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LAP19: Anil Gupta of PeerCube on P2P Lending Analysis

by Peter Renton on July 9, 2014

Today, p2p investors have many options when it comes to analyzing loan performance. One of these options is PeerCube which was founded by Anil Gupta, a software engineer with a background in data analytics. In this latest edition of the Lend Academy Podcast I talk with Anil about PeerCube and the importance of data analysis for p2p investors.

In this podcast you will learn:

  • Why Anil decided to get into p2p lending in the first place.
  • How he started investing and how PeerCube came into being.
  • What PeerCube has to offer p2p investors.
  • Why it is important for him to share the filters others use to invest.
  • How his Bad Loan Experience (BLE) index works.
  • How PeerCube tracks the new loans added to Lending Club and Prosper.
  • An explanation of his recent analysis of loan returns based on the time loans took to get funded.
  • The very interesting and unexpected findings of this analysis.
  • The reason he maintains a healthy skepticism of the p2p lending industry.
  • Why he considers Lending Club and Prosper loan brokers and why they remind him of real estate agents.
  • Why Anil feels that people are ignoring the risks involved in p2p lending.
  • What the future holds for PeerCube.

In this interview we talked at length about Anil’s fascinating analysis of Lending Club loans time to fund – below are links to all four articles in the series:

Mad Rush at Lending Club Loan Release Time: Part I
Mad Rush at Loan Release Time: Part II – Loan Performance with Time to Fund
Mad Rush at Lending Club Loan Release Time: Part III – Delinquency Rate and FICO Score Change
Mad Rush at Lending Club Loan Release Time: Part IV – Interest Rate with Time to Fund

You can subscribe to the Lend Academy Podcast via iTunes or Stitcher. To listen to this podcast episode there is an audio player directly below or you can download the MP3 file here.

{ 6 comments… read them below or add one }

Raymond July 9, 2014 at 8:25 pm

In the Part III of the four articles in the series, with regarding to the delinquency rate, I think it would be better to calculate the delinquency rate of each time-to-fund group by using the number of records in that group only, not divided by Total Number of Records. For example, N1 notes were issued in 0 – 1 minnute, d1 notes was delinquent, then the delinquency rate of 0-1min group would better be (d1 / N1).

Reply

Anil Gupta July 9, 2014 at 9:05 pm

Raymond, Is there a confusion in article how delinquency rate is calculated? Because delinquency rate with time to fund was calculated as you suggested.

Reply

Raymond July 9, 2014 at 10:03 pm

I had this question when I was reading your articles. I thought you might use the total number of records in the portfolio due to some sentences like listed below. I tried to look for a clearer statement but failed. That’s why I had the question. Thank you for clarifying it, and thank you for the articles.

1. On the graphs, titles like “% of Total Number of records”
2. “The delinquency rate is generally defined as the loans that have delinquent payment as percentage of *total loans in a loan portfolio*”

Reply

Ed Seid July 9, 2014 at 9:57 pm

Just signed up for PeerCube to check it out.
I found Mr. Gupta’s blog at http://andirog.blogspot.com/
Very interesting read! I appreciate that he lists the Key Takeaways at the posts’ end. :)

Reply

Anil @ PeerCube July 10, 2014 at 5:33 pm

Thanks for the mention of my ‘other’ blog. If you like this blog, you may also enjoy PeerCube blog https://www.peercube.com/blog. I try to keep my blog posts as simple as possible with key takeaways at the bottom for those who may not be inclined to go through the data and charts.

Reply

Peter Renton July 11, 2014 at 7:08 am

Thanks Ed for providing a link to Anil’s older blog. I didn’t link to it here because there is so much great stuff on the current Peercube blog now that I think people should read what’s been on there before exploring the older posts.

Reply

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