What Kind of Online P2P Lending Platforms Are More Likely to Have Problems

Abstract

This paper aims to discern the characteristics of problematic P2P lending platforms. We collected the information of 650 platforms from P2P websites manually and defined 16 variables in five dimensions. Then we used binary regression model to figure out which variables significantly influence the probability of a platform being problematic. Results show that existing time, bank custody, the number of executives with financial working experience, guarantee, annual rate, ICP certificate, backer and the type of products that the platforms offer are significant variables. Particularly, this paper discovers that the platforms offering house mortgage or car loan are less likely to have problems while those offering SEM loan are relatively riskier.