Abstract: With the development of Internet information technology, P2P lending has promoted the development of Internet finance and inclusive finance. It is particularly important for the relevant platforms and lenders to make an accurate risk assessment and prevent the default risk of borrowers. Taking 4738 borrowers′ lending data provided by Rong 360 platform as research samples, the paper adopts Logistic regression model to analyze the key factors of borrower default risk, and discusses the specific characteristics of the delinquent borrower and its influence factors. The empirical results show that the borrower′s total income, total expenditure and wage income among economy features have significant impacts on borrower′s default risk in terms of repayment ability; borrower′s gender, loan limit, loan amount and delinquent amount have obvious effects on borrower′s default risk in term of repayment willingness; the number of the fewer web page and website visits are important factors of borrower′s default risk in terms of online browsing behavior. Therefore, the risk supervision department should establish a key information sharing mechanism, clarify the review scope, implement the key points of examination, and then reduce the economic losses of platform and lenders by constructing a default risk assessment model to promote the healthy development of the P2P lending industry.

Key words: P2P Lending, default risk, Logistic Regression Model