Prosper.com - Don't blame the economy

From time to time, someone will try to explain away the poor performance of prosper.com loans by blaming it on the poor economy. Its become a national pastime to use the economy as an excuse these days. But is it true?

To sort this out, I have graphed the default rate of all prosper.com loans side by side with the U.S. unemployment rate. If bad economic conditions cause prosper borrowers to change their behavior, then you should see the prosper.com default rate go up when unemployment goes up, and vice versa.

These two curves don't look correlated at all!

In the last year, unemployment has roughly doubled, which represents a huge change in economic conditions. During that time the default rate on the prosper portfolio has bounced around, but it certainly hasn't gone up in tandem with the unemployment rate.

In a recent blog, Prosper's CFO Kirk Inglis was describing Prosper's new system for rating borrowers, and he said "...the historical performance that underlies the Prosper Rating System is derived from a poor economic environment. As a result the estimates of loss are biased higher than if the economic environment had been more benign."

In other words, he argues that because he did his calculations using loan data from the recent past, when economic conditions were bad, then surely future loans should do better than his model predicts. His unstated underlying assumption is a correlation between prosper loan performance and the economy. I see no evidence for his conjecture. Wishful thinking.

It may seem counter-intuitive, but we can't deny the data. Loan payment performance doesn't seem to track economic conditions.

Boring methodology footnotes: To compute the instantaneous default rate of the entire prosper portfolio, I looked at prosper's performance web page. I asked it to show me all loans (for all time) as observed on the first day of each month. I copied down the number of loans that had defaulted as of that date. Subtracting these numbers for two adjacent months tells me the number of loans that defaulted during that month. To convert this to a default rate, I divide by the total number of loans prosper had originated as of four months earlier.

I chose the four-months-ago total because loans take four months to default. Using a later total would have included loans in the denominator which could not possibly appear in the numerator. Finally, I converted this monthly default rate to an annualized default rate exponentially, ie da = 1-(1-dm)^12 .

This process produces an instantaneous "whole prosper portfolio" default rate. Beware that this number doesn't help us judge the performance of loans prosper originated at any point in time, or at any credit grade, becaue here they are all mixed together. It does allow us to observe trends (if any) in borrower payment behavior over time, so it seems appropriate for this inquiry into how borrowers behave during economic hard times.

You probably note a downward tilt in the default rate curve during the months that Prosper was shut down by the SEC. This is a side effect of the loan portfolio "aging" during that period. No new loans were being added, and the existing loans were all getting older. Therefore the age distribution of loans in the prosper portfolio was changing. This aging produces a lower default rate, because the default rate naturally falls somewhat as loans age. This happens because the portfolio is a heterogeneous mix of loan quality. The bad loans (think HR, E, D, ...) tend to fail early, leaving a more aged portfolio with a higher quality mix.

The unemployment rate shown is the whole-country U-1 series produced by the bureau of labor statistics, and which I obtained from www.economagic.com . This is the unemployment rate that you most often find quoted in the press.

PS: The best discussion among P2P lenders can be found at prospers.org .