Jason Yeung

Jason Yeung

Senior Director, Analytics Center of Excellence at SAP | Passionate about enabling and helping customers on their analytics journey.

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About Lending Club

For those unfamiliar with Lending Club, it’s the world’s largest peer-to-peer lending platform. It enables it’s members to borrower unsecured personal loans (up to $40k) from investors. Investors can contribute as little as $25 to help partially fund these loans.

Its technology operates as a credit marketplace, but with much lower costs and interest rates than traditional banks. For investors, the interest rates are much higher than a traditional bank and they have solid predictable returns – but they carry the risk of unsecured loans.

To help investors, Lending Club shares all of its historical data around their loans, borrowers, payments, interest rates, defaults, and so on. This is great for data savvy investors to generate their own insights – to see if the return was worth the risk.

Crunching the numbers

Since their inception in 2007, Lending Club has nearly 2 million loans to date. The total value of these loans is nearly 7 billion dollars.

Looking at the long-term trends, Lending Club has achieved significant growth (in terms of number of loans) from 2017 – 2015. However, over the past few years, their growth seems to have plateaued.

Types of loans

The most common loans are between $5-15k; however, there’s also a large percentage of loans that exceed $25,000. 71% of all loans are issued for terms of 36 months, or 3 years.


Who’s applying

The data shows the typical borrowers are teachers and managers.

Using the geo map, we can also see the majority of loans come from California, New York, and Texas.

Borrowers have an average income of $84k with most loans being used to pay off debt. The average loan amount is around $16,000.

Loan payback

For a typical loan, a borrower can expect an average of $473 monthly payment over the next 3-5 years to payoff their credit card and other debts.

From the chart below, we see that the monthly payments and the interest rate varies on the loan amount.

Interest rates

The longer the term and the worse the borrower’s credit, the higher the interest rate. In addition, the reason for the loan impacts interest rates as well. Education and weddings yield the highest interest rates.

Risk and reward for investors

With higher interest rates than a traditional bank, it’s easy to see how Lending Club is a great investment. But there’s risk.

Since these loans are all unsecured, the investor assumes the liability if a borrower defaults on their loan.

First, in the visual below, we see the majority of loans are for borrowers with an average credit score (B or C) and they use this for debt consolidation.

We an also see that the interest rate is slightly lower if you use the loan for educational purposes. Perhaps the idea is that a borrower who invests in their education, will likely pay off loan sooner.

Finally, if we look at this by defaults (e.g. people not paying back their loans), we can see that the worse the credit, the higher the default rates.

However, there are some outliers.

Those with bad credit and use these loans for “vacation” or “renewable energy” have a 50% chance of defaulting on their loans. We also see that people with average credit have a higher chance of defaulting on a loan when used for “education” than those who use loans for other reasons.

Final thoughts

  • Peer-to-peer lending works — the growth of peer-to-peer lending coupled with the competition in this space shows how peer-to-peer lending is becoming a popular alternative to bank-funded loans.
  • Data reveals our challenges managing our financials — This data illustrates just how hard it is for the middle class to make ends meet. Rising costs coupled with flat salaries has led to large debt that these families need to pay off – and a good number of them default on their payments.
  • People need analytics, not data — while Lending Club and other banks do an excellent job providing timely and updated “raw data,“ they provide little analytics and insight into this data, like we’re seeing above. This type of analytics let’s us see the whole story in the data and to allow us to do our own discovery.

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