P2P网贷借款人违约风险影响因素研究——基于Logistic模型的实证分析

Research on the Factors Affecting Default Risk of P2P Online Loan Borrowers:An Empirical Analysis Based on Logistic Model

P2P网贷在爆发式增长的同时,也面临着重大的信用风险,对借款人违约风险的预测是降低信用风险的重要方法。以"人人贷"平台上采取的数据为研究样本,构建借款人信用评价指标体系,采用二元Logistic回归模型建立借款人信用风险评估模型。结果表明,借款期限、借款人年龄、信用评级、逾期次数对借款人信用风险影响最为显著,其次是学历、成功借款次数、借款利率和房产。

While P2P is experiencing explosive growth,it also faces significant credit risks.The prediction of borrower default risk is an important method to reduce credit risk.Taking the data taken on the platform of"Everyone's Loan"as the research sample,the credit evaluation index system of borrowers is constructed,and the dual-logistic regression model is used to establish the credit risk assessment model of borrowers.The results show that the borrowing period,the borrower's age,credit rating and overdue times have the most significant impact on the borrower's credit risk,followed by education,successful borrowings,borrowing rates,and real estate.