Sending Mixed Signals: Multilevel Reputation Effects in Peer-to-Peer Lending Markets

Online peer-to-peer (P2P) lending organizations enable an individual to obtain an unsecured loan from a collection of individuals without the participation of a bank. Previous research has addressed the use of reputation systems to reduce information asymmetry based on individual history within online markets. Within the last few years one of the market leaders in P2P lending, Prosper.com, has sought to replace the information vetting and monitoring typically done by the bank with a community of users free to select its community members based on any criteria it chooses. By embedding individual reputations within a community reputation, incentives become aligned for peers to select highly qualified borrowers and produce more costly information signals to reduce the adverse selection and moral hazard risk typical of any principle-agent relationship. This study draws on theory from the principle-agent perspective to empirically examine the signals that enhance community reputation.