Research on Risk Factors Identification of P2P Lending Platforms

Abstract

We take 2259 P2P Lending platforms as the sample, and integrate 14 variables from five dimensions to analyze the risk factors of P2P Lending problematic platforms by binary logistic model. The empirical results show that the 11 variables which are the type of company, platform background, operation time, the type of project, interest rate, fund custody, term of loan, day-bid, transfer of creditor's rights, automatic bidding and information disclosure, have significant influences on the operating status of the platform, while the other variables such as registered capital, the number of employees and security mechanism have no obvious impact on the operating status of the platform. The results provide a reference for investors and regulators.

Causality Between Peer-to-Peer Lending and Bank Lending in China: Evidence From a Panel Data Approach

“…For example, Chen et al (2013) found that there was significant gender discrimination in the P2P lending market in China, showing that female borrowers were less likely to be funded than male ones, but their default rates were lower. What is more, Lu and Zhang (2018) proposed that platform strength, profitability, risk control, liquidity and transparency could predict the probability of the platform becoming problematic.…”