Does Appearance Matter? Exploring the Role of Facial Features for Judging Borrowers’ Credibility in Online P2P Lending Markets

Abstract

Prior research has found the beauty premium effect in peer-to-peer (P2P) lending markets. However, it remains unknown whether and how lenders rely on borrowers’ facial characteristics to infer their financial credibility. In this research, we propose a set of facial features that can be automatically extracted from images using face recognition techniques. Our analysis of a large sample collected from a Chinese P2P lending platform reveals that borrowers with lower socioeconomic status are more likely to include face images in their account profiles. However, these images do not necessarily help attract more investors. The in-depth analysis of the facial features shows that when presented with face images of borrowers, lenders tend to associate the appearance of borrowers with their financial credibility and generally prefer “good-looking” borrowers, who have a round face, a longer philtrum, and a higher nose. However, these facial features cannot be used to predict loan repayment performance.