Peter had a post today on Social Lending Network titled An Apples to Apples Default Rate Comparison about P2PXML, which is an attempt to standardize p2p loan data.  According to p2pxml.com, a standardization rating system can be derived using rate groups, described as follows:

Rate groups are a way to group loans by interest rates. The formula used is: RG = 1 + (floor(interest rate) / 2). When comparing platforms the grades do not translate. Since the interest rate is theoretically supposed to represent the risk of a note, it makes sense to compare platforms base on the concept of a rate group.

This is supposed to allow investor to compare apples to apples when looking at types of loans across platforms since the credit grading system differs on each one.  I’m not sure I buy the assumption that rate groups are the best way to standardize this comparison.

A few months ago I applied for a p2p loan with both LC and Prosper. LC offered me a 8.99% rate, while Prosper offered me a 6.49% rate. Using this model, my exact same loan would be compared in different P2PXML rate groups.  The interest rate is the price the platform believes will satisfy borrower and investor expectations. I’m sure those rates vary at any given time according to the platform’s desired growth rate, supply of loans from borrowers, demand from investors, etc.

Let’s pretend for a moment that interest rate alone represents a fully comparable, cross platform risk rating. What would it be that a p2p platform would do when servicing a loan with the same level of risk to cause or prevent default?  I suppose it would come down to the diligence of their collection processes.  That seems like a tricky thing to measure.  However, if we use rate groups as a comparison of pricing models, a platform’s ability to properly match loan risk to an interest rate, by analyzing default rates across platforms sold at the same rate, the analysis would be much more telling.

Remember, these platforms don’t make money directly from the interest rates on these loans, they make money on servicing the loans – underwriting, collecting and distributing payments, and performing collection duties.  They have to set rates reasonably to keep their investors (and regulators) happy, but ultimately their job is to sell services.

To get an apples to apples comparison, you would have to compare the source data, which would be the borrower’s qualifications and requested loan reason, payment schedule, and amount, etc. The same information from the borrower that LC / Prosper used to grade and price the loan.  Then, use that info to come up with a new, standard grading system.  You’d almost be rewriting the underwriting model.  That’d be a tall order, and I’m not sure how that information would change my investment behavior.

The most effective way to judge the performance of each platform is to do just that – compare the ROI of each marketplace’s entire portfolio and compare your own ROI on each platform.

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