Jun Yang is an associate professor of finance at Kelley School of Business, Indiana university. Prof. Yang obtained her Ph.D. in Finance from Washington University in Saint Louis in 2005 and Ph.D. in Operations Management from the Chinese University of Hong Kong in 1997. Her main research areas are Financial Contracting, Corporate Finance, Corporate Governance and Executive Compensation. Her research has been published in top academic journals such as Journal of Financial Economics, Review of Financial Studies, Journal of Economic Theory and Management Science.
Using data from a major peer-to-peer (P2P) lending market, we document that lenders appear to follow a simple heuristic, and make quick investment decisions based on interest rates. This heuristic is helpful because the institutional arrangements in this market significantly limit the loss from default, and hence interest rates and loan performances are highly correlated. Interestingly, credit ratings, which are provided by the P2P lending platform, also strongly predict loan performances. Holding the interest rate constant, loans with a “High Risk” rating underperform other loans by over 1% per year. Despite the fact that these ratings are free and only a click away, investors appear to largely ignore them. Through experiments, we find that by making credit rating information more salient, we can “nudge” investors into paying more attention to ratings and hence significantly improve their welfare.