I don’t know why they haven’t paid, but they always pay, they are very high credit and walk through all the different products they have with me so my car loan at that time, my mortgage at that time, they see every student loan payment I’ve ever made, that I’ve made, you know, they have all of my financial info and I ask, hey what can we do about this, I’m really scared.

The response I got was that I should go look into payday loans or borrow money from friends and unfortunately Johnny, we’re not your friends in this case. I can’t tell you how disappointed, scared, frustrated, I mean, it was such a big mix of feelings in that moment and I just felt very much left out in the cold. What was confounding to me, ultimately, when I got over my emotional response to this, was they were in the best position to give me some kind of financial product.

They knew everything about me and something wasn’t matching up with that narrative in my head of great FICO score, great credit history, tons of financial products with this institution, you know, real problem, but they can’t do anything about it. Like they had a real opportunity to make some very low risk cash in that situation and they didn’t take it.

So I started to really think about that and realized that as a freelancer, as a small business owner, as you’re sitting in our credit system, in a bucket that’s very difficult for our credit system to underwrite, or there is no underwriting guidance for it, or it doesn’t make economic sense because, you know, the dollar amount is so low. The credit system we live in that provides mortgages and car loans and what not really, really nicely for M&A lawyers doesn’t really do anything for freelancers and small business owners.

So I started diving into why that is just from that one innocent little question of why did this happen to me, me and my co-founders realized that one, I wasn’t the only one, but also there are, you know, there’s a massive need and opportunity to really provide a lot of value and help to these populations of folks that are similarly situated as I was at that moment.

Peter: Right, so let’s just move on then to explaining what actually Qwil does, what is your offering?

Johnny: Qwil helps freelancers and SMB’s get a payment that would be otherwise paid, let’s say, in 30 days, we give it to them today. We do this by selling into the places that freelancers and SMB’s are working for. So if you work for a large Fortune 500 company and that Fortune 500 company has Qwil available when there’s a payment that that Fortune 500 company is going to pay you in 30 days, Qwil finds the data around that payment being at that time.

Sends the individual that’s going to get paid in 30 days an email saying congrats, you’re going to get paid in 30 days and if you’d like to get paid today, we’ll give it to you for…on average it’s about a 3% fee that’s just taken off so if it’s $100, we would say you can get paid $97 today. It’s really that simple, no fee if they don’t do anything and if they don’t want to take the funds early and that small fee doesn’t bear any interest if they want to take the funds today.

Peter: Okay, so then let’s maybe give some examples of some of the places that offer Qwil, maybe some of the different verticals that you’re in. Why don’t you give us some examples.

Johnny: Absolutely, and I’m glad you asked. You know, in my situation at that moment, I self identified myself as a freelancer and so one of our earliest set of partnerships was with freelancer marketplaces. I don’t know if I’m allowed to name anyone, but we work with all across the realm of skill sets so we have folks that are drone pilots and work for drone marketplaces, we have folks that are delivery drivers and work for driver marketplaces, software engineers that are freelancing and, you know, those types of freelancer marketplaces and design, etc. so we really cover a range of skill sets.

Anyone that’s a freelancer in one of those marketplaces that we cover, every single time they have any payment that’s been approved, it’s going to come to them in the form of hey, you can get paid today, if you want, or we’ll just push funds through to you on day 60 as well and incur no fee.

We started to apply that model, we found a lot of…one, we had a lot of success with that and we realized that actually, a lot of the volume that we have isn’t from people like me that are looking to avoid a bad situation, it’s freelancers and agencies, SMB’s, etc. that they’re using the capital to grow their business.

So we started to identify the verticals that would similarly sort of follow that narrative because we really like the story of, if you take a dollar from Qwil that’s, you know, going to be 30 days earlier than when you otherwise would get paid you’ll actually make more money, that’s a wonderful story.

Peter: Right.

Johnny: So we started to go into digital media marketplaces so app developers and really anyone operating in these sort of publisher networks like the Apple App Store, Google Play are very well known examples and realized that, you know, these small businesses are so sophisticated from a marketing perspective that the same kind of rules apply if we advance them a dollar that they would otherwise get paid in 60 days by Apple, they’re going to make much more than the fee that they paid on that dollar by deploying that dollar today.

Peter: Right.

Johnny: So that’s another area where we’ve been quite successful.

Peter: Right.

Johnny: Then we have a final vertical that we just broadly refer to as “liquidity as a service” because we’ve been able to drop it into a bunch of different contexts, but really where you have any B2B payments ecosystem or, you know, an ecosystem where there’s a technology solution that’s facilitating either the exchange between a business and another business or freelancer, the payment flow between a business and another business or freelancer, we can, you know, basically let that ecosystem leverage our tech.

They can continue to do what they’re doing well and we offer liquidity to that ecosystem broadly as just a part of their baked in offering and so that’s our “liquidity as a service” thing and we’ve done that with ERP’s, payment networks, invoicing networks, big vendor and supplier networks, those are sort of examples of things we’ve done that in.

Peter: Okay, so really it’s still all of those things that all boil down it sounds like…it’s one product that’s providing an advance on an invoice or future earnings. So just so I’m clear though, say you’re an independent contractor like you described in your situation with your mortgage payment, you’re an independent contractor and you’ve got some kind of random company that you may have never heard of, can you still get financing there or do you really need to be hooked into the corporation providing the invoices?

Johnny: We have to be hooked in for now and we do have plans to expand that, especially with…we get a ton of recurring use, in fact it’s staggeringly high. You know, we’ve built up relationships with a lot of the folks that are using this as a new source of working capital and in the future we’ll definitely have options for going outside of our immediate ecosystem, but for now, yeah you do have to be working with a company or a platform that Qwil is embedded into.

Peter: Right, right. Okay, so then what are the dollar amounts that you’re typically doing and what’s sort of the range and the average of the dollar amounts you’re advancing?

Johnny: About $1,000 and the beauty of the technology is that by essentially going from the top down, we’ve cut out a lot of the costs that are associated with underwriting or acquiring, you know, a given customer and so that means that we can do a $10 advance or we can do a million dollar advance. Ultimately, our machine and the way that we underwrite and manage risk and match the advance with the lender that’s actually providing the funding, that can be hyper efficient so that we can do tiny, tiny advances, or very large ones.

Peter: Right, right. So you’ve got someone like you’re embedded with a company, there’s someone who comes on and says, right, whatever it is, let’s use an example, I don’t know whether it’s actually your client, whether let’s say a Lyft or Uber driver comes in and says, right, I want to get my pay now and you’re hooked into them, what actual underwriting do you do? Do you just…because if you’re hooked into that company , wouldn’t you…maybe you just tell me what kind of underwriting you do.

Johnny: Yeah, it depends, we could be underwriting a bunch of people, we could be underwriting a bunch of companies. So in the Uber scenario, we would probably be underwriting Uber and the driver on, you know, do they have a high dispute rate, is the rider likely to ultimately come back and say that the driver was driving like a maniac and they want their money back.

Let’s take another example where let’s say we have a designer that’s going to be doing some work on behalf of a staffing firm, that has a client that’s a Fortune 500 company. The Fortune 500 company is ultimately the one that’s paying for the invoice, the designer is the one providing the services, the staffing firm is kind of making the market; we might underwrite everybody to get to the ultimate decision and it happens very quickly obviously. But to make the ultimate decision about price and try and get the best price to the freelancer in that scenario. We’ll go to as many counterparties as we possibly can to get comfortable there.

Peter: And then once the company then pays you, instead of paying the person who earned the money…is that how it works?

Johnny: That’s right, we are typically in the funds flow and we’ll get paid back first and then if there’s…let’s say our designer, they’re going to get $100 in 30 days, may decide, okay, I want to take an advance inclusive of the fee on half of the amount so they take $50, we would get the $100 payment from whoever the staffing firm client is or the staffing firm directly and then we would just pass through whatever the remainder is, to the designer.

Peter: Okay, I’m curious because one of the great things about this business…I know you haven’t been in business that long, but these are really short term duration types of advances so you can get a pretty good idea how you’re doing, I mean, you’ve had many, many turns on your book, even if you have only been doing it a couple of years so tell us a bit about the performance of your portfolio.

Johnny: Yeah, I’ll talk about the turn first. Initially, it was average 7 days or something and as we’ve worked with more sort of high end freelance and SMB’s, the counterparty risk gets better, but the payment terms get worse. So it’s sort of counter intuitive, but you’ve made it as a designer, you just landed that contract to do design work with Apple but then you find out that Apple pays you 90 plus days in the future. So as we’ve worked with more counterparties like that, what initially started out as a week has trended to more like 30/35 days and we assume that it may land somewhere more like 45 or 60, ultimately.

But the risk model and how we underwrite has performed very, very well and we’ve had nominal defaults across the entire book and have been able to provide very competitive pricing for the freelancers and SMB’s that are taking our offering such that we ultimately end up being usually less than what a freelancer or SMB would have to pay to accept a credit card payment or use a payment processing platform. That’s been great and the fact that we do have fast turning stuff and we are leveraging sophisticated underwriting to minimize risk on defaults, it just ultimately means that we can push the best pricing back to our SMB’s and freelancers.

Peter: Right, right, got it. So then can you give us some sense of the scale that you’re at today?

Johnny: Totally, so from a headcount perspective, I think this is really interesting, we started last year with about seven people so 2018, and last year alone we advanced $70 million to freelancers all over the world and we’re now about 25 and growing quickly from a headcount perspective and on pace to do a very large multiple of what we did last year.

So we’re still lean and mean, we’re still leveraging tech in all the right ways to grow as quickly as possible and retain as low a headcount as possible, but also in the process of expanding headcount and make sure that we can deliver the best product to our global SMB’s and freelancers.

Peter: Right, so then I read somewhere that when you were starting Qwil, you were turned down by investors more than a hundred times when you were initially raising money. I know we got introduced through Ron Suber who pretty much every listener here would know and I know he’s involved in your business. But, maybe you could tell us how you got over that hump and who are your investors.

Johnny: Absolutely, you know, it’s funny when you’re first starting, everything takes longer. I woke up last week and we were featured in Fast Company’s Most Innovative Companies and everything moves way, way faster now, but going back to that initial seed round that we raised, man, that was brutal. I knew that we were on to something big, I knew that our ability to make an impact in a way that would keep me excited and interested…you know, effectively, I’m trying to selfishly solve the problem and the fear that I felt when I couldn’t get help, right.

But I knew that this was something I wanted to do and devote a lot of my life to so that the 300 million or so freelancers like myself at that time and countless SMB’s don’t have to have that problem. We were going to need venture funding to do this in the right way. Fintech companies are hard, you know, we’re sending payments all over the place, we’re advancing money out that is from the capital markets and from our lending partners and doing that as a small business or something less than a technology company is very tough and so it was very obvious that we were going to go for VC dollars.

That said, I’m a first time founder, I previously was a lawyer and had worked in bitcoin, like there were always these reasons why… I didn’t know anyone in Silicon Valley that was really going to back us at that time so I had to do say a hundred, but it has to be more, frankly, and just to get the word out about what we were doing…

Peter: Right.

Johnny: …and then all the reasons why you wouldn’t back a first time founder come in. So ultimately, we had to do tons and tons of meetings just to bring in the first $500K or so that came in through Plug and Play and 500 Startups and then it gets incrementally easier after that and then it starts to move much faster, but it was a slog, it was really tough until we got the anchors from Plug and Play and 500 I was basically just doing meetings as my full-time job and getting told no a lot.

Peter: Right, you’ve got to have the vision there because that can be very demoralizing.

Johnny: Man, even…I had full conviction that I was seeing something, me and my co-founders were seeing something that the market had just not yet seen and was not capable of seeing because not everybody has felt this fear in the pit of their stomach about how am I going to make my mortgage payment, but it was tough, it was really hard.

But then as we ended up finding…I’m glad I did that because it introduced me to a ton of really helpful people, you know, Alireza Masrour and his team at Plug and Play Ventures and Sheel Mohnot and his team over at 500 which I think is how we initially got connected, have been incredibly helpful throughout the lifecycle of the company and have became personal friends of mine. So ultimately, we got a Series A done about a year and a half or so after we did that first seed round and have done a bunch of debt deals and have brought in amazing investors like Ron Suber and Sam Hodges from Funding Circle so I’m very thankful, but yeah, it definitely was hard at the beginning.

Peter: Okay, so then when you sort of look at what you’re doing, I mean, it seems to me that there’s a lot of people doing obviously factoring or invoice finance, some are doing it online and some are doing it in like for app developers in different niches, but when you look at your business who do you see as your main competitors?

Johnny: Yeah, I get that question a lot and as you mentioned, there are a lot of folks that do something similar and I don’t view us as competitive with a traditional invoice factoring company. I would actually view us as a complimentary offering where you know if you get the email from us that says hey get paid now or get paid 60 days later when the company finally pays you.

The small business that might use BlueVine or FundBox or someone else to factor their invoice, they can also use us. We’ve applied an approach to customer acquisition where we can really leverage technology to embed in an ecosystem and be alongside all of these other offerings.

So there really aren’t a lot of folks that I view as just like us though there are good examples of folks that offer sort of parallel services and Clearbanc does advances to Airbnb hosts and DailyPay does advances to freelancers and employees and Earnin does advances for employees before the payroll runs. Yeah, those are kind of the folks that I would put in the same bucket as us, but our approach is novel and our use of technology and how we leverage technology is novel.

Peter: Right, right. So it sounds like you’ve really focused on the I guess…it seems like the gig economy workers seems to me like where you have really focused your energy and that’s sort of your primary market. It’s interesting because it seems like when I look around, I see it’s massive and getting bigger and people now talk about the fact that this is a whole shift in the way people earn a living.

Some people are going to be earning a living as gig economy workers for their entire career and they may have two or three jobs, but it just doesn’t seem like…there’s not someone helping them along the way like I hear things like Uber are providing quicker advances, these companies are providing quicker advances, but you know, it seems that the gig economy worker has kind of…from a financial services perspective, they are now underserved, it feels like, and they are becoming the largest segment. Why do you think that…is it just because companies move too slowly, why do you think these gig economy workers are underserved?

Johnny: Well, you know, this is a massive paradigm shift and by 2027, we’ll have over half the workforce that’s working freelance and that doesn’t even account for the SMB population of newly minted small businesses that in my mind serve as the backbone of the business economy. Everybody has to start somewhere and so, yeah, it’s a big problem.

I think on the pure freelancer or contractor or however you define that term because, you know, everybody self identifies a little bit differently, but we’re talking about revamping a payroll process that has been embedded deeply since before the 50’s when folks stayed at their same job…if you’re really, really lucky, you know, GE or something similar for your entire career and then you retire rich with a pension.

That paradigm is shifting and the infrastructure around it is not and these are deeply embedded companies that have long standing histories and not a lot of incentive to switch and accommodate a small dollar, much higher frequency type of existence in the form of your gig economy, your freelance contractor, etc. worker. So I think that’s one reason and there’s also just a lag in the awareness from the financial services standpoint.

Companies know this, companies understand that to be strategic, to be competitive in the marketplace right now, you have to have, and it’s called contingent workforce strategy, and that means you have to be able to supplement your existing workforce with the entire range of the talent spectrum in the form of folks that are willing to freelance basically at a moments notice, or that you’re able to actually acquire and get the right freelancer to work on, whatever your discreet sort of security job might be or something like that where like the best folks in the industry actually will never work for you full-time, they’re going to be freelance. So companies get this, but financial services…I think there’s always a lag on innovation on these fronts. I give financial services a pass there because there should be….

Peter: Right.

Johnny: …moving, you know, large amounts of money into like new novel stuff might be bad, you know, macro-economically or systemically, and so I think that’s one of the reasons. But I’m sure there are a host of others that I’m missing, but either way there’s definitely a massive opportunity for startups and founders especially if you’ve had the pain point and you can weather the storm of getting rejected a hundred times. (laughs) It may ultimately be very much worth it.

Peter: Right, right. Well we’re out of time, but before I let you go I’d like to get some insight into what this year holds, what are some of your goals for 2019?

Johnny: Absolutely, I mean, my high level goal is to continue to solve this problem and to expand our impact in just the number of people that we can help. We’re not quite at a 100,000 of SMB’s and freelancers that we’ve made an advance to, but getting there pretty quickly and I’d like to get that number as high as possible in addition to just sheer dollar volume of folks that we can help.

And then, obviously, sort of the final bit of that is to make sure that we’re embedding ourselves into new platforms and channels that are springing up all over the place, whether it’s, you know, a gig platform or a freelancer workforce platform or an invoicing platform. You know, the more of these things that we can embed ourselves in, the more people that get to benefit from our service.

Peter: Right. Okay, Johnny, we’ll have to leave it there. It’s a fascinating story and I wish you all the very best. Thanks for coming on the show today.

Johnny: Yeah, thank you Peter so much for having me and looking forward to seeing you at LendIt.

Peter: Yeah, likewise. Okay, thanks, Johnny, see you.

You know, companies like Qwil are taking an age old problem and bringing it into the new world and the reality is gig economy workers…they want to be paid immediately, they don’t have to wait 30, 45, 60 days to be paid. And when you’re looking at just a 3% average fee, for them that’s not going to be too high price to pay, I don’t think in many cases, where they can get their money, they can either put it to work in their business again or they can make their mortgage payment or whatever it means because we’re living now on this on-demand world and this sort of 30, 45, 60-day payment cycle, it just doesn’t gel with the modern world which is why I think companies like Qwil have a lot of runway to go because they are providing this on-demand payment in an on-demand world. It really feels like that is what consumers want, that’s what these freelancers want and, you know, I see a lot of room for a company like Qwil to grow.

Anyway on that note, I will sign off. I very much appreciate your listening and I’ll catch you next time. Bye.

Today’s episode was sponsored by LendIt Fintech USA 2019, the world’s leading event in financial services innovation. It’s happening April 8th through 9th, at Moscone West in San Francisco. It’s going to be the largest fintech event held in the Bay Area in 2019. We’ll be covering online lending, blockchain, digital banking and much more. You can find out all about it and register at lendit.com.

PODCAST TRANSCRIPTION SESSION NO. 190 / KAREN MILLS

Welcome to the Lend Academy Podcast, Episode No. 190. This is your host, Peter Renton, Founder of Lend Academy and Co-Founder of the LendIt Fintech Conference.

(music)

Today’s episode is sponsored by LendIt Fintech USA 2019, the world’s leading event in financial services innovation. It’s going to be happening April 8th thru 9th, at Moscone West in San Francisco. We’re going to be covering digital banking, blockchain, financial health and, of course, online lending, as well as other areas of fintech. There will be over 5,000 attendees, over 250 sponsors and registration is now open. Just go to lendit.com to register.

Peter Renton: We have a very special guest on the show today. I’m delighted to welcome back Karen Mills, she is the former Head of the Small Business Administration under President Obama. In fact, she was Head of the SBA during one of the most challenging times for small businesses in the last eight years during the Great Recession.

So I wanted to get her back on the show because she has just written a book that is about to be published and we want to talk about that. We cover a lot of topics, we talk about the state of small business lending today, some of the structural challenges within small business lending, we talk about the future of banking when it comes to small businesses and we talk a lot about regulation, the role of companies like Amazon, PayPal and Square and Karen shares why she’s very optimistic about the future prognosis for small business lending. It was a fascinating interview. I hope you enjoy the show.

Welcome back to the podcast, Karen!

Karen Mills: Delighted to be back.

Peter: Okay, so you know, we last had you on the show…it was just under four years ago and you talked about the opportunity and the future of small business lending and I wanted to start off with….maybe we could look back at the past three or four years and certainly a lot has changed, maybe we could start by talking about how has small business lending evolved over the last four years.

Karen: Well, fintech and small business lending have really changed tremendously over the past four years. Right at the beginning of that time when you and I were talking, there was this rush of excitement and we called it the “Wild Wild West.” Hundreds of companies were opening and then there was this pull back, this moment of pause in the whole innovation curve.

Interestingly, the dynamic is now even more powerful, in terms of how technology is going to change, because since that time, technology companies like Amazon and PayPal and Square have become major factors. Banks have woken up and the Artificial Intelligence and machine learning applications for lending and financial services have blossomed and come to the front and with them the fintechs, the small innovators have come back into the market. So we are at a  really exciting inflection point right now, probably even more exciting than the “Wild West.”

Peter: Right, and probably it’s more rationally exuberant as opposed to irrationally exuberant to sort of how it felt like. Looking back now that time, 2015, it was just a crazy time when money was just being thrown around in amazing fashion, if you remember.

Karen: Yes, the good news about that moment is that it was a moment that forced the incumbents, the banks and the old dinosaurs to wake up.

Peter: Yeah.

Karen: But it was a moment based on really only a surface innovation in some ways. The innovation was important because it dealt with the pain points in small business lending. The fact that it took, you know, three weeks or three months to get a response and you were xeroxing a pile of paperwork to carrying it down to the bank and this idea that you could complete an application in half an hour and get the money in your bank the next day, this was revolutionary.

You really have to credit the entrepreneurs and the innovators at that time for turning the whole thing, opening the spigot, then the issue became….you know, the new entrants really did not have competitive advantage, they had a very hard time accessing customers and they didn’t have a low source of capital. Banks did, they had deposits, banks had customers so they needed to come up to speed and respond. That took some time and now we have a lot of major players in the game innovating at an even higher level because of the input of new data techniques and API’s and the ability to take algorithms and Artificial Intelligence to the next level.

Peter: Sure, so I want to start talking about your book. As we’re recording this, it’s not yet published, but it will be soon. I mean, it’s called “Fintech, Small Business and the American Dream-How Technology is Transforming Lending and Shaping a New Era of Small Business Opportunity.” So I guess, first question I have is why did you decide to write this book?

Karen: Well, Peter, as you know, I was the Head of the US Small Business Administration and part of President Obama’s cabinet. I took on that job and joined President Obama exactly ten years ago at this time and I don’t know if everybody remembers how difficult that moment was. Credit markets had frozen, banks had overextended with their mortgages and they literally stopped lending to small businesses. Many, many small businesses had their credit lines pulled and we had a really serious situation in the first quarter that I was in office; we lost 1.8 million small business jobs.

So I was determined that we would try to get small business lending started again and I managed to convince President Obama and Larry Summers who was then the Head of the National Economic Council to let me do something pretty bold, in retrospect. I had come into government from venture capital so I was used to trying to solve the problem and this seemed to be a particularly difficult moment and we were able to raise the loan guarantee rates on SBA loans to 90%.

When we did that, it was like flipping a switch. We got a thousand banks back to SBA lending in six months; banks that hadn’t been making loans for the past several years and we put out $30 Billion of loans that year, record amount, and for the next several years. So that taught me a really important lesson. That is really when the book began and I talk in the presence of the book about this moment when I was down in Arkadelphia, in the middle of a saw mill and it was freezing cold in the middle of February.

I was with the small business owner and his wife who was the bookkeeper and she turned to me and she said something that really sort of changed my perspective on the day and really I think led to the writing of the book. She said, you know, you saved our business and they had then….just on the brink, unable to get a small business loan and I realized how important access to capital is to so much of our economy.

So when I was here at Harvard Business School writing white papers about the recovery, I began to get involved in fintech and how technology was starting to focus on this market and changing addressing these customer pain points we talked about. I began to realize that technology had the potential to really transform small business lending and really take away some of the frictions that exist in this part of the economy and in that way have an enormous positive impact on these important contributors.

Peter: Right, right, I totally get, you know, how important that is. I mean, obviously that’s what we…..I’ve dedicated myself the last ten years to sort of talking about this, exploring this and learning, but I want to dig into some of the contents of your book.

I want to start out with something that I didn’t know and surprised a little bit that there has actually been a decline in the number of new businesses that are being started in this country and I think you share some specific data in the book. That was a surprise because I thought that, you know, it’s easy when you’re involved in sort of fintech and there’s so much happening these new businesses starting left, right and center and you think that happens all over the economy.  But the reality is there are fewer small businesses being started today than there were ten years ago and certainly the percentage has gone down quite significantly. So why do you think that is?

Karen: Well you’ve identified what I think is one of the most worrisome trends in the US economy which is that the rate of small business starts is way down and it has not recovered after the Great Recession. We used to start 550,000, even up to 600,000 small businesses a year, we’re down to 450,000-ish and there are a lot of theories about why this is so, but the economists have really not come together and understood the problem. They’ve identified it, we’ve quantified it, but we don’t really know why.

One hypothesis, of course, is this access to capital. There are some other hypotheses about permits and regulation and there’s a lot of innovation and idea that we had at the SBA, we called it “Startup in a Box.” How can you use technology to just let somebody go online and immediately know all the permits they need to file, all the paperwork they need to fill out, apply for, you know, a credit card and a bank account and a domain name, how could we make it  easier for people to start a business. So that’s a really interesting area and I know big technology companies and some new small technology companies are addressing that problem. I’m really focused in the book on the access to capital piece.

Peter: Right, right.

Karen: And it’s very hard, of course, for startups on main street to access bank capital because they are new, but if we can figure out how to address some of the issues that I identified in the book, particularly what I call “Information of Past Deeds,” (?) it’s very hard for a young business to show that they’re creditworthy. And it’s really actually very hard for any small business to show a bank and be transparent about their prospects and whether they’re making money a lot of times because they don’t even know themselves. So this one of the places that, of course, technology can help take away some of the barriers and frictions of the market.

Peter: Right, right, but at the same time you talk about….there are certain structural challenges that really come with small business lending. I mean, you talk about it in the book. You know, the decline of community banks and community banks have often been the ones that are closest…….obviously, they’re closest to their community and they know these small business owners personally.

When they decline, it’s harder for small businesses to get access to capital then there’s the lack of a secondary market like the securitization market which…obviously, there’s been some developments with some of these newer players, but it’s a lot less robust than the consumer lending, certainly in the mortgage lending market.

Then you also talk about, you know, small business loans that are less profitable because particularly, that’s a sub-million dollar loan, sub-$250,000 loan which is what most businesses want. It’s been harder for these banks to really make money so there’s a lot of head winds for small business lending. Maybe you could just tell us your perspective on how fintech is really addressing these head winds.

Karen:  Well, I’m a big fan of community banks and community banks have been the go-to for small businesses for a long period of time, but as you just described, there’s a whole fed of structural reasons, head winds that are preventing community banks from coming back to this position of prominence. There used to be about…..when I was running the FBA, about 8,000 community banks; we’re down to 5,000 and many people……I talk about various myths, many people say, well if we just, you know, got rid of Dodd-Frank and we got less regulation, community banks would come back and flourish and the fact is that there’s some real structural problem.

It is very hard for a community bank to make money on a loan under $50,000 and so what has happened is that a gap has emerged in the small business lending market which is small loans to the smallest businesses.

When fintechs had come on the scene, this is the area, of course, that they have began to address. The average Square loan is about $7,000. It will be very hard in a traditional, you know, relationship banking mode to make money on a $7,000 loan so I think we need to find ways and community banks are finding ways to participate in this new fintech and to maybe hin their position and to use their relationship people in productive ways, but not as the first line information gatherers. We can do better than that with technology.

Peter: Right, right. And then so let’s sort of tease that out a little bit more. In fact, you talk about in the book….you talk about the small business banker, the future, you even bring up the idea of having specialist banks. That may be community banks that really focus on small business lending almost exclusively, so tell us a little bit about your vision there for this sort of small business bank of the future.

Karen: In the book, I take the liberty of making some predictions about how all these might come up, who the winners and losers might be and what the landscape might look like. One of the things that I talk about is the idea that there will be small business-focused banks. I tend to be quite annoyed that small businesses are sort of the poor cousins of the consumer banking market.

When you look at the divisions, you know, there’s sort of a wide fed of activity around consumers and then they modify the products and send them out to the small businesses. I argue in the book that small business lending is really a very different market and needs small business-focused solutions and technology that take into account these two driving issues. I mentioned information paucity, it is much harder to know what’s going on inside the small business and to find out if that small business is creditworthy than it is to figure out whether you should give a consumer a mortgage.

You know, you get ten pieces of data, you can pretty much figure out whether the consumer should get a mortgage, but small businesses are much more complicated. Once you figure out the algorithm for the dry cleaners, it may be totally different for the commercial landscape companies or the restaurants or the producers of, you know, automotive parts.

Peter: Right.

Karen:  So I believe that having verticals specialization would lend you expertise and this actually proves true with an interesting example, Live Oak.

Peter: Right.

Karen: You know, Live Oak began just with veterinarians and then, of course, I think they did funeral homes and poultry farmers. It also helps in gathering customers because word-of-mouth spreads around in the sector and you become the trusted expert so I see a future where you could see vertical specialization within the small business banks. They would understand the small business market, they would develop products that really address this heterogeneity, the fact that all the small businesses are different, and they would really gear their products and their services and their advice and their counsel to the small business borrower.

Peter: Right, right.

Karen: And I think that might be a recipe for success.

Peter: That’s interesting that certainly some of the online lenders, you have….Kabbage started with eBay sellers, OnDeck had a few targeted verticals when they got going so you can see that there are certain advantages you can have when you focus on a vertical, but I want to touch on another success story, something certainly that…a bank that has gone a different way and that’s Eastern Bank.

You talk about them in the book and they are a bank that embraced fintech very early on and they even spun out a tech company basically, I guess, a fintech company out of their bank so tell us a little bit about Eastern Bank and what has been their secret to success.

Karen: I’m teaching now at Harvard Business School and I love the story so much that I wrote a case about it which we teach to the MBA’s and really the key player in the case, our protagonist, Bob Rivers, the CEO of Eastern Bank, is a key factor in this story and their success.

Eastern Bank is a 200-year old mutual bank, it started in Salem, Massachusetts back in the days of the witch trials and it started with a community focus and each of the people who got a loan, just like a mortgage, had to come back and they had to work in the bank for an hour a week so that the other community members could get access to lending. That heritage has really defined the bank.

Bob Rivers realized that he was going to serve his community of small businesses and he was a big SBA lender, small business lender, that he would have to….as he said it, embrace technology and disrupt themselves, not way to be disrupted, but go out, find innovation and disrupt themselves. Now his leadership was key to this.

It took a little while for him to get his senior staff on board, but when they looked into the borrowers’ account and saw that they were paying interest to fintech loans that they had taken and these were customers of Eastern that had not even been offered an Eastern loan clearly were quite creditworthy. He said, you know what, we have to develop our own solution.

Peter: Right.

Karen: He attracted Dan O’Malley, they developed a solution over a couple of years so it was developed inside the bank and then they allowed Dan to spin it out and it is now providing, and full disclosure, I’m actually an investor, enumerated the spin out, but it is providing access to this kind of sort of technological front end to other community banks.

So I think this is terrific because we want community banks to be able to get up to speed fast. They don’t have to reinvent the wheel, create their own technology. We want a plug-in solution so that they can provide this fast solution to their own customers and that’s one element of what I hope will be a very broad and sweeping set of solutions for all kinds of small business owners who want to engage with all kinds of different institutions; traditional ones or new ones.

Peter: Right, right. And just on that, I want to bring….obviously, you were Head of the Small Business Administration for several years and, you know, the Small Business Administration……

Karen: Five, a long time.

Peter: (laughs)….okay, they primarily work with banks when they’re doing this guarantee that you’ve talked about. There was an interesting Op-Ed the other day in American Banker, it was by the Head of Funding Circle USA, talking about you know what…..I know that there are certain non-banks that do have access to these SBA guarantees, but not many and given the way it’s changed….I know you no longer have authority at the SBA, but I’m curious to get your perspective. Shouldn’t the SBA be partnering more with fintechs than ever before?

Karen: Well, as you might imagine, I am a big fan of the SBA and its mission and its mission is to provide access to credit to small businesses who cannot, otherwise, access that credit, but are creditworthy. What that means is, if you can get a loan from a bank, regular bank or fintech, without an SBA guarantee, then you should, that’s how the market works, but in many, many cases a small business owner comes to a bank and is just not quite needing the credit threshold.

So the bank asks the SBA, would you guarantee this loan, maybe 75% of it and the SBA will give approval and that will allow the bank to make the loan with some skin in the game but not all the risk. We know that that fills an important gap in the US economy and we actually know the size of that gap because the SBA has a portfolio of $100 Billion of these loans.

We know these are good loans because the loss rate on the SBA portfolio is less than 5% so $95 Billion worth of loans are made in this country that would not otherwise be made to good important small businesses which, by the way, the SBA over indexes in underserved minorities and women on businesses so this is a really important program that fills the gap. The other thing that’s good about it is that because the loss rate is not high, the guarantee cost that you, as taxpayers…. almost no money.

If this is the role of the SBA then, of course, it should be engaged with all of the lenders who are, you know, the conduit to these important gaps in the marketplace, but it’s also the role of the SBA to be very, very careful with taxpayer money so it is up to the fintechs, I think, to prove that their portfolio should be worthy of an SBA guarantee because we’re playing with, you know, your tax dollars or my tax dollars. I think that’s the place that is a sequence and my guess is that will absolutely come about as the fintech market stabilizes and becomes a regular part of American small business lending.

Peter: Right, because, as you say, there’s a lot of these fintech companies that have limited track records and there are some that focus on the higher risk side of the market where defaults are way over 5%, they’re well into double figures in some cases. They might not be appropriate, although….even with some of those companies like they would argue that they have a portion of their portfolio that probably would be suitable, just not all of it. That’s good to hear, I feel like this is a program that I would like to see extended and I know that the government does not move quickly, but I’m glad to hear that you’re on board with it.

Anyway, I want to move along and talk about a couple of other things now. I went through your book in some detail, actually I went through the PDF that you sent me a while back and I was looking at how many times you mentioned Amazon, PayPal and Square and you do mention them throughout the book. But I found it interesting that Amazon gets mentioned more than twice as much as either PayPal or Square and I wanted to get your take on all three companies. Specifically, you do seem to focus more attention on Amazon, are they ….do you think these companies and maybe that company, in particular, is going to be a very big player or maybe even the biggest player in small business lending in the future?

Karen: Well, I didn’t actually count so that’s an interesting observation. I am a big fan, particularly of Square, because Jack Dorsey came and worked with us at the SBA when he launched Square and he and I did National Small Business Week before he even went back to run Twitter so I’ve been sort of with Square since the founding. But Amazon is, without a doubt, going to be one of the critical small business forces in the US and I’m sure you know that they are already a major small business lender and PayPal and Square have insight into a lot of information because they see the receipts on a real-time basis and so they will be important in the equation.

One of the questions is, what happens to the businesses who don’t have a retail focus, who don’t have a Square device, who don’t sell products through Amazon; they might be a service provider and where do they come in in the market. So although I believe these technology companies and others, like Intuit, I see them as really important thought leaders and drivers of the change as they have the head, of course, in their whole history.

But I also don’t think that they will take over the entire market; I think that the JP Morgans and Wells Fargos and Bank of Americas are going to make sure and the community banks are going to also play a role as well. As I said, you know, really innovative players like vertical banks so I think the landscape is open, you know, there’s real opportunity, but without a doubt, for a certain segment, the Amazons and the Squares will be critical.

Peter: Yeah, yeah, okay. So I want to talk about another big topic and I know that we’re running out of time, but I wanted at least to spend some time on this and that is, regulation, you have a couple of chapters in the book dedicated to it. Maybe we could start off with borrower protections and this has been obviously in California, there has been a bill passed there to help the small business lending disclosures….that small business lending disclosures have to be provided, but what are your thoughts on borrower protections when it comes to small business owners.

Karen: Well there are two full chapters, I will say, in the book on regulation and you and I do find it interesting and I actually think it is a critical sort of underpinning of understanding what’s going to be veering into the future of small business lending. As you mentioned, there are some critical worries. Small businesses have really fallen through the cracks of the regulatory system as it exists in the US today; I call it a “spaghetti soup.”

There are seven regulators and not one of them, up until the OCC recently said they would, has the ability to charter a fintech and most worrisome to me, small businesses are not protected by the Consumer Protections and disclosure requirements of the CFPB, the Consumer Financial Protection Board, and I think that’s wrong. Small businesses, the Fed surveys approved this, and I made quite the case in the book about the fact that small businesses really require the same kind of protections as consumers.

One of the ways I prove it is I take the Fed focus group questions and I showed them to Harvard Business School students and alumni and a whole set of people and I say, you know, tell me, interpret this loan, tell me what the interest rate is and I get numbers from, you know, five to 30 to 50 as answers. It’s very hard to interpret a loan. In loan documents there’s all kinds of hidden fees and costs so why can’t we do what we do for consumers and have a smart box, a disclosure box, and just tell them that this is what all the costs are. So that seems to me a no brainer.

Peter: Okay, so then given the reality of the situation with any….you have a great diagram in the book that just sort of  shows all the regulators with loans going all over the place, how the small businesses are regulated, but given that you did spend time in government, you know what is realistic, but what should regulation look like if you’re really going to do something that is better than what we have now?

Karen: Well streamlining and simplifying this process is, of course, critical. Actually, the US Treasury put out some recommendations which were very thoughtful in this regard.

The other thing that’s coming though that no one has really figured out is all of the European open banking activity and privacy laws will the critical aspect of regulation going forward. If you look at what I’ve described in the book as most promising really transformation that will happen to small businesses and to small business lending, it really lies in this ability to gather data, to suck it up to these API’s and create a small business dashboard and know from that dashboard how the businesses are really going to do.

The ability to do that exists now because we have infrastructure providers like Plaid and Yodlee who will pool all that data from your credit card provider and your bank and your turbo tax account and your QuickBooks accounts all up into a dashboard. I call this, by the way, Small Business Utopia.

It’s this notion that not only your banker can have a vision of what’s going on inside your business, that you as a small business owner, you could have that as well and in order for that to occur, we have to pay attention to open banking. And whether or not we want to adapt that as part of our regulatory framework here in the US, I believe that that is going to be critical to creating this open innovation environment which will, we hope, create all these new products and services that are part of Small Business Utopia.

Peter: Right and you provide there a fascinating example in your book about how this actually would work in practice. I think it’s a coffee shop owner from memory…..

Karen: (laughs) Yes.

Peter:….that you provide about whether she could buy……

Karen: That was the coffee shop owner, yes. So I have a made up story in the book about the coffee shop owner, but I have to tell you, I was walking down main street in my hometown in Brunswick and a young woman and her partner have opened one of those micro breweries and I was describing the coffee shop owner and the Small Business Utopia in the dashboard and she said, you know, this would be perfect.

I go home at night, I stay on my bed, I open my laptop, I pull up my bank account, I pull up my QuickBooks account, I open my iPad and my phone, I have six or seven screens open and in my head I’m trying to create an Excel spreadsheet that tells me how’s my cash flow going to be, do I need a seasonal loan?

To me, we can solve this problem, technology can solve this problem tomorrow and so I believe as we do, we will have more small business owners. We will have more small business owners who succeed and I think this could really have an enormous impact on our economy and on the ability of people to achieve the American Dream.

Peter: Yeah, yeah, indeed. Just on that, last question, you do paint a pretty rosy picture of the future of small business lending in the final chapters of your book, but I want to just maybe close with what are some of the things you’re optimistic about and what are some of the things you’re pessimistic about when it comes to small business lending in the future?

Karen: I am an optimist so I will admit that. I wrote this book because I really believe that there is an opportunity, that in a sector which has perhaps been forgotten about and a little bit left behind, the small business owner with their pain points of accessing capital are now going to enter new possibilities of being well served as innovation takes over this market.

I want to, in any way I can, through this book and through the efforts of places like LendIt see how we can create an open landscape where large tech companies like Amazon for this solution and old fashioned banks like Eastern or large ones like JP Morgan, you know, also competing and new entrepreneurs and innovators push them by offering new products and online vertical banks, all of it geared around the ability of technology to solve these critical frictions in small business lending…… this informational paucity, this heterogeneity, these things that make small businesses hard to lend to, hard to understand.

If we do this right and we create a regulatory environment that allows for open banking and access to these data and we don’t have data monopolies, then we have the opportunity to fuel this critical part of our economy and also the part of our economy that creates economic mobility and this is sort of my history. You know, I come from a family of immigrants who started small businesses so I believe in the American Dream and I think technology gives us more possibilities, more promise of that if we do it right.

Peter: Okay, that’s a good note to end on. I certainly think it’s exciting times now. I really appreciate your coming on the show today, Karen.

Karen: Thanks so much, always a pleasure.

Peter: Okay, see you.

Karen: Bye.

Peter: Before I close, I just want to give you a heads up on the timing of the launch of the book. We’re recording this on the last day of February and the electronic version of the book will be launched on March 14th and the hard cover is being launched on April 4th. I will have a link to the page on Amazon where you can go and pre-order the book.

Before I go, I just want to touch on Small Business Utopia, as Karen puts it and I think we really are nowhere near there yet, but I know there are several companies that are working on creating exactly what Karen describes where you’ve got basically a dashboard where all your information is being pooled in from different sources and you have a complete picture of the financial condition of your business.

Now I think it’s not going to be done overnight, but given the fact there are several companies working on this, I really expect within a year or two there will be several good options that small business owners can have that will be able to give them a much better picture on the overall view of their business.

Anyway on that note, I will sign off. I very much appreciate your listening and I’ll catch you next time. Bye.

Today’s episode was sponsored by LendIt Fintech USA 2019, the world’s leading event in financial services innovation. It’s happening April 8th thru 9th, at Moscone West in San Francisco. It’s going to be the largest fintech event held in the Bay Area in 2019. We’ll be covering online lending, blockchain, digital banking and much more. You can find out all about it and register at lendit.com.

 

PODCAST TRANSCRIPTION SESSION NO. 189 / JASON GROSS

Welcome to the Lend Academy Podcast, Episode No. 189. This is your host, Peter Renton, Founder of Lend Academy and Co-Founder of the LendIt Fintech conference.

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Today’s episode is sponsored by LendIt Fintech USA 2019, the world’s leading event in financial services innovation. It’s going to be happening April 8th through 9th, at Moscone West in San Francisco. We’re going to be covering digital banking, blockchain, financial health and of course, online lending, as well as other areas of fintech. There will be over 5,000 attendees, over 250 sponsors and registration is now open. Just go to lendit.com to register.

Peter Renton: Today on the show, I’m delighted to welcome Jason Gross, he is the CEO and Co-Founder of Petal. So many people have heard of Petal, they have not been around very long, but they have certainly been out there in the fintech airspace, shall we say. They are a credit card company, but trying to do something a little bit different, a credit card company for the underserved, for those people who really are rejected by the mainstream companies and what they’ve done is not just create like a secured credit card or a very, very low credit limit type card.

This is a card that really has a lot of the same features as a premium card, but it is targeted at the underserved. It’s a fascinating challenge that they’ve undertaken here and it was a fascinating conversation. I hope you enjoy the show.

Welcome to the podcast, Jason!

Jason Gross: Hey, thanks for having me, Peter.

Peter: My pleasure. So I like to get these things started by giving the listeners a little bit of background about yourself, if you could just tell us what you’ve done in your career to date.

Jason: Sure, and so I’m the CEO and one of the Co-Founders of Petal, originally trained as a lawyer. I went to Harvard Law School, I met two of my co-founders while we were in school, we stayed in touch and ended up working together years later. Began my career working at a big law firm, corporate law, essentially as a Wall Street lawyer, my clients were all financial companies and financial institutions.

Over the course of my career, transitioned from the legal side of things to the business side and also transitioned from big Wall Street financial services to tech and then from tech back around to financial technology. Over the course of my career I’ve had the opportunity to, first on the legal side, work with some of the fastest growing, most successful technology companies and venture capital funds.

On the financial services side, I’ve had the chance to work with some of the largest, most successful institutions in the world. That experience, and the breadth of that experience has been really helpful in my current role leading Petal.

Peter: Right okay. So then what was it that led you…where did you get the idea from, how did the process begin that led you to starting Petal?

Jason: Sure, everything began for us with a personal experience of one of our co-founders. So I mentioned that the founding team goes back quite a ways, we all knew each other in grad school. I was studying law at Harvard and my co-founder was at MIT at the time doing a masters and he stayed on to get a PhD in machine learning and data science. He has an international background, moved to the States for college and when he crossed over into the United States he was not able to bring his financial record with him so he was starting over from a financial perspective and was unable to qualify for many US mainstream financial products.

He did not have a credit history so when he applied for a credit card, he was declined and that lack of a credit history impacted him in other ways as well. He had trouble signing a residential lease because landlords were checking credit, he had trouble setting up a cell phone plan that wasn’t prepaid. It’s a frustrating experience that many folks who’ve crossed borders have run into. That got us talking about credit scoring, the data that is involved with credit scoring and sort of how that legacy infrastructure works and we were having a conversation right around the time that regulators and academics were starting to really shine a light on the contours of credit access in the United States.

When I think the light bulb really went off for us was the realization that the poor experience that our co-founder had in attempting to access financial services, notwithstanding his educational background, his financial resources, etc., was not unique to him, but instead was the experience of tens of millions of US consumers basically on a daily basis.

The research that I’m referring to in part is the CFPB’s research on credit invisibles and thin file consumers. As you know, there are tens of millions of adults in the United States with no credit score or with a thin credit file such that their credit score is not reliable.

Peter: Right, right, so you started Petal. Why don’t we actually take a step back and tell us what is it you guys do, what’s your core product, how does it work and how is it different to what else is out there?

Jason: Sure, happy to. So we have one product today, it is a Visa-branded credit card, unsecured credit card product. There’s really three things that make our product unique from what else is in the market and what has existed up until this point.

The first has a lot to do with addressing the problem that I was just describing, that is what we call cash flow underwriting. We are providing a credit card product that in terms of interest rate and credit limit and fee structure is the kind of product that previously was only available to people who had built significant credit history. What we do is incorporate the data that describes the rest of a consumer’s financial picture that’s not captured in a credit report. We incorporate data like income, monthly expenses, trends in volatility and that information to essentially appropriately underwrite customers that today can’t be well understood by the traditional system. So that’s number one and it allows us to offer people essentially more credit for less money.

Number two, we offer a user experience that is designed for a modern consumer, for digitally native consumers, and it takes into account the fact that so many of our users are seeking to establish and build credit in a safe and responsible manner. So there we offer a mobile app that is built around financial success and responsible use of credit. We embed financial education, we help folks to make the financial decisions in the use of the product that benefit them and help them to succeed financially.

We do not encourage people to borrow more money than they should, we do not encourage people to spend more money than they should, we make more transparent the cost of interest and sort of the workings of a credit card in a way that I think really is a different, more modern approach to the product.

Finally, I would say, number three, we’re building a different sort of financial company that puts the customers’ best interests first and that means that we are seeking to partner with our customers over the long term. It means that we want folks to make the decisions that are right for them, and that are right for them financially. It’s one of the reasons why we don’t charge any fees and one of the reasons why the product is as transparent as it is. You know, the business model there is really based on this recognition that today customers are looking for a financial company that has their best interest in mind. If they’re able to find that kind of a provider, we think that they’ll stick with us over the long term.

Peter: Right, right, got it. Okay, so then can you talk a little bit more about that person. Who is the typical customer? You obviously talked about the immigrants who have come here, obviously you’re dealing more with the thin file/no file type crowd, but are these people who are really professionals who’ve come here or are they…why don’t you give us a little bit of a profile.

Jason: Yea, well the thing about the thin file/no file crowd is that we were all once members.

Peter: Right.

Jason: Everyone is born credit invisible and from the industry’s perspective, subprime. So we find today that our product is a really good fit for folks that are seeking to establish and build their credit so oftentimes, we’re the first credit card in someone’s wallet. We also are a really good fit as the second or third card as well. So we have folks who were previously only able to qualify for a secured card for instance, and they are able to upgrade from that secured card to use our product.

I mentioned that the underwriting allows us to extend more credit so we’re able to give people credit lines that are significantly higher than what they would get from similar introductory credit products. So we see a lot of young people, we see a lot of immigrants and more and more we’re tracking interest from consumers that are outside of the category that I just described. People that have been attracted to us more because of the product and because of the brand.

Peter: Right, so they’re attracted to you because of sort of the usability, is that what you’re saying?

Jason: That’s right, yeah, I think that people are looking for that sort of simple, modern intuitive user experience, you know, the same way that we’re seeing customers flock to neo banks, to some of the mobile first stock trading platforms, Robinhood for example…I think these people are looking for a similar experience in the credit card space.

Peter: Right, that makes sense, that makes sense. So, you know, I want to dig in a little bit into the underwriting piece. You’ve touched on it already, but I want to sort of get a much clearer picture if I can, and then…is your primary tool to sort of dig into the borrower’s bank account so you can really get a sense of cash flow, or is there a multitude of things? I mean, how are you approaching underwriting?

Jason: Sure, this is an area, in general, where I think in the industry there’s been far more sizzle than there has been steak. People talk about, you know, artificial intelligence and machine learning, they talk about very exotic data sources, but when you get down to what actually is in use in the market, practices tend to be fairly consistent. At the end of the day, 99% of all the lenders that are out there are using information that they get from the major credit bureaus or from the potential customer in the application form.

We actually are reliant on a whole new set of data which is the digital financial record of the consumer and we use machine learning and we use sort of the latest methods of analyzing that information, but what’s most important is that the inputs to our model are vastly different from what the rest of the industry is looking for. So we’re an application built on top of essentially open banking rails.

We asked ourselves, in a world where the whole financial picture of a customer is machine readable, is digital, is easily transferred by the customer, how does it make sense that we’re looking only at essentially the liabilities side of a customer’s balance sheet? We’re looking at the amount that they owe and the amount that they have owed historically without a clear view into the assets or into the cash flows and the income of the prospective borrower.

Our perspective on this is before we start getting into the exotic world of alternative data and before we start mining someone’s social media or, you know, making judgments based on someone’s cell phone battery, we should begin by just developing the capabilities required to understand their financial position, revolutionary concept, right. Anyone who’s been in lending for a long time who has seen judgmental underwriting or who has looked at the underwriting of larger products, you know, understands that at the core of the information you’re looking for really is a question of income, stability in income and willingness to pay. By allowing customers to share with us that holistic financial picture, we can really measure those things in a way that hasn’t been done before.

Peter: Right, so when you say you’re allowing your customers to share, so are you saying like they connect their bank account, do they connect their Robinhood account, I mean, what are the sort of things they’re connecting?

Jason: That’s exactly right. So folks are connecting their primary accounts so checking accounts, savings accounts. If they have liquid assets in other places as well, they can connect those sources of information also and that allows us to gain this more holistic picture. Of course, you know, when you apply for a mortgage, you turn over bank statements as well; the big difference here is in automation.

The average cost to underwrite a mortgage in the United States is something like $8,000 and obviously in the credit card market you can’t spend $8,000 underwriting every single application and so really the innovation here is that the system is fully automated. That customers connect their bank accounts, customers send us their credit information as well and we algorithmically analyze that information and make a decision on the spot so we’re able to tell customers from a credit perspective whether they are pre-approved in just a matter of seconds.

Peter: Okay, and so then you could tell that but then are you doing like risk-based pricing at all because you’re going to obviously have people who…I’m sure there are people you deny, there’s people that you approve, but they really only just made the grade and then there are going to be others you easily approve, what is your approach to pricing on your card?

Jason: Sure, so when we thought about designing a product that was appropriate for this huge segment of potential customers, it was really important for us to build something that had some flexibility baked in. And again, everyone begins credit invisible and thin file, right, we know that out of that potential group of customers we will have very high income folks with the ability to afford a very large credit limit, we know that we’ll have lower income folks and everything in between.

So our pricing ranges pretty dramatically, you know, we try to match up credit lines, for instance, that are appropriately tailored to someone’s financial position. You don’t want to give them too much and you don’t want to give them too little, sort of a Goldilocks situation.

So credit lines for us range from $500 on the low end to $10,000 on the high end and the average is around $3,000 which, you know, if you compare that to other introductory credit card products, 10X, what you tend to see then APR’s, again, risk-based, range from 14 which is pretty low in the credit card market up to 25/26 which is where most introductory cards start.

And then finally, the last piece which is not risk-based is that we don’t charge our customers any fees at all. By having such a wide spectrum of pricing, we’re able to one, get the most leverage out of the sophisticated work that we’re doing on the underwriting side and two, we’re able to serve a wider range of customers.

Peter: Interesting, it’s always surprising to me how so many credit card companies don’t operate a wide band of pricing for their products so that makes sense. So then what about…how are you approaching fraud, obviously there’s going to be some bad actors out there who are going to try and get this card, what’s your approach, how are you fighting it?

Jason: Yeah, so this is something that, you know, everyone participating in the industry is facing. We’re fortunate in that some of the best fraud fighting tools are available even to new companies so we’re working with partners that are really at the cutting edge of digital identity mapping, transaction pattern monitoring, etc. We can kind of tap into the same technologies that are being used by the largest issuers in the market to make sure that we’re keeping our customers safe and that we’re also protecting our company against fraud.

One thing that we have going for us is that we are looking at more data at the application phase and so we have more opportunities to get wind of something that doesn’t look right.

Peter: Okay, so then I’m curious about how you are finding your customers today. You’re obviously on the app stores, where are you…do you require people to download the app and tell us what the main channels are for acquiring customers.

Jason: Yeah, so to date the largest channel for us has been organic and word-of-mouth. We had 100,000 people sign up for a waitlist when they heard about the product and we’ve done only very limited advertising to date. So I think that first, the product being unique, the technology being something that’s new to the market has gotten the attention of the media and we’ve been fortunate that a number of widely read outlets have told our story so I think a lot of customers have heard about us from those sources.

We are available in the App Store, we have apps on both IOS and Android, we’ve been doing some digital advertising now and over the course of the next year, we’ve planned to engage in multi-channel advertising to get the word out about the program even further so that customers will be able to find us in a variety of different sources, but we expect that word-of-mouth to really continue.

One of the things we’ve been very proud of is our NPS score with our early customers and even though we’ve only been out in the market for a short period of time and there’s still a lot that we want to develop in terms of features and perks and functionality that we offer through the product, we’ve been able to achieve a NPS scores in the mid-70’s. And of course, NPS, for those that are not familiar, is that question that company’s ask that says, how likely are you to recommend this product or service to a friend or a family member.

You know, the average in credit cards I think is in single digits. The average in financial services is something like around 30. In the mid-70’s, we’re up there with really some of the most loved brands like Apple and others, so that is a good measure of word-of-mouth potential so we’ve been very proud of being able to achieve that.

Peter: Right, right. So then I’m curious…you said you’ve only been out for a few months, when did you actually launch your first credit card?

Jason: So as it turns out, building a nationwide credit card program from the ground up is harder than it sounds.

Peter: (laughs) It sounds hard, actually.

Jason: (laughs) Yeah, it’s one of the things where if I had known back then what would go into this, I don’t know if I would have made all of the same decisions.

Peter: Right.

Jason: I joke a little bit, but even though we’re a small company, you know, we’re doing just about everything that the largest credit card issuers in the market are doing, from the marketing and advertising to underwriting and decisioning through the whole customer journey and customer support, all the way to the end of the life cycle, collections and everything in between. So to stand up that whole platform and to do it in partnership with WebBank and with Visa certainly takes some time in the development phase.

So brief history of the company, we’ve put together the very early team, you know, the first ten people at the beginning of 2017 and end of 2016. Spent 2017 building up a platform and developing the software, etc. towards the end of that year began to issue our first credit cards.

So we did that in a beta program, first just operational and then kind of expanding in terms of robustness of the data and then finally in the middle of 2018, we had finished the end-to-end testing of the program, etc. and we were able to start issuing our first credit cards to customers.

Peter: So have you gone through the 100,000 people on your list and does everybody have one who wants one?

Jason: So everybody on the list has the opportunity to apply.

Peter: Right.

Jason: So we are now publicly available, you can go to the website at petalcard.com and you can apply for the product right now.

Peter: Okay, so obviously you’ve got a few months of history behind you, you must have…the great thing about a credit card is that you get a pretty quick window into your credit performance. So what can you say, I know it has only been a few months, but what can you say so far about the performance of your portfolio?

Jason: Yeah, you know, even with a credit card it does take some time to really measure your performance. You know, you tend to see defaults on credit card loans later in the customer life cycle, year two, year three, etc. but there are a number of attributes that we can begin to look at like utilization of the credit line for instance.

So far, we’re feeling really good about our approach and I think that it has to do with the fact that we are not relying on an untested, exotic data set but that we’re talking about people’s income, their savings, their monthly expenses. So one of the things we’re most excited about is if you look at the population of folks who have come to us and qualified for the card with no prior experience of credit, the truly credit invisible segment, we’re seeing performance from that segment that mirrors the performance that we see from folks who have applied with prime credit scores, that’s in terms of their utilization, in terms of their enrollment in autopay which is another indication of folks that have the ability to easily pay their obligations.

We really think that we’ve been able to uncover a good segment of customers that we’ve been calling the invisible prime. You know, that from a traditional scoring perspective appear extremely high risk, but actually if you dig in a little bit further to the data you find that they are folks that are going to have a 750+ credit score, they just haven’t had the opportunity to build it yet.

Peter: Right, right, that makes sense. So then is your business model like a traditional credit card company, you’re making money off the interest? Is there any other way you’re generating income?

Jason: Interchange is really important in the credit card business.

Peter: Sure.

Jason: A lot of our income comes from the merchant fees as well, but those are the two primary sources, interchange and interest revenue.

Peter: Yeah, sure. So then how are you getting the money to fund these credit lines with these cards, like who has jumped in early to be part of the funding sources?

Jason: Sure, so our primary funding sources are Jefferies, the international investment bank and Silicon Valley Bank to date but we are set up from a legal perspective in a manner that’s very similar to a marketplace lender where we work with a bank to originate the loans, or in our case to originate the receivables and then those receivables are financed on the back end so we have these investors, Jefferies and Silicon Valley Bank for instance that essentially finance the receivables.

As we grow, we are planning to work with the sorts of investors that are interested in that asset class and sort of larger and larger institutions so eventually, we’re set up in a manner that will allow us to securitize just like any large credit company might do.

Peter: Right. Okay, so I downloaded your app before this interview and when you actually load it up it says…”a credit card with a conscience.” So obviously that’s sort of something that you’re promoting, what do you mean by that? Tell us a little bit more about sort of the thinking behind having that come up every time someone opens up your app.

Jason:  Sure, so when we started working on this product, we realized very quickly that when it comes to the new to credit audience, the problem is not just that people have trouble qualifying and when they do qualify they don’t get enough credit or their APR is too high. We also found that the needs and expectations of these consumers are not being well met by the traditional options.

I think that in the credit card space, generally, you have a lot of focus and attention on the most premium customers, sort of that tier of customers that have super prime credit scores and are looking for travel rewards and paying large annual fees, a lot of the marketing dollars and the thought and effort from the big institutions goes to fighting over those customers.

At the same time, if you look at the tens of millions of customers that are newer to their credit journey, the products don’t seem particularly thoughtful from our perspective. You see very little in terms of financial education, you see very little in the user experience that is tailored to the needs of that customer.

Really what people are looking for is the of kind simple, modern, transparent experience that they’ve come to expect from service providers across other facets of their life. I think that this trend towards greater transparency and towards wanting to do business with companies that will act in the customers’ best interest. This is a trend that is playing out on a very large scale and it’s just starting to take root in financial services.

So a lot of introductory credit cards are larded with fees, have very high interest rates and don’t help even a brand new customer who is brand new to credit to understand how to use the product responsibly. Almost everyone has either personally experienced or knows someone who has experienced the process of getting a first credit card and using it like it’s Monopoly money and running up a whole bunch of debt inadvertently so we’re trying to design a product that takes a totally different approach to that relationship.

We know that our customer group in particular would benefit from a product that’s easier to use, that helps you to make more informed financial decisions so we’re, like I said earlier, working to help our customers to financially succeed and not the alternative, we don’t want folks to pay unnecessary fees, we don’t want people to run up debt that they can’t pay back. We want, instead, for people to make the right financial decisions and set off successfully on their financial journey. That’s what we mean by “credit with a conscience.”

Peter: Right, got it. Okay, we’re almost out of time, but just a couple more questions. You’ve chosen an endeavor, you mentioned that already, it’s not easy starting a credit card company, you don’t get a bunch of…it’s not like a hot thing to go and start a credit card company like it might be a neo bank these days, but…so I’m curious now looking back…I mean, you’ve obviously overcome a great deal of hurdles and your alive and you’ve got a real business now, what’s the biggest challenge now for you guys as you’re starting to grow your company?

Jason: Yeah, you know, I think that for us, we’re starting to face the challenges of the scaling phase of the development of our business so we’ve been able to successfully develop the product, get a product to market that users are really responding to, that users like, that fills an unmet need in the market, but we now have to go from the small company and small program that we have today to a program that can support tens of thousands, if not hundreds of thousands or millions of customers.

So we are dramatically increasing our head count, we are over 60 people today. At this time last year, we were about 16, so really growing in terms of our own capabilities and I think along with that we’ll be looking to get the word out about the program and to really grow with our customers and make sure that we continue to deliver a product that is really useful and valuable to them over the long term.

Peter: Okay, so then last question then, in 2019, we’re still here at the beginning of 2019, what will success look like for you? What are your goals for this year?

Jason: We’ve set goals in a pretty ambitious manner. This year we are looking to expand our customer base by about 10X, we are looking to significantly increase the features and functionality that we offer to our customers and we’re looking to really establish ourselves as a legitimate alternative to the mainstream options in our category.

So today when you think about getting a first credit card, you ask someone on the street who might send you to Capital One or might send you to Bank of America. By this time next year, we think it would be amazing if folks added Petal to that conversation as something that people can check out and, you know, a real alternative to what’s previously existed in the category.

You know, if you look at the growth of marketplace lending in the personal loan category ten years ago, almost entirely dominated by the banks, in terms of online lending very little activity. Over the last decade, you know, we’ve seen the online marketplace lenders take something like 35% of that overall market share.

In the credit card category, I think where the personal lending, marketplace lending was ten years ago where there was huge consolidation in credit cards…I think the top four or five issuers had 90% of the market, all the products that are in the market come from a traditional bank.

But over the last year, there’s been something like $300 million invested in new technology focused startup credit cards so I think that, you know, we’re in the early days, but we’re going to see a similar transformation in this category just like we’re seeing in terms of the checking and neo bank, just like we’re seeing in wealth management and stock trading and like we have seen in some of the other lending categories. We’re very keen to be part of it on the ground floor.

Peter: Okay, well best of luck with that, Jason, I really appreciate you coming on the show today.

Jason: Thanks so much. Great chatting with you.

Peter: Okay, see you.

Jason: Alright, take care.

Peter: It is interesting to me that most of the innovation that is happening in the credit card space is really happening at the prime end of the spectrum. You’ve got all of these different reward cards, I see new ones coming out all the time that are really targeted for the premium customers, but in the subprime space, or in the non-prime space, shall we say, there’s a few secured credit cards and there’s certainly a handful of fintech companies trying to attack this problem, but there isn’t sort of this surge of innovation that you’ve seen in other areas of fintech.

So it will be interesting to see if Jason is right and it’s going to become the next frontier of fintech. They certainly have…you know, they’ve got some big goals and they’ve got an interesting approach, and I wish them all the best. It will be fascinating to watch them as they progress.

Anyway on that note, I will sign off. I very much appreciate your listening and I’ll catch you next time. Bye.

Today’s episode was sponsored by LendIt Fintech USA 2019, the world’s leading event in financial services innovation. It’s happening April 8th through 9th, at Moscone West in San Francisco. It’s going to be the largest fintech event held in the Bay Area in 2019. We’ll be covering online lending, blockchain, digital banking and much more. You can find out all about it and register at lendit.com.

 

PODCAST TRANSCRIPTION SESSION NO. 188 / ZOR GORELOV

Welcome to the Lend Academy Podcast, Episode No. 188. This is your host, Peter Renton, Founder of Lend Academy and Co-Founder of the LendIt Fintech Conference.

(music))

Today’s episode is sponsored by LendIt Fintech USA 2019, the world’s leading event in financial services innovation. It’s going to be happening April 8th thru 9th, at Moscone West in San Francisco. We’re going to be covering digital banking, blockchain, financial health and, of course, online lending, as well as other areas of fintech. There will be over 5,000 attendees, over 250 sponsors and registration is now open. Just go to lendit.com to register.

Peter Renton: Today on the show, I am delighted to welcome Zor Gorelov, he is the CEO and Co-Founder of Kasisto. Now Kasisto is a fascinating company, they’ve been around not that long, but they have developed a conversational AI platform for banking. So we talk about exactly what that is, I didn’t know, and I learned a lot in this conversation actually.

We talk about how it actually works in practice, we actually go through an example of a bank that has implemented Kasisto’s technology into their bank and the difference it has made for them. We talk about how these products learn, what makes them just really dedicated to banking, how they’re able to focus on that particular sector, we talk about the future of interaction. We obviously have voice and text and how that’s playing out and what is also coming down the track shortly at Kasisto. It was a fascinating interview, hope you enjoy the show.

Welcome to the podcast, Zor!

Zor Gorelov: Thank you, Peter, happy to be here and thank you for having me.

Peter: Okay, no problem. So I’d like to get these things started by giving the listeners a little bit of background so maybe you could tell us some of the things you’ve done in your career. You’ve had a pretty interesting career to date so why don’t you share with the listeners some of the highlights.

Zor: Yeah, I’m a software engineer by training and I worked in software companies, In the mid-90’s or so, I decided to fulfill my life’s dream and start my first software company which I did. The company was called BuzzCompany.com and at BuzzCompany we built enterprise messaging software, some Fortune 500 companies using that software and then from there, I moved on and I started a company called SpeechCycle and at SpeedCycle built a speech recognition activated virtual assistants for telcos.

I started doing this way, way back, you know, Telstra, Time Warner, Cable Vision, Cash Communications were all customers. Both of these businesses were venture-funded, were successful at this and then in 2013, I started Kasisto, I was Co-Founding CEO of all these ventures.

Before that, my interest was speech recognition natural language technology goes back many, many years when I worked at Bell Labs, one of the early speech recognition and natural language projects that were sponsored by Darpa and we were running the systems on super mini computers that were larger than the size of the conference room that I’m sitting in now (Peter laughs) and this technology in the past 20 to 25 years made tremendous progress and enabled us to get to where we are here and enabled companies like Kasisto creating really amazing humanlike conversations between AI systems and computers.

Peter: Right, right, yeah, that’s interesting. So what was the idea that led to the founding of Kasisto?

Zor: So first of all, Kasisto is a spin-off from Stanford Research Institute or SRI. That’s a very famous research lab that has decades of Artificial Intelligence experience. I think they started working with some of the systems in the 70’s so one of the largest independent R&D labs in the world. SRI also has a very efficient and well known venture licensing program and was the IT that just created SRI, gets commercialized and licensed to other companies and sometimes they create ventures.

Many of your listeners probably heard of Siri, Apple Siri. Siri was created at SRI before it was sold off to Apple, and actually, the history of Kasisto goes back to Siri. There was a team of scientists at SRI that stayed on and continued to work on next generation virtual assistant system which ultimately became KAI and then, of course, we’re using KAI in banking. So in a way, in the Artificial Intelligence way, Siri and KAI are related, well I can say that, Siri is KAI’s older cousin, not as smart in banking, but, you know, part of the family nonetheless.

To answer your question on what led me to this, well KAI has been fascinating with speech recognition and natural language at AI systems for most of my career. Like I said, I worked early on at Bell Labs and I believe that conversational user interface will continue to become more and more sort of main way users interact with computers, same way we interact with each other, same way you and I are communicating now.

What led to Kasisto idea is this basic premise that as banks go through a digital transformation, the relationship between consumers and banks become very transactional, you know, people check balances, transfer for money, they look things up and they move on, and I think oftentimes there’s an emotional connection that gets established between brands or banks in this case and customers, consumers is getting close. Our belief early on was that humanlike conversations was a way for banks to continue to engage with customers on digital channels and help them better understand their money, help them make better decisions about their money, all using humanlike exchanges.

Peter: Okay so then what is the difference between, you know, Siri or…obviously, there’s Alexa and Google’s got a product, I mean, there’s lots of these voice assistants now so what’s the difference between KAI….I mean, you said KAI is really for banking and finance so how is it similar and how is it different to these other main stream voice recognition systems?

Zor: Well first of all, KAI is the conversational AI platform, banks use KAI to build virtual assistants and chatbots that interact with their customers. So think of KAI as a banking brain that banks has made their own where they can create their own conversation, they can present those conversations that are on Waze, on mobile devices, on their websites, on Alexa, on Facebook Messenger and KAI knows how to have these conversations.

What makes KAI unique and different is that it is trained on banking and it knows and understands, banking, it knows, you know, debits and credits and withdrawals and deposits, it knows the current accounts, the same thing as checking accounts, it knows about FDs and CDs, it knows about account opening. You know, that’s what makes KAI unique plus it comes with the infrastructure that allows banks to rapidly deploy these systems and customize and brand those systems.

Peter: Right.

Zor: The other thing that makes KAI unique, KAI is not a search-like experience where you go on the website, you search and you get ten responses. KAI is not a search engine, KAI is a do engine, it actually can ask a question and not only does KAI answer the question, it will help you get things done. Like for example, you can go to KAI and say…hey, I’d like to make a payment on my credit card and KAI will come back and say….okay, I see that your balance is $1,000, do you like to make a minimum payment or you’d like to pay off.

You may say…well, I’d like to pay it off, but do I have enough money in my checking account, and KAI will come back and say…well, you know, you don’t have enough money in your checking account, but I see that you have enough money in savings, would you like to transfer? So it enables this humanlike conversation and helps consumers get things done and ultimately it helps consumers make better financial decisions about their money.

Peter: Right, right. So, you know, I can ask my bank through Alexa what my account balance is and what my credit card balance is, but, I guess, it’s pretty rudimentary, What you’re saying is if you’ve got an engine that can really do a whole bunch of different things so maybe we could start with an example. I know you’ve got some high profile banks that you have signed-up, why don’t you just take one of those, something that’s publicly available information and just tell us how they’re actually implementing your technology in their bank.

Zor: Of course. Before I do that, let me explain a little bit about what conversational AI is.

Peter: Okay, that’s probably a good idea.

Zor: Yes, conversational AI is really about enabling human and humanlike conversations between humans and machines. Conversational AI is not about having voice recognition or natural language to enable some of the features that users already do in their mobile banking apps on their websites.

Peter: Right.

Zor: That is not that interesting, right, you know, you know how to transfer money in your mobile banking app, you don’t need to go and voice-activate this feature. Some banks may choose to do that, but that’s not in our stuff. Where conversational AI becomes interesting… where users can start interacting with banks using their own language like for the first time, KAI allows banks to go to a microphone or give a text back for their users when their users go in and tell banks what they want. Think about the power, but, you know, what people say are thousands and thousands of different things that they want from their banks.

So conversational AI is really creating that new experiences, in other words, conversational AI is about enabling users to do things that they are not able to do on their mobile apps or on banking websites which tend to be very transactional. What did I spend on Uber last week, right, can we go quickly get an answer to that question in your mobile app, right, probably you can. Not only can you really do that in your mobile app, you probably want to call your bank to ask this question so think about calling your bank and say…hey, I want to know what I spent on Uber last week, they’ll probably hang up on you, right.

Peter: Right.

Zor: So conversational AI is really about creating that new experiences for users that they can get from their banking services. Some of these experiences…they didn’t exist before, you know, can I afford to go on vacation or should I buy a car? There are so many things that people express that are just simply not doable through any other means.

Peter: Okay.

Zor: So I’ll give you a story from one of our customers to answer your question. DBS, Development Bank of Singapore, is one of the largest banks in Southeast Asia. The CEO of the bank decided to build their international expansion strategy around this new mobile only bank that they call Digibank and they decided to launch this bank in India first. So this is mobile only bank, no branches, no call centers.

When they launched their mobile app, it had two unique features; one was a 90-second paperless account opening that was enabled through India’s Aadhar Biometrics Identification System and a virtual assistant called Digiba (?) that was powered by KAI. We trained KAI to answer thousands of different questions about banking. Today, the bank has 2.5 million customers, KAI is handling 80% of all interactions between consumers and banks through Artificial Intelligence, only 20% of these sessions go to the live chat agents. That enabled the bank to run Digibank in India at 1/5 of the cost of a traditional bank.

KAI, today, supports everything from customer on-boarding, how do I open an account, what documents do I need to open an account, where is the nearest biometrics identification center to customer education, which products I have, what interest rates do you charge, how do I upgrade my account to customer service, you know, I’m traveling to England, do I have to pay ATM fees when I get cash.

So this is the power of KAI that allowed a major bank in Southeast Asia to launch completely new digital mobile only offering and run it at a very cost effective manner. We believe that virtual assistants for both traditional banks as well as challenger banks is becoming a must have to enable any kind of true digital transformation.

Peter: Okay, so then how’s it actually being implemented? You’re answering 80% queries from customers, is this through virtual chat like a chatbot type thing or are there other delivery mechanisms for it?

Zor: That’s an excellent question that you asked. So KAI is built into a Digibank’s mobile app and users go in and they all kind of interact with it. All interactions, or 99.9% of all interactions that are handled by KAI today, are handled by DBS Digibank are handled through text.

Peter: Okay.

Zor: Now generally speaking, voice adoption in banking is interesting. We have customers running Alexa and then the demand continues to grow, but we are not really seeing massive adoption from the consumers on our own systems of voice as a preferred modality for interactions. Majority of our interactions across all of our systems are KAI-based.

Peter: Are you sort of agnostic on whether it’s voice or text as far as….is it the same behind-the-scenes engine that drives this or are you really geared up for text?

Zor: No, we’re actually agnostic. We view voice as another modality and consumers can choose to interact this voice, text or touch from that perspective. The industry lingos calls this multi-model system. KAI is also an omni-channel system, you know, you can start interacting with KAI on Alexa and then log-in to your mobile app and continue those interactions so it supports and it knows…we channel you on and it knows how to optimize interactions for your channel.

So, you know, you mentioned your bank in Alexa, I don’t know who your bank is and I know how Alexa’s permutation is done, but, you know, some banks continue to build syslog channels. They build something from Alexa and they go and build conversational experience for perhaps their mobile app or Facebook Messenger….you know, our vision for KAI is a brain that can interact with users and optimize those interactions independent on the channel they’re on.

For example, if you ask Alexa, show me my last ten transactions, you probably don’t want to sit in the kitchen and, you know, hear ten cryptic names for your transactions.

Peter: Right.

Zor: You know, when you ask that question of KAI, KAI is smart enough to know that this question is coming from Alexa and you’ll get a response that says, okay, well over the past ten transactions, you spent $582, would you like me to send the list to your mobile app and then it can initiate the transaction and you get a list of transactions on your mobile device which is much more meaningful customer experience.

In addition to that, we set up the ability to handle multiple channels and optimize your experiences in wherever channel. You know, you kind of start with voice in Alexa, you can  continue with text or touch on mobile device; KAI can also personalize your interactions with any of the user type or user segment. In other words, if you say, you know, I’d like to get a credit card or a life supply fuel gold card, depending on the use of KAI, if you are a high net worth individual versus millennial, you may get different behaviors from KAI.

Peter: Okay, okay, that’s really interesting. So I guess one of the things I’m interested in is how is KAI learning… like obviously, it’s conversational AI and it’s extremely complex to be able to have a detailed conversation. How is it getting better? What are the things….just because it’s learning from all the interactions…maybe you can just tease out a little bit about how it is able to improve itself.

Zor: So that’s another good question that we often get asked. To be frank with you, there are a lot of hype around AI. You know, we hear some people talk about self-learning and it’s a very popular topic, KAI uses a combination of supervised and unsupervised learning. Supervised learning is when KAI training is done by people and unsupervised learning is where we use machine learning technologies to improve KAI over time.

The process of training, actually, is shared by Kasisto, but also our customers. You know, these systems when they get deployed, it’s just like hiring people in a call center, they require some monitoring, some training, some performance improvements and we give our customers tools where in real-time they can monitor behavior of KAI-powered virtual assistants and they can actually effect that behavior and train KAI. Of course, we have our own teams looking at KAI and KAI interactions in improving KAI perform this as well.

I often get asked by banking executives about KAI and self-learning and I always go back to an example of a Microsoft bot called Tay. I don’t know if you’ve heard the story, 2016, I think Microsoft launched tutor bot and it allowed the users to train Tay and then the users trained Tay and they created a bot that was sexist and racist and Microsoft was not pleased with the results and the outcome of this experiment.

The banking world is very, very different, it’s a highly regulated industry and banks are very, very careful about what their virtual assistants are trained on and how they interact with their users, what they say, what they shouldn’t say so it’s a very tightly controlled and optimized process that relies on combinations of both supervised and unsupervised learning as well.

Peter: Right, right, okay, I got it. So it’s interesting to me that with this explosion of this voice interaction at home and then…..I was actually a bit surprised to hear you say you’ve got 99.9% of interactions with the one client, DBS, that’s doing….it’s a chatbot type text messages. Are there other examples of banks that are really moving more towards voice because it feels like voice is really becoming this sort of way we interact, but where are you at like with this journey from text or voice? Are there some banks that are doing a lot more voice than text?

Zor: I think banks that are doing voice are mostly doing Alexa-based implementations with us.

Peter: Okay.

Zor; With that, now the issues of data privacy are obviously of consideration like when you’re talking to your Alexa, your banking data is going to the Amazon cloud and banks have different perspectives on that. Some banks are more open to this, others are not as open, but I think the voice implementations are mostly…but, of course, Bank of America’s virtual assistant, Erica, you’ve heard Bank of America launching it…I think they are on the record saying that text and touch are by far two popular modalities for their interactions as well.

The question is why, right, and most people on their mobile….it’s one thing when you’re sitting in your kitchen and you’re asking Alexa about your balance, however, when you are on public transportation, subway or bus, you probably don’t want to get your phone out and start talking about your finances. I think there is a social factor that needs to be considered, and of course, most consumers in public settings like that are also worried about privacy. Of course, privacy is not what you say to a banking app, the privacy is really what you hear back……

Peter: Right.

Zor: ….because you can ask your banking app what’s my balance, what you don’t want to happen is people in New York City on the subway to hear that you have $10,000 in your checking account.

Peter: Right, that is true,

Zor: But there are ways to manage that as well because the smart assistants will actually detect that users have headphones and they can play it back. However, if you are on your speaker phone, you probably just want to display it on your device and not sound it out for the users.

Peter: Right, yeah. Okay, so then there’s other companies pursuing AI-powered products in financial services, I mean, there’s IBM Watson doing some things, Google’s doing some things, do you see these companies as competitors to you or are you kind of working together with them. How do you interact with the big tech companies?

Zor: Well we focus on banking and we do have competitors, obviously we see them in our accounts. Our focus is also on what our customers are asking us to do and our customers are asking us to build virtual assistants that are knowledgeable about banking, that can help users get things done in banking that are secure and are easy to manage. So that’s been our focus and we’re doing it in banking, KAI is trained on millions and millions of banking specific variances. You know, if you start as Google or IBM, you probably need to have enough data to make a virtual assistant smart from day one and that requires time.

Peter:  Right, right, for sure. So then are you working with any of the online banks and the online financial services firms that ….there’s lots of online lenders out there that would really benefit from a service like this. So are you focused purely on the banking sector?

Zor: We are primarily focused on working with large banks, however, we are also engaged with challenger banks and some fintechs as well, you know, depending on their maturity cycle and how many customers they have and the kind of customer acquisition goals. We are definitely looking at their market and is of great interest for us.

Peter: Right, right.

Zor: And then when you think about our customers, right, I mentioned Digibank. Digibank effectively a part of DBS, that is it’s version of online bank so we are working with both, with traditional banks and also we’re engaged with online banking. In fact, I think two weeks from now, we’ll be making a major announcement about KAI being implemented at one of the largest online banks in the world.

Peter: Okay, okay. We are recording this in early February and it will actually be published more than two weeks from right at this moment so I will make sure to link to that in the show notes when we actually publish that so people can know what you’re referring to.

Zor: Yeah.

Peter: Okay, so we’re running out of time, but just a couple more questions I’m really interested in. Let’s look out five years, how are we going to interact with our financial institutions, do you think it will still be this sort of mainly text with a little bit of voice or is there going to be a shift?

Zor: Well I think consumers will choose whether they want the voice or text and I think there will be natural progression. Voice as it matures will become more secure, I think there will be more voice usage naturally, it’s a major convenience of our feature, but I think it will be more interesting in five years.

AI systems will help democratize and personalize financial advice. I think there is a unique opportunity for conversational assistants to capture best knowledge, best practices that exist today, the best minds in finance and deliver that advice, deliver that guidance and help consumers, help investors make better financial decisions, help them improve their financial well being. I think over the next five years, that’s where the value in the conversational systems will start out.

Peter: Right.

Zor: And the voice and text, I think consumers will choose whatever channel is more appropriate for them. I do expect to see more voice. For me, most interesting part is really enabling these conversations to democratize and personalize financial advice and guidance.

Peter: Right, right, now that makes sense. It’s going to be super interesting and I feel like there’s a wide open space there that is yet to be occupied by anybody for what exactly you’re describing. Okay, so then last question, what are working on today? Let’s sort of bring it back a little bit into the near future, what are you working on today that is most exciting at Kasisto?

Zor: Well, we’re doing a number of very interesting things. First of all, our rules were in the retail banking and now we have customers applying KAI, deploying KAI for business banking and corporate banking use cases. In other words, we’re taking KAI and expanding its capabilities in finance in new areas, whether you’re a small business or you’re a CFO of a Fortune 500 company, now you can interact with KAI, not just about your personal bank account, but about the wires and tails or some other things so that’s the expansion to a new area of finance is of interest for us.

The other areas that we’re looking at …we are developing more tools and more infrastructure and more API’s to make it even easier for banks to deploy, manage and improve KAI. So these are the two initiatives that we are focused on; creating the systems that are broader in their knowledge about finance, but also create systems that are enabling banks to deploy KAI more wisely and make it easier, more efficient to manage and expand KAI.

Ultimately, we see KAI as the fabric, conversational fabric, that is used across all financial institutions to communicate with their various constituency using humanlike conversations powered by AI, of course.

Peter: That’s fascinating. You’ve got a really interesting company, Zor, and I appreciate your coming on the show today.

Zor: Great to be here, thank you so much for having me.

Peter: Okay, see you.

Zor: Bye.

Peter: You know, I think Zor is the third guest in the last six months that has talked about the same thing, about this intelligent assistant that has a wealth of financial knowledge that can help us navigate our financial lives. We’re not there yet, but, you know, with all of the technology that Kasisto is building, all the voice-powered devices that are out there, it doesn’t take much for us to see, whether it’s five years or ten years, but, certainly, in the near future, we are going to have an assistant that will be virtual and it will be personalized to us and it will gather the world’s knowledge of finances, specifically pertaining to your situation and allow you to make better financial decisions.

I actually think this is super exciting, it’s a way to really help you make better decisions and do things that are beneficial for their lives and not necessarily honing themselves because one thing that I’ve learned in the last few years is that it’s difficult for people to really embrace what is best for them and they really need a personalized guide, I think, to help them along the way.

Anyway on that note, I will sign off. I very much appreciate you listening and I’ll catch you next time. Bye.

Today’s episode was sponsored by LendIt Fintech USA 2019, the world’s leading event in financial services innovation. It’s happening April 8th thru 9th, at Moscone West in San Francisco. It’s going to be the largest fintech event held in the Bay Area in 2019. We’ll be covering online lending, blockchain, digital banking and much more. You can find out all about it and register at lendit.com.

 

PODCAST TRANSCRIPTION SESSION NO. 187 / NIMA GHAMSARI

Welcome to the Lend Academy Podcast, Episode No. 187. This is your host, Peter Renton, Founder of Lend Academy and Co-Founder of LendIt Fintech.

(music)

Today’s episode is sponsored by LendIt Fintech USA 2019, the world’s leading event in financial services innovation. It’s going to be happening April 8th through 9th, at Moscone West in San Francisco. We’re going to be covering digital banking, blockchain, financial health and of course, online lending as well as other areas of fintech. There will be over 5,000 attendees, over 250 sponsors and registration is now open. Just go to lendit.com to register.

Peter Renton: Today on the show, I am delighted to welcome Nima Ghamsari, he is the CEO and Founder at Blend. Now Blend is a fascinating company, they are really a software company that has built a platform, a digital platform, for simplifying the mortgage process. They’ve been very successful, they’ve got banks, all the way up to the size of Wells Fargo, down to community banks on their platform and they’re able to bring the mortgage process interestingly into a mobile device where people can complete the entire process on their device.

So we talk about how they’ve done that, we talk about what’s preventing mortgages from being processed in a more efficient way, we talk about how they’re able to get a large bank like Wells Fargo on board and we talk about their marketplace. They have a new Blend marketplace, we talk about anti-fraud and the addition of a very high profile advisory board member that they recently added. It was a fascinating interview, hope you enjoy the show.

Welcome to the podcast, Nima!

Nima Ghamsari: Thanks for having me, Peter.

Peter: Okay, my pleasure. So I like to get these things started by giving the listeners a little bit of background about yourself. I’d like actually to start…tell us about your story and how you came to the US and also your professional background.

Nima: Sure, so I was born in Iran and my family immigrated here in the 80’s, came here, became academics. I grew up in the Midwest, in Ohio, and you know one of the things that I was very fortunate to see was the impact that buying a home can have and my parents, they got a mortgage 20 years ago with very little money down, there was almost no money in their savings to put any money down.

They were able to get that mortgage 20 years ago and now they’re able to retire as a result. That house is fully paid off, it’s an asset, they just sold off and now they’re able to retire. So I guess that’s kind of one of the things that made me passionate about this industry is seeing my family directly impacted by it and of course, there are millions of other stories like that.

Peter: So then did the idea for Blend…is this something that germinated in your childhood or is this something that, you know, I know you’ve got a computer science degree from Stanford, when did you first think about the idea that was behind Blend?

Nima: Well I think almost nobody leaves college and says, I want to go build a mortgage technology company (Peter laughs) because almost nobody in college has gotten a mortgage. So I definitely didn’t think…I was at Stanford, I was getting my computer science degree, you know, my sister had gone into financial services, on the trading side, just before the crisis and then in 2008, when I graduated, it was just before the crisis hit and I was considering between going to financial services and joining the company that she was or one of the other companies out there in New York or staying in tech.

It was a tough decision because I did really think that there was an opportunity on both sides, but ultimately I ended up staying in tech and saying, you know what, I got great advice from a fellow entrepreneur who turned to me and said, Nima, if you ever want to build anything great, you should probably stay around here and work in tech because you can’t build things in New York, you know caught in this web. So anyway, I ended up joining a tech company here, it was Palantir in 2008, it was a fantastic experience and right then the entire financial services ecosystem started to collapse.

You know, Lehman Brothers went out of business, Citi, all of the others started to go down so I obviously looked like a genius because I hadn’t made the decision to go out there just a few months earlier, I looked like I had predicted something (Peter laughs), but it really was just luck. I was passionate about technology and in this crisis, a big part of Palantir’s business right after the crisis was working with the financial services institutions on their mortgage books to help them find better alternatives to foreclosure so that was how I got introduced into this space.

Peter: Okay, so you were introduced to that and you saw obviously a lot of people lost their homes, then what did you actually do? When you started the company, what was sort of the idea that really drove you to go and do this yourself?

Nima: As we were working with the financial services institutions on their mortgage books, I saw that basically everything that was being done in that space was being done using 20, 30, 40-year old technology and it was all paper-based. It was really bad for consumers because when you’re doing a bunch of paper-based things, it’s not the modern experience that people are starting to expect, it’s bad for the lenders, it’s high cost.

It was something that they couldn’t sustain as the other parts of the ecosystem were becoming more digital and it was bad for the system as a whole because, you know, I think…not to say that the crisis was caused by a lack of technology, but technology creates transparency, especially around data, a set of documents would have made it so much harder to make mistakes or do all the things that ultimately led to a lot of loans not going through and being as successful as they were.

So I felt like there was a real opportunity and to the earlier point I made around why consumers or why college students don’t leave college and go into mortgage startups, I was in this unique position, in 2012, when I saw this big opportunity, this big gap and this big impact, I felt like nobody else was going to do it if I didn’t do it. I felt like I as a technologist who had seen this space and really understood this space to some extent would be able to go in and make a real impact by building a team and working with the ecosystem.

Peter: Okay, so let’s just step back for a second. Why don’t you just explain exactly what Blend does, give us sort of the elevator pitch.

Nima: Sure, so what Blend does is we…it starts with the consumer when they’re first getting ready to apply for their loan and instead of asking you for a bunch of documents, as a consumer we ask you to, if you want, to aggregate your data instead. The benefit of this data over documents for consumers means that things can be done in a few taps for a consumer and all the information that’s needed to underwrite you as a loan holder would be instantaneously collected by the lender using our software.

We partner with lenders, we’re not a lender ourselves, we offer software as a service to the lenders, it’s a white labeled solution or grey labeled powered by Blend and that technology then in real time evaluates the data, gives the consumer an approval and then gives them a one-stop shop shopping list of here’s the next seven or eight items you have to do to close this loan.

And that’s the idea, creating that one tap or close to one tap approval and then that one-stop shop for consumers. I think that’s where sort of consumer behavior is driving across all different industries, but financial services will be, you know, I think pretty much all like that in the next five or ten years.

Peter: I notice you said one tap and not one click, is this really optimized for mobile? Is that where most of the people are coming from?

Nima: Yeah, especially in certain segments most of the traffic comes from mobile these days. In fact, when we started the company, people thought mobile didn’t make any sense to focus on because it’s such an important lending decision and it’s such an important consumer life decision, but it doesn’t mean it has to be a high friction decision.

It should be a highly thought out process, there should be a lot of education there, but it doesn’t mean it should be a high friction process and so making it so it can be mobile friendly….you know, 56% of people on our platform who are aged 30 to 40 applies on their mobile device. It’s not much lower for the next age band and so…and similar, especially with low income households when we’re talking about accessibility of credit. They are three times as likely to use a mobile device as a high income household and it’s because mobile devices are ubiquitous now and being able to have a mobile first experience means that there are certain populations that were previously really difficult to get to, that now people can serve. Those people might not want to go into a branch and go and talk to a banker before they know what they can afford.

Peter: Right, right. So I just want to dig in a little bit to the process so all the listeners can understand and I can understand it. So you said you sort of aggregate data…when someone is applying for a loan on a Blend-powered product, what are you actually doing? Are you connecting bank accounts, how are you able to sort of aggregate the data?

Nima: We connect to bank accounts, we connect to the bureaus, we connect to payroll accounts, we connect to tax accounts, the IRS. Essentially the idea is, you know, the consumer shouldn’t be messing with the data, the lender shouldn’t be messing with the data. The data should be coming from a verified third party and if it’s machine readable instead of a document, we can evaluate it in real time.

So one example of this process would be in the old way, let’s say you’re applying for a mortgage at ABC Bank and you go through as a consumer and they ask you for a bank statement. Of course, they need to know that you have enough money to get the mortgage and so they ask you for the bank statement, you provide the bank statement. A couple of days later, maybe somebody reads that bank statement, flags a few different items on there, checks to make sure the total balance is enough.

Then as they flag they go back to you a couple of days later with, hey, here’s the items that I need from you, Peter, in order to finish this loan. And they send you an e-sign or worse an actual physically signed document that they need from you and then you do the work on that, you send it back to them a couple of days later and this is why the mortgage process becomes so frustrating. There are hundreds of examples of these things.

With Blend, the alternative, you know, the new age way of doing this is…not everyone is forced to aggregate their data, but the ones that want to can, but the new age way of doing this is a consumer shows up, they connect their accounts for their bank account, for instance. We, in real time, verify the assets that are in the accounts to make sure they’re enough. In addition to, we extract income streams that are in that asset statement and we verify with the consumer in real time and then we also look for things that might be the anomalies that a bank might look for a week or two weeks later.

So for instance, you’re not supposed to have large deposits in your bank account that are loans from friends and count that towards your down payment. Another loan that counts for the down payment, kind of increases the amount that you’re being loaned so it needs to be accounted for properly. So if we flag those things in real time, instead of an underwriter finding it in a week, two weeks later, we can have a consumer explain it in real time, we can have the underwriting team get a certified document that tracks who and when that was found, where and when that was found, who signed for it, etc. and have that filed over in the right folder behind the scenes.

There’s no loss of information and there’s a full audit trail. So creating that one tap consumer aggregation and then one tap of all the anomalies that need to be tracked in a mortgage process in real time in our system is part of the intelligence that we hope to bring to the process more broadly.

Peter: Okay, so what about, like the documents that often times, you know, you have to go through anti-fraud, there are certain things that the process requires, is that all like a mobile experience, like can you take a photo of your driver’s license and send that in or how does it work?

Nima: Yeah, so we have a whole marketplace of providers that provide things like identity verification to ensure that the person who says that they’re this person is actually that person and that’s mobile friendly, we have the ability to take photos and grab a driver’s license and then scan that in, we have the ability to…and by creating this more marketplace approach, we enable these third party providers who are providing these services to integrate against a standardized platform that’s being used by a huge amount of the industry and then have that technology innovation happen much faster.

Peter: So then…I mean, it’s still…you know, when you talk to people today buying a house, most people are still having this sort of 6 to 8-week nightmare that’s sort of extremely stressful. How long do you think it’s going to be before that nightmare is over for the vast majority of consumers and they’re going to be in a more, you know, digital stream where maybe you can close in less than month, how long do you think it’ll be before that happens?

Nima: So I think the key inflection point for when mortgages become…the timeline compresses greatly, there’s probably two that are top of mind for me. The first one is when there’s enough adoption of this data instead of documents because then the information around assets, income, credit, employment are evaluated in real time and we see that compressing the timeline up to 20 days with some of our customers, we’re doing this in real time, what they call instant decision and that’s huge and that’s a big, big part of it.

And then the other part on the collateral is how do we get smarter and smarter about how we evaluate the value of collateral such that, you know, an appraisal that typically took seven to ten days to get back, we can have back sooner. How do we get a better marketplace for that, how do we find better information for the…maybe we don’t need an appraisal on some smaller number of cases and over time make that more of a digital process. So I think there’s two major bullets and if we can solve both here at Blend we can cut the time down to the minimum required by law.

Peter: Right, which I think is what, seven days, ten days, it’s pretty short, isn’t it?

Nima: You can have a mortgage in ten days, yeah.

Peter: Ten days, yeah, that will be nice. Can you tell us some examples of who are some of the banks or non-banks, for that matter that you’re working with today?

Nima: We did about $230 billion in mortgage applications last year. We work with banks ranging from small credit unions to some of the biggest banks in the world, Wells Fargo uses us, US Bank, down to small, you know, sort of credit unions and independent mortgage banks. We aim to be a system that’s sort of able to serve the entire ecosystem.

Peter: I imagine it’s a pretty different…I mean, a small community bank or credit union is going to be different to Wells Fargo. I imagine when you’re implementing this process…so just talk about Wells Fargo for a second, I mean, if I go and apply for a loan at Wells Fargo today, will that be using Blend technology or is it just a subset of what they’re doing?

Nima: If you go and apply on their website, you would be using Blend.

Peter: Okay, I guess, if you’re applying in a branch in person that’s probably their old system, I take it.

Nima: It sort of depends by channel how it’s being used.

Peter: So what was it like, I mean, how did you get a bank like Wells Fargo to get over the line and say, right, we need your technology. I mean, they could have built it themselves clearly. I’m sure this wasn’t an easy exercise for you so just tell me a bit about that process.

Nima: So I think there was a big shift that happened in banks and I don’t know exactly why or the exact moment it happened, but sometime in the last seven or ten years, there’s been a greater desire within the banking ecosystem of wanting to partner with financial services technology companies like ours, and I think part of the reason is because the rate of change of consumer behavior has gotten so great that speed has become king.

So if we can divvy up the work, you do this part, I do this part, then we can necessarily be faster than the alternative. And so I think that there’s been a great shift towards the partnership model which is very appreciated from I think both sides of the equation. I don’t want to have to go and build a lender and I don’t think, you know, as a bank you want to necessarily have to build all of your own technology anymore. There are parts that are really worth using out of the box and those are the parts that we aim to build and make available to the marketplace.

And so a lot of it has been first aligning on that, you know, here is what it takes to partner, here’s what a good division of responsibility is and here’s how we can get to our end goal the fastest together and aligning on speed of execution, aligning on iteration, aligning on not heavy customization because customization becomes a bit of a depreciating asset where now you have something that is being used that is no longer being supported because it’s custom by definition and so how you continue to grow when that’s the case.

So there are a lot of things that need to be philosophically aligned on to partner with a financial service institution or vice-versa for a financial services institution to partner with a fintech, but getting aligned on those things first and upfront has been critically important because without that alignment, I think we would have ended up sort of dying of indigestion as a small company.

Peter: Right, right. Do you think in ten years time, this is sort of going back to the question I asked before, but do you think in ten years time it will be impossible to walk into a branch and take out a loan, or do you think that that’s really going…taking out a mortgage loan, do you think that’s going to take a lot longer then ten years for that to disappear?

Nima: You know, Peter, I would say that that’s probably not the goal, right, if you go into the Apple Store, there’s this Genius Bar, there’s people who are helping you, there’s great ability to understand the products better. And granted these are physical products versus digital products, but I think that the physical retail world in some ways is just changing.

It’s becoming, I think, more consumer first and finding those really…I guess, if I can back up a second, the thing that I am focused on is there’s a really large spectrum of consumer behavior, many of whom want to talk to a human and want to talk to a human in their way of talking to a human, whether it’s in person or over the phone or on an online chat. I don’t think that that’s going to change, whether you’re buying an iPhone or you’re getting a mortgage, or buying a home, or whatever it is, I think that spectrum is going to exist forever, maybe not forever, but for a long, long time and we want to be the ones to enable that spectrum of behavior to be satisfied by the institution’s user software.

Peter: Yeah, yeah, fair enough. So I want to talk a bit about some of the things that has happened at Blend in recent months. You launched the Blend Marketplace last year, so why don’t you explain what that initiative is and what you’re trying to achieve and the traction that you’re getting.

Nima: One of the things that we have realized as we’ve gotten a lot of penetration into the financial institutions has been that we do a lot of volume, it was a lot of money, a lot of time it took to get those financial institutions on our system and continue to grow them. We realized that we, as the technology company, can no longer keep up with the demand of things that want to be built against our system.

We were getting approached by partners constantly saying, hey, can you integrate this thing, can you integrate this signing technology, can you integrate this closing technology, can you integrate this data source, can you integrate this credit provider and there’s so much that’s happening in this world now, there’s so much innovation that’s happening.

I didn’t want to be the bottleneck and I didn’t want to have our team build everything anymore for the things that…and I realized partnership was the best strategy, similar to what I had talked to the banks about, similar for us was how do we create a better set of partnerships and how do we enable our partners to do the things that they do best which is innovate and not be bottlenecked by us on our roadmap and our product roadmap.

So we created this marketplace to enable precisely that, the ability for a third party who is interested in integrating with Blend an open set of APIs in around certain parts of the process where they can build essentially an app and make it available to our customer base in a standardized way. And hopefully that means that they’re going to get in more doors, they’re going to work with more lenders and also for us, it means our customers are going to get more value. For our customers it means their customers, the consumers, are happier because the process is more connected and simpler.

Peter: So can you give us some examples of the type of companies that are in the marketplace?

Nima: Sure, so we have a number of CRMs that connect to Blend. You know, a lot of different banks use different ways of managing their customer relationships and so information asymmetry is not a good thing, you want to have the same information in both systems. The CRMs are connected to our marketplace and the data in one shows up in the the other and vice-versa, as an example.

Also, some of the lead gen providers, the online marketplaces that point out to or link out to our lenders from their online search tools like LendingTree, they connect to Blend. Credit providers, there’s so many different credit agencies out there, we want to be able to support them for our customer base; they’re connected in our marketplace as well.

Peter: Okay, okay, but interestingly you also launched I was reading an insurance agency last year, it’s interesting that you chose to…I’m curious to know why you chose to do that as opposed to just adding them into your marketplace and connecting there, and is this a standalone business or are you really just…is this really to be offering insurance inside the Blend software?

Nima: Well that is actually done through partnerships as well, the insurance marketplace was done through partnership as well, Peter, where we partner with a number of carriers and we show them as a marketplace to the consumers at the right point of the process. We do not do this as a standalone, we only do this as part of the mortgage process because we want to streamline the mortgage process for our customers and their customers and we are sort of…the mechanics of being able to create a marketplace like that is we have to become a licensed agency and so we did that.

And then we created the partnerships, got them in the marketplace. Now a consumer can go in and in a couple of taps, get a full quote for insurance from a number of carriers and create kind of the best possible experience for them.

Peter: Right, okay, okay, that makes sense, that makes sense. So I want to talk about anti-fraud for a minute because, you know, in the financial crisis anyone…you could lie, they even called them liar loans I think, you could sort of lie on your application about how much money you earned and that sort of thing. I’m not so much talking about fraud insofar as someone is trying to really steal money, but they’re trying to get a mortgage that they really don’t qualify for. So how are you combating that today with your software?

Nima: I think to the credit of the system that’s in place now, it is very, very difficult to get a loan that you’re not qualified for because there’s so many requirements around verifying assets, income, credit, etc. that are required to be done now which were not necessarily required to be done before. The problem that’s created is that’s created a lot of overhead, I shouldn’t just say overhead, a lot of human capital…using technology powering that for most lenders and so what that means as a lender is, mostly before it was you would collect a bunch of documents and read through it and then flag things and go back and forth, the process I mentioned earlier. The problem with that approach is there’s still some possibility of fraud because those can be altered.

So if somebody doesn’t catch something in reading through the documents or catch an inconsistency between your pay stub and your bank statement, you know, maybe there’s a possibility that there’s still some fraud. Now what we do is we go and we get the data from the source and it’s not altered by the consumer or the lender, it’s purely a third party that shows up in Blend and it can’t be changed and I think that’s a huge benefit because not only is it cheaper and a better experience, but because it can’t be changed, we can be really sure the data is the data that should be used to underwrite that loan.

Peter: Okay, okay. So I want to talk about a big name that I read that’s joined your advisory board Jack Lew, who’s the former Treasury Secretary, certainly a very significant name in the world of finance, how did you get him interested into joining a company like yours?

Nima: I think we had a shared belief that after the crisis, things could be better. He had a very different view, obviously, we came from different perspectives where he has a very policy perspective on things and I have a very technology perspective and I was introduced to him through an investor and we talked about some of these things and it just felt like a really good fit and something that he could help us to accelerate, in terms of understanding how to fit in with some of the aspects of other constituents in the industry, policy, etc. So we had a common, I guess, vision for how things could be and were able to come to an understanding that it would be good to work together.

Peter: I’m curious about the policy piece.  Is he helping you navigate that world because certainly there’s a lot of…I mean, Washington has still…there’s Dodd-Frank and all sorts of other things in place that are impacting the mortgage industry, so is he helping you navigate that world or is there something specific that he’s working on?

Nima: I guess from a high level perspective Blend as a company has been paying attention to compliance and policy since we were founded because mortgage is such a regulated space…

Peter: Sure.

Nima: ….and (inaudible) we’ve reached volume where we have to and our customers won’t even use our product if we don’t. Where he’s really helpful with us right now is we have a few kind of special projects that we’re working on that will be incredibly impactful, technology projects that will be incredibly impactful if successful and are also, I guess, somewhat complicated from a policy perspective in a good way, right. These are things that will be really, really good for consumers and really good for all sorts of constituents in the industry, but we had to find a way to navigate all that and that’s where he’s been really valuable.

Peter: Right, right, got it. Okay, so I think you mentioned this earlier, but I’d love to know…tease a little bit out about the scale you’re at today, how many employees you have, I mean, how many mortgage applications you’re processing. I’m curious even about what percentage of US mortgages are going through Blend’s systems now. Do you have some of that info?

Nima: Yeah, we did about $230 billion last year, I think we’ll do a multiple of that this year because we have a number of customers who are scaling up mortgage applications. Our customers represent more than 25% of the mortgage market, we had our best…you know, despite I think there’s some macro things, interest rates, things like that, that are in flux, and despite that we had our best volume weeks ever in the first couple of weeks of this year already which is fantastic to see our lenders thriving in a difficult environment. We have 350 employees spread from the West Coast to the East Coast, mostly in San Francisco, although we have a pretty big New York presence, and we’re growing pretty quickly and hopefully we can find a way to continue to scale and grow our impact at the pace that we have up till now.

Peter: So are you looking beyond mortgages? There’s obviously lots of other verticals, I mean, mortgages are the biggest, but there’s clearly other places that could use some improvements in how loans are processed. So are you looking at other verticals?

Nima: As we’ve started to work with and become the trusted partner to these banks, I’ve actually started to hear that there’s a lot of applicability to the things that we do around data verification, understanding the consumer’s credit in real time that would apply to other aspects of consumer finance, other aspects of consumer lending and so we’ve started to understand and get a perspective that our product and platform could be valuable in those areas and started to expand.

We launched home equity last year, we’ve launched some other products end of last year as well, and we’re hoping to continue to expand. I think there’s a lot of overlap between underwriting a consumer in one tap for a mortgage and all the other products and we think we can serve the institutions across all their needs.

Peter: Sure because I mean in some ways the mortgage loan is the most complicated. It would be easier, I imagine, even to do an auto loan or home equity obviously is still very, very much a real estate product, but I could see many different ways.

Anyway, we’re just about out of time, so last question, I’m curious about what are you most excited about for this year, what’s on tap for Blend in 2019?

Nima: What I’m most excited for Blend in 2019 is we are going to have the first one tap consumer approval for a mortgage and that’s a full verified approval, I believe in 2019 which will be a fantastic moment for hopefully the whole industry.

I’m also excited to…you know, as we’ve gotten deeper into the process we’re going to have our first end-to-end workflow done in Blend, meaning every aspect of, not necessarily the back office aspects which are handled by loan origination systems, but everything that the consumer has to do all done in one system. There’s a lot of moving pieces from the application to approval to, you know, the loan estimate, to the appraisal and title and insurance, to the closing disclosure to the closing itself. There’s a lot of components to that and getting that all together has pretty much never been done before for consumers and so we’re excited that that’s going to happen. We think it’s going to happen this year.

Peter: That is fascinating, fascinating indeed. Well I wish you the best of luck and I really appreciate you coming on the show today, Nima.

Nima: Yeah, thank you so much, Peter.

Peter: Okay, see you.

You know, Blend are doing some really amazing work, there’s no question about that. It’s interesting what Nima said about the bank branch question I asked, whether it would be possible to take out a mortgage in a bank branch and I think sometimes, most of us in fintech, myself certainly included, we tend to forget that people still want face-to-face interactions and doing it online is not the right way, not the preferred way for everybody to operate.

Even though it may be more efficient, even though it certainly will be more convenient, people like person to person contact and I think it’s something to keep in mind as we build all of these wonderful automated systems that the human touch, the personal contact is something that is still very much treasured by a good percentage of the population.

Anyway on that note, I will sign off. I very much appreciate your listening and I’ll catch you next time. Bye.

Today’s episode was sponsored by LendIt Fintech USA 2019, the world’s leading event in financial services innovation. It’s happening April 8th through 9th, at Moscone West in San Francisco. It’s going to be the largest fintech event held in the Bay Area in 2019. We’ll be covering online lending, blockchain, digital banking and much more. You can find out all about it and register at lendit.com.

 

PODCAST TRANSCRIPTION SESSION NO. 186 / SUSAN EHRLICH

Welcome to the Lend Academy Podcast, Episode No. 186. This is your host, Peter Renton, Founder of Lend Academy and Co-Founder of LendIt Fintech.

(music)

Today’s podcast is sponsored by Experian’s Clarity Services. They are the leading sub-prime consumer credit reporting agency providing innovative risk management solutions to address the full consumer credit life cycle. Clarity leverages the combined power of the largest and most comprehensive alternative credit data source with traditional bureau data to provide a more complete view of a consumer’s financial behavior. Clarity is committed to providing products that address rapidly changing market conditions. You can learn more by visiting clarityservices.com/solutions

Peter Renton: Today on the show, I am delighted to welcome Susan Ehrlich, she is the CEO of Earnest. Now Earnest is an interesting company, they are one of the largest student loan refinancing companies. In fact, Susan shares in the show that they’re now number two, as far as loan volume goes, and they also do personal loans, they’ve been around for many years.

They were bought by Navient, the large student loan servicing company back in 2017 so we wanted to talk a little bit about that, talk about how much she interfaces with Navient; we talk about the student loan crisis and what Susan thinks about that. We obviously talk about the products that they offer, their approach to underwriting, acquisition channels and cross-selling and much more. It was a fascinating interview, I hope you enjoy the show.

Welcome to the podcast, Susan!

Susan Ehrlich: Thank you, thanks for having me.

Peter: Sure, so I like to get these things started by giving the listeners a little bit of background about yourself. You’ve had an interesting career to date and why don’t you share some of the highlights with the listeners.

Susan: Yeah, of course. You know, I think my career so far has really had three chapters. I began my career in traditional banking and then I shifted over to retail and most recently, I’m now in the financial technology space. So I really feel like I’ve been a part of that transformation that both banking and retail have been impacted by from bricks and mortar to digital.

My career started with Citibank in New York City, followed by Providian in San Francisco. These were kind of the “go go” days of credit card marketing where credit cards were democratizing access to credit, credit scores were race and gender blind and we were able to expand access to credit for people who hadn’t had that before. I really loved the left brain/right brain aspects of direct marketing, that combination of the analytical underwriting and pricing and the qualitative marketing and communication.

In the second part of my career, I moved over to retail finance, chose the exact wrong time to be doing that. It was in the midst of the financial crisis so you had retailers losing sales as the economy was tanking and banks pulling back on credit so it was an insanely tough place to be. I was working with Sears and Kmart at the time and we actually dipped into an old playbook and brought back layaway and Christmas club and installment loans at point of sale and turned layaway from kind of a consumer accommodation that we used to do ad hoc in store into a billion dollar business for Sears and Kmart in the middle of the financial crisis.

From there, I kind of shifted from…I took that brick and mortar retail to online retail step and moved over to Amazon, spent about a year and a half there and with that Amazon tech experience in my background moved over to fintech and spent some time at Lending Club, at Simple, before now joining Earnest.

Peter: Sure, so then what was it that…why did you take the job at Earnest? I’m curious to sort of get your perspective on why, moving to Earnest.

Susan: Sure, that’s a great question. You know, because before Earnest I was at Simple, I was learning a new craft as the chief financial officer at Simple, a role I had not held previously at any company I’d worked for before. I was enjoying the foodie culture in Portland and perfectly comfortable when I was contacted by a recruiter about the opportunity at Earnest. I had known Earnest already, I had met the founders, we had on and off talked about partnering opportunities and so when I was approached about the opportunity I knew more about the company than most people would.

I was very impressed with the underwriting, with the brand they had built and the customer experience they had created. I’d also been following the explosion in the student debt market, I was an advisor to Gradifi and I really believed in the mission that Earnest was focused on to help clients get a better deal. But I’d also be remiss if I didn’t say that the opportunity to lead a company as CEO and the chance to move to one of my favorite cities, San Francisco, were also draws, for sure.

Peter: Right, right. So let’s talk a little bit about Earnest and the product suite that you have. I mean, I know that Earnest began refinancing student loans, but what is the mix of products today?

Susan: Yeah, you know, interestingly, Earnest launched its first product with a personal loan in 2014.

Peter: I didn’t know that.

Susan: Yeah, it was Louis and Ben, the founders, used Boston as a test market since there was a high concentration of young professionals. They were really focused initially on super prime personal loan and it wasn’t until the following year, in 2015, when the company raised their Series A that they announced the launch of student loan refinancing.

Peter: Okay.

Susan: So it was actually the second product that the company had and along the way we’ve tested additional areas. We have a handful of auto loans, we were in the mortgage business last year, we’ve now exited that space. We’re focused today in installment lending with a strong focus on students. We are continuing to evolve our student loan refi product and we’re adding a student loan in 2019.

Peter: Okay, okay, so for existing students not graduates.

Susan: Correct, that’s right.

Peter: Got it, got it. So, you know, most people know…I’ll just to refresh everybody’s memory that Navient, the very large student loan servicer, acquired Earnest in 2017 so you’ve obviously come along after the acquisition. I’m curious about…obviously, you were comfortable with the structure of the company taking the job as CEO, but is Earnest really…is it hands-off when it comes to Navient or how much do you actually interface with the mother ship, shall we say?

Susan: Yeah, you know, this past year has been one where we’ve really tried to explore a bit how that relationship should work. We are a wholly-owned subsidiary so we operate fairly independently, we maintain our own brand, identity and marketing and you can see that in how we go to market and we staff and train our own employees, our own client happiness team, our own credit, product and engineering teams. Where we’ve most benefitted from the acquisition and the integration with Navient has really been with respect to access to capital.

You know, in Earnest’s old days, as with many fintechs, that steady access to capital is a huge challenge and it causes a lot of volatility in how companies operate. And so now that we’ve got that steady source and supply that Navient helps to provide us, we’ve really been able to grow from 5th to 2nd, in terms of market volume, in student loan refi and just continue on a very steady growth path which has been great.

Peter: Okay.

Susan: I think in return, you know, in terms of…that’s kind of what Navient has provided for us. I think, in return, we’ve really helped to showcase for them how to take a more user-centered approach to product design and to thinking about the client. We run a usability lab as part of Earnest’s standard business as usual operations. It’s run by our product, design and customer research teams and it’s been the most frequently visited part of Earnest from Navient. So I think that it’s early days, but I think that…you know, we look forward to continuing to impact their thinking about client and client experience and we thank them for their assistance in helping us access the capital markets.

Peter: Okay, so I want to step back for a second and just talk about student loans. Obviously, this is a big part of what you guys do and much has been written about the student loan crisis. I’m not sure what the exact number these days, $1.5 trillion outstanding, I know that defaults are going up. When you look at this country today and the student loan massive debt that many, many young people are taking on early in their lives, what do you think is needed to really end the crisis or to change things up?

Susan:  Yeah, it’s definitely a challenge of our time and I don’t think there’s anyone in the country who wouldn’t agree it’s an issue for our younger generation where the burden is falling most heavily. You know, when I look at the big picture, I kind of break this into two parts. There’s originations, the new student loans that customers are taking on and then there’s the existing loans and I think, you know, as a nation, we’re starting to rethink the origination part.

I think there are times when student loans are appropriate, but there are clearly degrees where it’s not worth taking a huge loan for and I think people are beginning to look at the cost benefit of education in a more sensible way and I think that’s a good thing. Personally, and to be clear, I’m speaking not for Earnest or for Navient, but I actually think universities should have more skin in the game than they do today. I think, you know, from my experience here at Earnest, I can see that graduation rates are a key determinant in whether a student loan gets repaid.

Peter: Sure.

Susan: And if a student is getting accepted by a school and they’re taking out a loan for their tuition and fees, but they don’t graduate with a degree, that’s commonly the reason they are unable to repay the loan so I personally think universities and colleges should take more responsibility for that. They should be willing to guarantee a student loan. I think that, you know, taking a page out of my retailer history and playbook, I think that would really be standing behind their students and would be a money back guarantee. I think it would be a real game changer and I’d like to see colleges and universities considering that.

Peter: Yeah, I couldn’t agree more. I feel like we’re going to move to that direction, something has to give. I mean, the top schools are going to continue to attract many, many students…as you say, not all of them are going to graduate and if you’re going to Harvard and you’re paying whatever it is, $60,000/$70,000 a year, you’re there for two years and you don’t graduate, you drop out, something happens, I mean, that’s a really bad outcome for that person potentially.

I feel like we’ve got so much data now available, look at the data that we use in credit, in personal loans, small business loans, what have you, there is so much data available and yet I feel like the universities…we should be using the data. There is information on graduation rates, but I’d like to see it, what is the graduation rate by major, what is the starting salary by major…

Susan: Agreed.

Peter: …all of that sort of information should be available so when kids go off to college, they are armed with full knowledge of what they’re getting into….

Susan: I agree.

Peter: …and I love the idea of having universities actually guarantee the loan, at least a portion of it. That would change everything I think overnight…I think it would.

Susan: And I think it’s, you know, a guarantee always sits in the background, right,  it doesn’t have to be activated…

Peter: Sure.

Susan: …unless you’re in a situation where something has turned out not the way you expected. So I think it would be very easy to implement, easy for a university to do, but I do agree with you. I think more transparency and information so that a student, with their parents, can make a better decision up front and I think a university really standing behind their commitment to graduate that student would be a very important signal to send. In an era where universities are going to continue to compete more and more for students, I think that could be a really powerful message to send.

Peter: Sure. Moving along, you know, you operate obviously in a very competitive market, the online lending space is much more competitive today than it was five years ago and I’m curious about…maybe we can take the student loan product and the personal loan product, I mean, they’re obviously two quite different markets, how do you differentiate yourself with the other student loan refinancing companies and the other personal loan providers?

Susan: Yeah, you know, in the product categories that we’re competing, they’re largely driven by price, but we are differentiating in a couple of regards. The first is we focus on a very high touch, very human interaction. Our in-house customer service team we call, client happiness, and we’re very committed to making sure that we’re…folks have contact with us, it is very intuitive, it’s very clear they’re getting the information that they need to make the decisions that they need to. We’re also very committed to leveraging technology to create a digital experience that makes it very easy and intuitive for a customer to understand our product and for our client happiness team members to service that client when they need it.

And I’m really proud of the fact that we are the only lender that offers precision pricing. This is something that’s in our student loan refinance product and what precision pricing is it enables a client to set the exact monthly payment they want. In student loan refinance, it’s more traditional for the lenders to force clients to choose from a few options, a 5-year term, a 10-year term. At Earnest, by using precision pricing and working back from what the client is looking for, we let the client set the monthly payment amount that they want to pay, the exact amount to the penny.

From that, we work back to what the loan term and price for that loan would be and the result of that is, you know, you may not have a 10-year loan, you may have an 11-year loan, but it’s going to enable you to pay exactly the thousand dollars a month that you want to be paying to pay back your loan and we’re going to set that interest rate at the lowest possible rate that matches that monthly payment. So the client gets the exact amount they’re looking for, it reduces for Navient and our securitization and investors any pre-payment risks so it’s a win-win and we’re the exclusive provider of that and we get a lot of good positive customer feedback for it.

Peter: Interesting, it makes sense. There’s no reason why the term of the loan shouldn’t be an output rather than an input. I know Marcus did this when they launched in personal loans, that was one of their unique offerings. They did it in the personal loan space and I feel like….because so many people, they know they can afford whatever it is, $500 a month, $700 a month, and that’s what they can afford. Obviously, they want to pay the least amount over time, but if you give them something that’s $900 a month and they can only afford $500 a month, yet it’s the lowest rate, that’s still not going to be a good outcome. So I think that’s what makes the most sense.

Susan: I agree, in this day and age too, you know, I think banks worked back from what did the market want, what were investors interested in and so they map to 5-year, 10-year, 15-year. In this day and age, you can generate the loan agreement real time and, again, by being able to give clients exactly what they’re looking for, you know, they’re comfortable with and committed to making that payment consistently. It puts control in the client’s hands and it ultimately creates a better experience for everybody.

Peter: So right now, that’s just in your student loan refinancing product, it’s not in the personal loan?

Susan: It is, that’s correct.

Peter: Okay, so are you doing like…for the personal loans, are you doing a lot of cross-selling with personal loans, are customers coming from other channels? Maybe let’s firstly answer how much are you doing cross-selling with your large student loan database?

Susan: You know, cross-sell hasn’t really been an emphasis for us now just because we’re seeing more opportunity with organic growth and we really are putting a very heavy emphasis on student loan refinance. We’ve just seen more opportunity in the market there for us and we’re going to stay committed there and I think we’ll be, as I mentioned doubling down on both student loan refinance and looking at in-school student loans in 2019.

Peter: Okay, so then how are you finding your customers, what are the main channels that you’re using?

Susan: A wide range of channels as all lenders typically do, but you know, our main and defensible channel is really word-of-mouth and existing client referrals which has allowed us to compete really effectively and to reach the number two market position in 2018 without a 9-figure marketing budget so we’re really pleased and proud with that result.

Peter: Right, okay. And then so let’s talk about underwriting for a little bit. I’m curious about what your approach is here, the technology you use, the data sources you’re using. Can you give us a little bit of color on that?

Susan: Yeah, I think, you know certainly in the early days of fintech there was a lot of talk about new data sources and new credit models and I think from our experience it turns out that it’s perhaps not as complicated as people thought. You know, the most important indicator is income and beyond that debt to income so that’s really where we’ve been focused on how we evaluate free cash flow and to help make sure that we’re putting customers in loans that they can afford and with precision pricing payments that they can comfortably repay.

You know, a big part of our process has been making it simpler and faster for us to get the information we need to confirm income and validate that and move people through as automated a process as we can. The faster we can get them to a credit decision, the more quickly they can begin saving money.

Peter: Right, right, okay. So something else, I’m looking at your LinkedIn profile, I’m curious about…you were very much involved with the Center for Financial Services Innovation, it looks like you were Chairman of the Board there for many years and we’ve had Jennifer Tescher on the show here, I’m curious about how your time there, how that sort of informs what you’re doing at Earnest because obviously the CFSI is very much about financial inclusion and building, creating products that are win-win and helpful for the underserved and what not. Tell us a little bit about your time there and how it applies to your time at Earnest.

Susan: Yeah, absolutely. I’m really pleased and proud of the work that Jen and the team at CFSI have had over time. You know, I, like Jen am very committed to a mission of inclusion and making a meaningful difference in people’s financial lives and, you know, I think that really played a part in my coming to Earnest seeing an opportunity to take what the company was doing and really extend further the reach and opportunity in the area of student loan refinance.

I’ll give you an example, when I got to Earnest this past summer in July, we had a group of MBA students who were interning with Earnest and one of the projects that we had asked them to take on was to calculate how much we’ve saved our clients since the company got started five years ago.

At that point we had refinanced about $3 billion of student loans and when we calculated the savings, we had generated just over $400 million in total interest expense saved and that’s a consumer benefit that was not available before the advent of student loan refi and talk about a disruptive force for good, an opportunity to improve consumer health which is very much the focus that CFSI has these days.

So on an individual level, that client who’s refinancing, shortening their loan term, speeding up their pay down is saving $31,000 over the life of their loan. That’s a life changing amount of money and something that we’re really proud to play our part in helping to improve consumer financial health. If you have the opportunity to refinance, you should take advantage of it. There’s meaningful money that can be saved up toward buying a house, paying for a car, taking a vacation, you know, it’s life changing.

Peter: Right, I completely agree. It’s like getting a tax cut in some ways where you suddenly have more money every month and given how much burden so many people are under and anything that you can do to ease that burden is certainly worthwhile, a worthwhile cause.

Susan: Sure. In the Bay Area, $31,000 might not add up to a lot of money, but it’s a down payment on a house, it’s the price of a car. I think it changes the trajectory of people’s lives and we’re just proud to be able to play a part in that and put the client at the center of what we’re doing. We’re very mission-driven.

Peter: So do you think that…I imagine most graduates now…obviously, student loan refinancing didn’t exist ten years ago, you know, for many reasons, but do you think that most or what percentage of graduates do you think now…like some of these graduates obviously have federal student loans. I know I’ve had one of my colleagues here at work has got a very low interest rate and tried to refinance and it just wasn’t worth it, but those that have private student loans. Some of them are, 8, 10, 12%, do you think…what percentage of them are still out there, do you think, that have not been refinanced?

Susan: Yeah, there’s…you know, as you mentioned earlier, the volume of existing student loans that are out there is in the order of $1.5 trillion. We’ve made a dent in that universe, we’re a little up over $4 billion in student loans refinanced. Obviously, SoFi is a bigger player in this category than we are, but collectively, you know, we’ve only made a tiny dent in the opportunity that’s there. Variable rate loans will continue to see rates increased on those as rates rise and continue to rise so I think, you know, students will continue to graduate with student debt to be paid back.

And so, I think, we expect to continue to see the market remain sizable and growing into the near future and anything that we can do to help improve the financial circumstances for our clients by looking into and refinancing is worth doing. It’s very easy to come online and do a rate check to see what the benefit can be, it’s a 2-minute exercise and I think anybody who has graduated from school and has a job should do themselves the favor of just checking and making sure there isn’t a better deal out there.

Peter: Right, right, for sure. So I want to talk a little bit about the funding of these loans. I’m particularly interested in the context of what you said earlier where you have these loan terms that are an output rather than an input to closing a deal. So how are you funding these loans, is it all on balance sheet, are you doing securitizations, what is the mechanism you’re using?

Susan: Yeah, we’re leveraging the access that we have now through Navient to a strong balance sheet and so we fund our loans on balance sheet and then on a periodic basis, we’re executing asset-backed securitizations to improve our liquidity and reduce the balance sheet stress.

Peter: So how does it work when you’ve got all these sort of like 11-year loan terms? Are you sort of packaging them all up into one group that is all the same loan term or how is it working?

Susan: Yeah, you know, as they structure the securitizations, it’s going to be a mix of payments and repayment terms and schedules and so that’s just in the pool and factored into the cash flows.

Peter: Right, right. Okay, so we’re just about out of time, but last question. We’re recording this in early January of 2019, and I’m curious about what your….as you’re looking ahead to this year, what are you most excited about for Earnest in 2019?

Susan: Yeah, thanks for the opportunity to share. So first off, we’re very excited about the new product launch that will be coming in the first half of this year so please stay tuned for that. We’re also looking forward to getting bi-weekly payments back as an option in our student loan refi business. We think that’s going to be another key differentiator.

And you know, we’re certainly actively hiring so we’re looking for key members of our teams in the area of engineering, product, marketing and risk so if there are listeners out there who are interested in and intrigued by what they’ve heard, I’d love to hear from them. And you know, we’re looking forward to just continuing to do what we’ve been doing and proving to be really good at which is helping clients save money by refinancing their student loans.

Peter: Okay, well on that note, we will have to end it there. I very much appreciate you coming on the show today, Susan.

Susan: Thanks so much, Peter, appreciate you having me.

Peter: Okay, see you.

Susan: Bye now.

Peter: One of these days, I would like to think that the total outstanding student loan balance will start to fall. It’s been going up, I remember when it crossed $1 trillion, it wasn’t that long ago and now it’s up around the $1.5 trillion mark and I would like to think that one day it will actually go back down below $1 trillion. Certainly companies like Earnest are helping to make these loans more affordable for people after they graduate and even when they’re in school.

I also think that the idea that Susan had about having schools guarantee some of these loans, I think that’s super interesting and one thing that we’re going to be covering at LendIt in April. I think this whole idea about schools having skin in the game, really having some sort of incentive in the outcomes beyond just, oh look at our graduation rates or whatever. I feel like this is where we can really move the needle and I feel like going to school in ten years time is going to be very different. The application process will be very different to what it is like today as I think more of this sort of results-based orientation for students will certainly take center stage.

Anyway on that note, I will sign off. I very much appreciate your listening and I’ll catch you next time. Bye.

Today’s episode was sponsored by Experian’s Clarity Services. Clarity’s suite of FCRA-regulated reports and predictive scores yield significant insight into a consumer’s financial behavior throughout the alternative financial services industry. Clarity delivers data-driven risk management solutions that address prospecting, credit evaluation, fraud detection, portfolio management and collections. You can learn more by visiting clarityservices.com/solutions.

 

PODCAST TRANSCRIPTION SESSION NO. 185 / JEFFREY MEILER

Welcome to the Lend Academy Podcast, Episode No. 185. This is your host, Peter Renton, Founder of Lend Academy and Co-Founder of LendIt Fintech.

(music)

Today’s podcast is sponsored by Experian’s Clarity Services. They are the leading sub-prime consumer credit reporting agency providing innovative risk management solutions to address the full consumer credit life cycle. Clarity leverages the combined power of the largest and most comprehensive alternative credit data source with traditional bureau data to provide a more complete view of a consumer’s financial behavior. Clarity is committed to providing products that address rapidly changing market conditions. You can learn more by visiting clarityservices.com/solutions

Peter Renton: Today on the show, I’m delighted to welcome Jeffrey Meiler, he is the CEO and Founder of Marlette Funding, also known these days as Best Egg which is their consumer facing brand. So I wanted to get Jeffrey on the show because we’ve never had him on before and Marlette has become one of the true leaders in the online lending space.

As you’ll see in this episode, they’ve really done things that no other platform has done and they have built themselves a very strong brand in the industry. So we talk about their loan performance, we talk about profitability, we talk about Jeffrey’s perspective on the entire online lending space, we talk about the investor side of the business and what’s in store for 2019. It was a fascinating interview, hope you enjoy the show.

Welcome to the podcast, Jeffrey.

Jeffrey Meiler: Hey, thank you, Peter.

Peter: So I like to get these things started by giving the listeners a little bit of background and some context. You’ve had a pretty interesting career to date, Jeffrey, so why don’t you go through and give us some of the highlights.

Jeffrey: Sure, I’d be happy to. My background, and importantly the background of my colleagues at Marlette, is a bit unique in the online lending space. Myself, my leadership team and actually the overwhelming majority of the folks at Marlette have backgrounds in consumer finance and banking so in the context of the online lending industry, we’re a bit more fin than tech-weighted from an experience standpoint.

Now I specifically have 25 years of consumer finance and banking experience with seven years actually spent in the UK and Europe, but the majority of the time in the US with the focus really on unsecured consumer lending. In fact, as you may know, many of us at Marlette worked together in the US credit card industry. If you look at my leadership team, six of the nine people have known and worked with me for over 14 years. If you look at the broader strategy staff, about 60% of us have worked together previously.

Peter: Wow!

Jeffrey: Yeah, it’s pretty unique.

Peter: So was that primarily at Barclaycard or is that what the majority…

Jeffrey: Yes, it is. Let me give you more color to that. What is really unique is, yes, it’s at one issuer and what is special and has been unique for us is the nature of our shared experience. We collectively, had the experience of building a US card business from a billion dollars to $12 billion from a portfolio standpoint in five years, making it a top ten card issuer and the team, the team that is at Marlette, built the prospect database, the credit models, the value propositions that enabled the success of that credit card business. As you can imagine, that was great context for what we’ve done at Marlette.

Peter: Yeah, right, for sure, for sure. So then let’s go back just a few years to the founding of Marlette. What was it that you saw and why did you decide to start an online lender?

Jeffrey: Hey, that’s a great question. We incorporated in August of 2013 and then launched in the middle of March in 2014 and there were really two things that really informed our thinking about starting Marlette. The first was we clearly saw that consumers were not being served and appreciated the size of the total addressable market. That was the first thing.

The second thing was we saw an opportunity to take a different approach than the current incumbents, more fin than tech, more focus on credit and capital markets than on growth in isolation, better alignment and attention across the capital stack and more focus on building a resilient personal loan business that reflected our recession tested team’s experience in the credit card industry.

Peter: Okay, okay. So then before we move on, I’ve got a strange question for you. You know, I noticed that your email address changed recently from Marlette Funding to bestegg.com. What is your company name, what are you going by these days?

Jeffrey: Great question. The company is still named Marlette Funding, but our lending platform and what consumers recognize is Best Egg and we found, to your good point, that many of our corporate relationships were not connecting these two brands. So over the past two years, we’ve made a concerted effort to increase awareness and the connection between the two brands and that’s, hence, why we made the email addy change to try to connect the two brands so that there isn’t that confusion out there, but a fair question.

Peter: So the Marlette brand isn’t going away, you’re just sort of aligning more with the Best Egg brand?

Jeffrey: I would preclude us embracing more and more, as time went on, the Best Egg brand.

Peter: Okay, where did that name come from? What’s the origin of Best Egg?

Jeffrey: Sure, sure. So the origin was really part and parcel of the thinking about the customer that we wanted to serve and when we really analyzed who we were going to be working with, who we were going to be helping here, it was typically a consumer that is 46 years old, is an individual that has liabilities that exceed assets and they’re carrying, typically, $15,000 plus in credit card debt and they’re looking to make a change. The theme for a lot of these people as we talk to these consumers was the desire, the aspiration to have a nest egg. So it was a bit of a play on words, well, you know, you don’t have a nest egg, get a loan from Best Egg…

Peter: Right.

Jeffrey: …and start on your path.

Peter: Got it, that makes sense, that makes sense. So then you’ve talked a little but about this, but I want to delve into it a little bit more. Like the background at Barclaycard, you know, Barclaycard obviously…Barclays is a very well established, dare I say old, British bank that goes back centuries, how’d your time there influence what you’ve been doing over the last…particularly when it comes to how you sort of built a successful company. How have your learnings at Barclaycard helped you do that?

Jeffrey: I think that’s a great question and to your point, Barclays is a couple hundred year old institution and to have folks come from there and go and do a startup, it isn’t necessarily the logical expectation, but the thing that was unique was Barclays had purchased a startup in the US, something called Juniper, and that was the entity that I referenced earlier that the team grew rapidly. So really Marlette is leveraging that specific experience.

It also, though from a 200-year old bank perspective, I think there are some things we borrowed from there also. I think the compliance discipline, the credit practices were things that we took from Barclays and embedded in Marlette very early on and both of those specific things had a level of maturity that exceeded the maturity of the company itself.

Peter: Right, got it, okay. So then now when you look at the competitive landscape today and you see there’s more personal loan offerings for consumers than there probably has ever been, certainly in the last couple of decades, I’m just curious about when you’re looking at the landscape and you’ve obviously got all of the other online lenders today, you’ve got banks coming in as well, how are you differentiating Best Egg from the other offerings that are out there?

Jeffrey: Hey, that’s a super relevant question. As you know, Peter, the most successful players in the online lending space are those that deliver a fast frictionless customer experience and we spend an inordinate amount of time, energy in focusing on that.

In the context of 2018 specifically, we introduced new funnels from a customer standpoint, one that is focused on a better experience for those people using a desktop and one is focused specifically on those customers that are using a mobile device. Those efforts in 2018 resulted in us having a net promoter score of 68, an A+ rating with the Better Business Bureau and a 9.5 out of 10 TrustScore from TrustPilot. I think that that’s going to be the key, that focus on the customer is going to be the key to differentiate and win in this space and I think that segmentation and personalization is something that, specifically in 2019, we’re going to make a lot of strides in.

Peter: Okay, we’ll delve into that a little bit more in just a bit, but I want to talk a little bit about your 2018 and the scale you guys are at. I know you just recently crossed another milestone so tell us, how big is your loan book today?

Jeffrey: So to your point about milestones, as we came to the close of 2018, we crossed the $7 billion mark, so in less than five years we have originated $7 billion. As far as the outstanding book, the outstanding portfolio is about half of the total originations so circa $3.5 billion.

Peter: Okay, so then when you look back at 2018 then, we are recording this in the middle of January, so you might not have closed out your books yet, but I’m sure you’ve got a very good idea of how it went. Tell us a little bit about…I’m interested in profitability, in growth and that kind of thing.

Jeffrey: Happy to share and to your point it’s unaudited financial results at this point, but happy to share those. So 2018, is the second consecutive year that the company has achieved GAAP profit in the double digit millions and year-on-year we had about a 60% increase in profits. Q4 specifically, Q4 of 2018 marked the seventh straight quarter that net income has been positive on a GAAP basis. Now turning to loan originations, 2018 was robust for us also, originations increased 27% year-on-year.

Peter: Okay, okay, that’s a pretty impressive performance. I want to get back to the profitability, it’s great you’ve got seven consecutive quarters of profitability. You know, when we look at many other companies in this space and it’s definitely been a knock on the space for the last few years where there has been a lot of venture capital money being thrown at the online lending space and profitability has proven elusive for many players.

Obviously we don’t have publicly available books for everybody, but there are for a few players so I’m curious, what’s your take on that? Obviously, you monitor your competition closely, I’m sure, why is it so hard for many companies to make money?

Jeffrey: Hey, that’s another good question. I think new business paradigms that are challenging well entrenched incumbents, in this case the banks, always struggle to be profitable. Now, specifically, if we look at the online lending industry, I think that near term profitability is also linked to where you are positioned on the fintech continuum.

Before 2016, I think it was generally more acceptable for the incumbents to pursue growth versus profitability in isolation. This is more commonly accepted in the tech space. For example, how many years did Amazon lose money.

Peter: Right.

Jeffrey: IPO was in 1997 and in 2009, they were still in the red. What happens in our industry is in 2016, it became abundantly clear that tech was important in delivering a frictionless customer experience, but credit performance, access to capital and profitability were more important and the pendulum had swung to fin versus tech.

Peter: Right, right.

Jeffrey: And I think those players that were more skewed to fin, like Marlette, had an easier time migrating to profitability and acclimating to the new consensus sentiment about the nature of the online lending industry.

Peter: So is that something that you consciously made the decision of? Obviously, we know 2016 was a difficult year for many companies in this space. I wouldn’t say funding dried up completely, but it certainly was a lot more difficult. So was that a conscious decision back then to say, right, we need to batten down the hatches and focus on profitability?

Jeffrey: Yes I would say, in general, we were always skewed, from an orientation standpoint, to be more fin than tech, but post 2016, it became clear that we couldn’t wait to get to profitability and at the end of the first quarter of 2017, the last quarter that we lost money, we narrowed the commercial agenda and became a lot more focused on profitability.

Peter: Got it, okay. So let’s talk a little bit about credit performance. You’ve already mentioned that several times and I want to know what color you can give us on the credit performance of your loan book.

Jeffrey:  So I, as you would expect, would say we have really a unique performance from a credit perspective. We have been really, really consistent in what we’ve delivered for investors and for the company. I really think it comes down to this orientation that is more fin-grounded than tech-grounded and let me explain what I mean by that.

For us, on a quarterly basis, job one was always to originate loans that would serve us well and our investors through a recession and we specifically, on a quarterly basis, target a specific loss coverage ratio and because we target that, we have more predictable and consistent results. In contrast, in contrast, others in the space, especially pre-2017, thought of themselves as a marketplace.

Job number one was balancing supply and demand for their loans. When demand for loans was high, interest rates to consumers went down and underwriting softened. That approach leads to more volatility and less consistency and I think that, in a large part, that’s been the biggest difference. It starts philosophically for how we see the nature of the business that we’re in.

Peter: Yeah, that makes sense, that makes sense. So I’m curious about how you view…when you look at your business overall, you have really maintained a focus on one product to date, the personal loan, and you’ve seen others who have branched out into different verticals or just sort of adjacent products, shall we say, and I’m curious about how you view that. Are you comfortable being a monoline business for the foreseeable future, or how do you think about adding a new product vertical to your business?

Jeffrey: Yeah, another great question. Yeah, to date we have been totally focused on building a profitable resilient personal loan business. Having accomplished that though, in 2019 we will start to take steps to broaden our product pallet and leverage the platform and the infrastructure that we have built. As you would expect, the first steps are likely, you know, close cousins to the personal loan business, but see over the medium term that we’ll go further afield from that, but absolutely, Peter, I think that the time has come for Marlette to diversify.

Peter: Well you know you guys seem to have a lot of experience in the credit card business. I wouldn’t guess, of course, what your next product would be, but certainly I know that you guys must have…that would be a logical step.

Jeffrey: I can’t comment, but to your point we love credit cards.

Peter: I know, I know. Right, okay. Anyway, so it’s interesting that you guys are based in Wilmington, Delaware. I don’t know if there’s any other fintech companies in Wilmington, Delaware, there certainly aren’t many. I don’t know of any other in the online lending business. Now Delaware is obviously a very…a lot of places have their official headquarters there for various reasons that the government has set up…the state government of Delaware has really promoted that, but I’m curious about…do you think that Wilmington, Delaware, being located there is an advantage or a disadvantage to you when it comes to attracting talent to Marlette?

Jeffrey: We think it’s a huge advantage to be in Wilmington and to your point, I don’t know if people broadly appreciate that this greater Wilmington area has the greatest number of people probably in the United States with unsecured credit experience and being in the middle of that has been super helpful for us in scaling the business. I referenced earlier that, you know, 60% of the strategy staff worked with us previously. Even outside of that, the people we’ve hired have experience in unsecured credit.

Now having said that, we are a fintech player and believe in hiring the right and best people and have tools that enable us to have people work remotely also, if that’s something that is important to them, but being in Wilmington has really enabled us to flourish.

Peter: Interesting, interesting. I imagine that all of the unsecured credit people is because the credit card companies set up shop there, is that one of the primary reasons?

Jeffrey: Yes, in Wilmington there’s essentially two industries, pharma and credit cards, financial services and to your point, a number of players are headquartered in the area.

Peter: Right, right, for sure. Okay, so I want to switch to the other side of your business, the investor side, and I’m curious about the investor mix today and what kinds of investors are buying loans and is that changing at all?

Jeffrey: Yes, that has changed greatly over the five year period that we’ve been in business. In the very early days, we were funded 100% from hedge fund money, that’s not the case today. I wouldn’t quote specific mix percentages, but would say that as we’ve built a track record and shown consistency, we’ve been successful in migrating, over time, to buyers, loan buyers, whole loan buyers, with lower and lower costs of capital and that has been really helpful and fruitful and has been, you know, a part of our migration to profitability.

Peter: Right, that makes sense. So then on that, we did have a couple of years ago, we had your Head of Capital Markets, Karan and Josh Tonderys on the show and we talked quite a lot about securitization and I won’t go into too much depth, but maybe…I will link to that show in the show notes, but you have become quite a prolific securitization issuer, your deals seem to attract a lot of attention so maybe you could just give us an update on that and do you plan to sort of keep this similar rhythm in 2019 that you’ve established?

Jeffrey: Yeah Karan, who you referenced, has done a great job in developing our securitization program and our deals have been well received. In 2018 specifically, we did $1.7 billion in transactions bringing the total Marlette issuance to date to $2.9 billion. Furthermore, in 2018, a number of the tranches from 2016, 2017 and 2018 received rating upgrades from Kroll. As we look to 2019, market conditions permitting, we’ll continue to be a serial issuer of securitizations.

Peter: Right, right, okay. We’re running out of time, but last question on 2019, the future, you’ve already touched on some of these things, but I’m curious about what you’re excited about when you look ahead to this year. What are some of the things that you want to accomplish?

Jeffrey: To your point, Peter, we’ve touched on some of this, but as we enter 2019, it’s really going to be about capitalizing on the robust and balanced performance that sets the stage for continued growth and product expansion. As you would expect, we closely monitor all conditions that may impact the business and are prepared to recalibrate, if necessary, but right now, right now, we remain optimistic that we can continue to expand our business at pace, both within personal loans and outside of personal loans.

Peter: Okay, well on that note, we will leave it there. I really appreciate you coming on the show today, Jeffrey, and best of luck to you in 2019.

Jaffrey: Hey, thank you, Peter.

Peter: Okay, see you.

You know, the online lending industry is certainly maturing and I think Jeffrey sort of brings on some of those points there where, you know, they’re a profitable business, seven quarters in a row, I think that’s extremely important. Gone are the days if you look back to 2015 when money was just being thrown around, anyone could raise capital and there was certainly no focus on profitability or very little focus on profitability back then.

Today, this feels like a different time, 2019, you know, if you’re not profitable, or at least have a really easy or strong pathway to profitability, you are in serious trouble. I think companies like Marlette are showing the way where you can make money in this industry, even as a monoline company. They have proven that it’s certainly doable and I think the rest of the industry needs to take note of that. I’d like to think that by the end of 2019, the vast majority of companies in the industry will be profitable.

Anyway on that note, I will sign off. I very much appreciate you listening and I’ll catch you next time. Bye.

Today’s episode was sponsored by Experian’s Clarity Services. Clarity’s suite of FCRA-regulated reports and predictive scores yield significant insight into a consumer’s financial behavior throughout the alternative financial services industry. Clarity delivers data-driven risk management solutions that address prospecting, credit evaluation, fraud detection, portfolio management and collections. You can learn more by visiting clarityservices.com/solutions.