Information Asymmetries and Identification Bias in Peer-to-Peer Social Microlending

The Internet enables intermediaries like Kiva.org to link Western lenders with impoverished third-world entrepreneurial borrowers. While this approach provides capital for lending and an ultimate goal of poverty reduction, problems arise when Western lenders are responsible for microloan funding decisions. First, there exists an information asymmetry between the microfinance institutions (MFIs) administering the loans and the lenders making capital investment decisions. Second, lenders’ funding decisions are biased by identification-links to borrowers. In this study, we demonstrate this information asymmetry in the context of P2P technology loans through an analytical model and data-driven empirical models. A new IT-enabled social lending theory is proposed that explains the gaps that exist between lending decisions and loan success. The study offers evidence that loan funding decisions in P2P social microlending channels are not made on the basis of potential loan success and that identification biases create inefficiencies in lender funding decisions.