Do Social Networks Solve Information Problems for Peer-to-Peer Lending? Evidence from Prosper.com

This paper studies peer-to-peer (p2p) lending on the Internet. Prosper.com, the first p2p lending website in the US, matches individual lenders and borrowers for unsecured consumer loans. Using transaction data, the paper examines information problems that exist on Prosper and seeks to find out if social networks can help alleviate them. The data identifies three information problems on Prosper.com:

• Lenders face extra adverse selection because they observe categories of credit grades rather than actual credit scores;
• Many lenders have made mistakes in loan selection but learn over time;
• Higher interest rates can imply lower rate of return because they attract lower quality borrowers.

Although microfinance theories suggest that social networks may help identify good risks, the paper finds evidence both, for and against the argument. It also finds that:

• Loans with friend endorsements and friend bids have fewer missed payments and yield higher rates of return than other loans;
• Estimated group loan returns are lower than non-group loan returns;
• Return gap between group and non-group loans is closing over time due to lender learning and the elimination of group leader rewards.