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Can Prosper be as Prosperous as Banks?

         Credit Markets are a clear case of information asymmetry between borrowers and sellers. Felix Salmon writes that peer-to-peer lending was meant to create a personal connection between borrower and lender, giving borrowers a greater incentive to repay their debts than to “hated, faceless banks”. Did peer-to-lending cause that warm, “fuzzy” feeling to pay back all your loans ?[1] Instead, Prosper turned out to be no different and faced insurmountable adverse selection issues as well. Of course, some potential solutions to this problem include underwriting, employed to some extent by Prosper and other peer-to-peer lending systems like Lending Club but there seems to be another interesting way of approaching this problem!

         The paper “Learning by doing with asymmetric information” by Freedman and Jin shows that learning by doing also plays an important role in alleviating information asymmetry.  Although Prosper discloses part of borrowers’ credit histories, lenders do not have access to a borrower’s credit history as traditional banks do. Hence, lenders face serious information problems because the market is new and “subject to adverse selection relative to offline markets”. The most likely method to get information about the true average risk of borrowers, is evaluating similar loans from the past. However, understanding this information depends on a variety of factors like the lender’s attention to his own portfolio, awareness of market-wide performance data as well his time cost and ability to digest the information. Lender learning can be effective in reducing the risk over time for early lenders who did not fully understand the market risk and are found to have underestimated borrower risk. Freedman and Jin report that a lender is more likely to stop funding any new loans as more of his existing loans are late. [3]

          As lenders learn from their own mistakes, they learn to gauge the risk of borrowing, better and as a result, more and more sub-prime borrowers are excluded from the market and the population drifts towards the population served by traditional credit markets. We see here that in the absence of traditional techniques such as reputation systems, there can be inherent ways that markets try to alleviate the asymmetry of information. Peer to peer systems like Prosper are unique in that most people who cannot be served well by traditional offline credit markets are drawn to it. This biases the market strongly toward adverse selection. The question is how effective methods like “learning by doing” can be, so that P2P does not provide a viable alternative for those excluded from traditional credit markets. It would be intriguing to see how P2P systems compete with traditional banks in the years to come!


[1] The problem with peer-to-peer lending

[2] An open letter from Prosper

[3] Learning by Doing with Asymmetric Information



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