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New Report Showcases How AI Will Transform Financial Services

The World Economic Forum and the Cambridge Centre for Alternative Finance just released "Transforming Paradigms: A Global AI in Financial Services Survey"

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The World Economic Forum and the Cambridge Centre for Alternative Finance (CCAF) recently published a report targeting one specific area of innovation in financial services: artificial intelligence. The report polled 150 senior financial services executives across both fintech and traditional financial institutions.

The study found that 60% of firms invest less than 10% of their R&D resources on AI even though it is an area where returns can be quite high. It also found that 64% of financial services executives expect to become mass adopters in just two years. The report details the areas in which companies are deploying AI. Most often we think of AI as a means to reduce costs, but it also is being deployed to increase revenue. Areas of most prominence include process automation, risk management, customer service and client acquisition. Perhaps not surprisingly fintech firms are creating new products using AI in a variety of ways while traditional financial services firms are using AI to improve existing products.

Beyond the benefits of AI, the researches also delved into risks of AI, such as the perceived risks of privacy breaches, cyber-attacks, biases/discrimination, systemic risks, and concentration risk. For this reason many firms are preparing for some of these challenges utilizing risk and compliance teams in AI implementation.

Beyan Zhang Executive Director of the Cambridge Centre for Alternative Finance noted in the release:

“This empirical research underscores the growing importance of harnessing AI in financial services which gives new impetus for firms to develop a holistic and future-proof AI strategy.”

Read the full survey results and report here.

Upstart Riding Automation and Bank Partnerships to Profitability

The online consumer lender has turned the corner in profitability during a year of strong growth

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Dave Girouard, CEO of Upstart, speaking at LendIt in 2017

Upstart has been quietly doing something that many others have found difficult: building a profitable online consumer lending business. I caught up with Upstart CEO, Dave Girouard, recently to talk about the state of his business and where he sees the biggest opportunities today.

To date Upstart has issued $2.8 billion in consumer loans which equates to 230,000 loans and they are doing about $180 million a month right now. They will end the year with double the loan volume they did last year. But Dave was quick to point out that they are not all that focused on loan volume. The metric they are most focused on is profitability. They have just completed five profitable months in a row and are now generating $1-2 million a month in profits. They expect to be profitable on a quarterly basis going forward.

How have they been able to move to profitability? One contributing factor is automation. Given Dave’s background (and many others on the team) at Google they have been very focused on technology at Upstart from day one. They have created an underwriting engine that is built for automation. Today, two-thirds of their loans are entirely automated and the median time to close a loan deal is 28 minutes. Most of that time is waiting for the user to respond, Dave said it would take less than five minutes if the customer was completely responsive. Manually underwritten loans have a median close time of 50 hours, still a pretty good user experience. They have also kept customer acquisition costs in check as their cost per loan has remained stable even as loan volume has accelerated.

Upstart made a name for themselves as being the first lending platform to leverage artificial intelligence and machine learning in their underwriting. They have also always used alternative data to build their models and have used this data in new ways. To provide investors comfort that all this was blessed by the regulators they sought and received a no-action letter from the CFPB in 2017. They continue to report to the CFPB on a quarterly basis. [Read more…]

Use Cases and Trends in Artificial Intelligence for Financial Services

A review of where financial services companies are beginning to implement artificial intelligence.

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Artificial intelligence (AI) is everywhere these days as more companies look to automate repetitive tasks to save money and reallocate staff to more meaningful work. We wanted to explore some of the current use cases for AI based technologies in financial services and where the industry is heading in the coming years.

Cut through the hype and you will find financial firms have started to implement AI in a few different areas. Back office operations and data management has been the biggest beneficiary as companies can run algorithms across full data sets and cut out repetitive tasks.

[Read more…]

Marketplace Lending Predictions for 2018

A review of our 2017 predictions and some new thoughts for 2018

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Happy New Year everyone. As I do every year at this time I make a few predictions for the year ahead as well as review my previous years predictions.

Review of my 2017 Predictions

First, let’s review my predictions I made exactly one year ago. We had an interesting year as an industry in 2017, it was certainly a better year than 2016. I think I did ok on my predictions from last year although as you can read below I did get some things completely wrong.

  1. 2017 will be the year of the bank partnership
    I would say I was partially right on this one. We certainly saw a large number of new bank/fintech partnerships with deals closed from Avant, Fundation, Upstart, P2Bi, LendUp, Biz2Credit and many others. And in Europe the floodgates opened with dozens of new deals between lending platforms and banks announced. But in the US I was expecting even more partnership deals than we had so I think it is bit of a stretch to call 2017 the year of the bank partnership here.
  2. The OCC Fintech Charter will receive a positive reception
    It was an interesting year for the OCC Fintech Charter. With Thomas Curry leaving as head of the agency in April, then Keith Noreika holding the acting role for a few months and finally Joseph Otting being sworn in to lead the agency in late November it was difficult for any new initiative to get momentum. There was also the case of the Conference of State Board Supervisors suing the OCC over the charter, which was dismissed in December. So, while many of the fintech platforms supported the charter there was no real positive movement this year.
  3. Lending platforms will offer banking products
    While we had a couple of platforms offering credit cards for the most part this prediction failed to materialize. With the possible exception of SoFi I think we are still some time away from lending platforms offering a variety of banking products.
  4. One large platform will be acquired
    I am going to say I got this one right as one major platform was acquired in 2017. Student lender Earnest was acquired by Navient in a deal announced in early October. My guess that Prosper might be the platform to be acquired was wrong but there were rumors flying around about acquisition talks at more than one major platform last year.
  5. There will be no new IPOs this year
    I was almost right on this one but one US lending platform did have an IPO in 2017. Short term lender Elevate went public in April after postponing their IPO in 2016. None of the major marketplace lenders braved the public markets in 2017 as valuations continue to be depressed at many of the leading companies.
  6. China will become an important source of capital outside the USA
    I got this one right. China continues to make its presence felt as more US companies are looking for capital from that part of the world. The leading Chinese fund, the CreditEase Fintech Fund, made investments in 2017 in Upgrade, dv01, Orchard, Lenda and Nav just to name a few. China is now becoming a consideration for many more companies looking to raise money.
  7. Artificial intelligence will take center stage
    I think I read more articles about AI this year than in the previous five years combined. Whether it is for underwriting, customer acquisition, collections, compliance or cybersecurity AI is now central to the success of many lending platforms. It has taken center stage and will remain important for the foreseeable future.

[Read more…]

Data Science is Becoming the Most Important Skill in Fintech

The explosion in data has made the data scientist an essential part of all fintech companies

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Data is everywhere. The world generates some 2.5 quintillion bytes of data every day. Some people have said we are drowning in data and that may well be true. But we are starting to get better at making sense of massive amounts of data. Which brings me to the point of this article. Data science is going to become, if it hasn’t already, the most important skill in fintech.

Before we go any further we should define what we mean by data science. There is no standard definition but I like how NYU describes it:

At its core, data science involves using automated methods to analyze massive amounts of data and to extract knowledge from them.

Extracting knowledge is the key point here. We may be drowning in data but a skilled data scientist will be able to extract the useful parts of this data and discard all the noise. With so much data available today in all industries, particularly in finance, those companies that can extract useful and actionable knowledge will be the winners.

Chris Skinner penned this interesting piece last week claiming the critical importance of data in banking:

Data is the new air, and the banks that breathe the best will win. In other words, banks that really get data analytics, and can apply machine learning to gain deep customer insights are the ones that will survive.

[Read more…]

How AI & Machine Learning Can Fix the Broken Credit Scoring System

Marc Stein from Underwrite.ai shares his thoughts on fixing the credit scoring system.

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Editor’s Note: This is a guest post from Marc Stein, CEO at Underwrite.ai and Principal at Artificial Intelligence Capital Management. A longtime entrepreneur and startup CTO, he cofounded the first auction platform for student loans, College Loan Market, a marketplace for equipment leasing, LeaseQ, and ScholarshipWS, the search engine that drives many of the largest college scholarship search sites. He also served as CTO at Y2M Networks, sold to Viacom and the Student Loan Consolidation Program sold to JP Morgan Chase, and as Global CTO for the Giving Group, a UK entity that operates the world’s largest peer to peer charitable fundraising service. In his spare time, he works on applications of artificial intelligence towards problems in cancer diagnosis and genetic biomarker identification.]

I was recently on a panel at Money 20/20 in Copenhagen with the intriguing title “Credit scoring is broken: Striving for fairness and accuracy in a data-rich world”.

The question stuck with me beyond the panel itself. Is credit scoring broken? If so, when did it break? Who broke it? And, most importantly, why is it broken?

In a sense, the credit scoring system exists to minimize risk to lenders by focusing on the lending of money to people who have proven themselves to be low risks. The dominant scoring methodology in developed economies is solely focused on how people repay prior loans, how many loans they’ve already taken, and how many times they’ve applied for credit.

This works to simply exclude those without existing credit.

I recently worked on a study for a large lender that was testing into their decline population. This gave me some insight into the performance of thin and no-file applicants without FICO scores. What was most interesting about the results was that the overall portfolio had a charge-off rate of 10%, with the lowest performing cohort charging off at 22%. The FICO unscored group, who would almost always be denied credit, charged off at 14%.

So, in fact, the applicants with no score were quite profitable if lent to at the higher priced tiers and outperformed the low end of the approved spectrum.

But does this mean that the credit scoring system is broken? In itself, no. Lenders can loan to applicants with FICO scores at or above 700 with a fairly solid understanding of repayment risk. This leads to the extension of government subsidized credit to the lowest risk portion of the credit spectrum.

But this divides the society into three classes of people. Those with access to cheap credit from subsidized sources, those with access to expensive credit from leveraged sources, and those with no access to credit.

The disparity in credit access is baked into the credit scoring method. But why did this happen?

I propose a simple explanation. In order to create models that can be efficiently implemented, the problem of credit risk has been oversimplified. The current methodology in widespread use seeks to model risk using linear models with a small number of inputs. [Read more…]

Smartphone Data is the Key to Expanding Access to Credit

Every smartphone owner produces a huge amount of data and companies are now using some of this data to underwrite loans.

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The average American checks their phone 47 times a day according to this study by Deloitte. The number is much higher (82) if you are in the 18-24 year old age bracket. We keep our lives on our phones and so it has become the most essential piece of technology we own.

With all that usage comes a treasure trove of data. Now, this also brings with it a host of privacy issues but that is not the focus for this article. What I am talking about here is smartphone data and how companies can leverage this to expand access to credit. This particularly applies to the underbanked consumers in this country and more importantly in developing countries.

For many consumers their access to credit is limited because they have little or no credit footprint. They may operate primarily with cash, have no credit score and are therefore unable to qualify for a loan from most lenders. Their credit needs are often more urgent than the mid-prime and prime consumer but because lenders have little or no data they have difficulty in obtaining credit.

This problem is particularly acute in the developing world. Here, most people are outside the traditional financial system, if there even is one, and do not have access to credit. But that is changing as companies like Kiva, Lenddo (listen to Episode 91 of the Lend Academy Podcast), Branch and Juvo (see this session at LendIt USA 2017) are helping consumers get access to credit, often for the first time.

What lenders are finding out is that even when there is no credit data available the data that is inside a consumer’s smartphone can be very predictive of creditworthiness. I think Lenddo (they are a technology provider, not a lender) is doing some of the best work in the space as they have a great deal of experience in many different countries using data contained in smartphones to score consumers. In this country LendUp and Elevate are also doing good work and I like Oakam in the UK.

Underwriting is All About Data

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Banks Going Digital – Transforming Branches, Apps and a Focus on Customer Experience

Banks know they must go digital and many are embracing new technology to improve the customer experience

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In Austin last week American Banker hosted their annual Digital Banking Conference where banks of all sizes gathered to discuss the innovation in banking today. There were a few main themes that came out of the event; banks are focused on transforming the customer experience, mobile first approaches are prevalent and technology solutions like AI and cyber security are becoming must haves within the bank.

The big banks have all started to understand that the traditional way of banking is a thing of the past. Keynote speaker Yolande Piazza, CEO, Citi Fintech talked about disrupting from within, changing how they operate to enable the customer and move to a mobile first approach. She explained how this approach is radical for a bank and the layers of compliance did not make the transition smooth. They have completely rethought how they hire, 50 percent of their fintech talent is from outside the company. They have looked towards fintech and technology companies to fill their pool, while the banking talent comes from within.

Consumer oriented experiences really drove a lot of the conversations at the event, banks and the vendors were all talking about how to best utilize the consumer’s time when they engage. Mobile apps seem to have become a bit of a competition among the banks, though some would describe it more as a competition of experience and not necessarily as a competition between different banks. No longer are banks looking to drive where the customers should go, they are looking for the customers to drive what they want in the experience.

Consumer experience is not limited to the digital channel; banks and companies like Samsung are also focused on changing the way people interact within the branch. In speaking to Reginald Jones, Director of Sales for Regulated Industries, he talked about how the consumer electronics giant is working with banks to help change the way people think and interact with their local branches. [Read more…]

This Summer LendIt is Offering Two Ways to Learn About China

LendIt is headed to China again this summer with our annual Lang Di Fintech Conference and LendIt China Executive Tour

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The LendIt team is excited to return to China for our second annual Lang Di Fintech conference on July 15 -16 in Shanghai and our fourth annual China Executive Tour from July 8-17. The tour will start with some fun in Macau, move to Hong Kong for our Investor Summit with AMTD, then onto Beijing for three days of meetings, and finally end in Shanghai for the conference itself.

The Second Annual Lang Di Fintech Conference in Shanghai

In China, the LendIt Conference is called Lang Di Fintech and it is the largest fintech event in the country. Similar to other LendIt events in the USA and Europe, Lang Di Fintech will be a key forum for the leading global fintech companies to meet, learn, share experiences, and build partnerships. We expect over 2,000 attendees comprised of entrepreneurs, investors, regulators, service providers, researchers and media from the US, Europe and China.

Lang Di Fintech will cover a broad spectrum of fintech topics with a special emphasis on technology and financial inclusion. We will have six broad categories, which include fintech technology, blockchain, lending, banking & technology, financial inclusion, and Asia Pacific Fintech outside of China. We will have specific panels on technology like artificial intelligence, biometrics and cybersecurity.

Lang Di Fintech will feature more than 50 Western speakers including government leaders and executives from leading financial services firms. As always, simultaneous translation is provided for all guests at our event.

The Fourth Annual LendIt China Executive Tour

[Read more…]

IBM Watson Just Bought A Company That Will Transform Bank Back Offices Through Artificial Intelligence

Watson is going to help automate regulatory compliance for financial services firms but that is just the beginning.

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IBM_Watson_AI_Promontory Financial_Group

The running joke is that after Dodd-Frank banks have become compliance companies that happen to make loans. It is funny because it is true. Dodd-Frank has over 22,000 pages of compliance regulation. Who can possibly understand and navigate all of that regulation?

There is one company that is widely regarded as the ultimate Dodd-Frank expert. This company is based in Washington D.C. and is hired by every major bank to help navigate these complex regulations. This company is called Promontory Financial Group and it is comprised of the all of the heavy hitters in bank regulation. Check out their firm leadership page, it includes senior leaders from the Fed, Treasury, White House, World Bank, Fannie Mae, FDIC and the OCC. They even have the former Vice Chairman of Citigroup and a Senator that was on the Senate Banking Committee for over 18 years. This firm has the who’s who of bank regulation.

Ever since Dodd-Frank was passed, banks have spent big time on compliance. It is a bull market for Promontory, which has helped everyone figure out those 22,000 pages of compliance. In order to put it into perspective, check out this WSJ chart from May 2016:

“The six largest U.S. banks by assets in 2013 together spent at least $70.2 billion that year on regulatory compliance, up from $34.7 billion in 2007, according to the most recent study by policy-analysis firm Federal Financial Analytics Inc., which said costs have continued to mount since then.”

The smart people at IBM took note of this massive shift in spend and the enormous regulatory problem for banks, they have the perfect solution – Watson. What if you take that 22,000 page book and you let Watson read it and then give advice? Let the computer figure it out. That is exactly what IBM has in mind now that is has purchased Promontory.

“Promontory, combined with IBM’s deep industry expertise and Watson’s cognitive capabilities, will directly address the massive operational effort and manual cost of constantly changing regulation and risk management requirements. With the completion of the acquisition, Promontory will help accelerate IBM’s development of cognitive solutions for risk and compliance.” [Read more…]

ABOUT LENDIT FINTECH NEWS

LendIt Fintech News, Powered by Lend Academy, has been bringing you all the news and information about fintech and online lending since 2010 when it was founded by Peter Renton. We not only have the industry’s most active news site, but also the largest investor forum and the first and most popular podcast.

We are a team of fintech enthusiasts who have been covering the industry for many years. With a deep knowledge of online lending, digital banking, blockchain, artificial intelligence and more our team covers the daily news and writes in-depth editorials.

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