Seminar (Dept. of Finance)

ABSTRACT:

In this paper, we adopt an innovative strategy to assess borrowers’ creditworthiness in consumer credit markets. This new assessment strategy applies machine-learning based analyses on real-time video information that records borrowers’ behavior during the loan application process. We find that the extent of borrowers’ facial expressions of happiness is negatively associated with the likelihood of future loan delinquency. In contrast, such delinquency likelihood increases with the degree of fear expressions. These results are consistent with two economic channels relating to the adequacy and uncertainty of borrowers’ future income, drawn from the extant psychology and economics literature. Our study provides important practical implications for marketplace lenders and policymakers.