P2P网络借贷成功率影响因素分析——以拍拍贷为例

An Analysis of the Factors to Influence Successful Borrowing Rate in P2P Network Lending——A Case Study of the Paipai Lending

本文以中国最大的P2P网络借贷网站拍拍贷为例,采用二元logistic回归模型建立网络借贷模型,研究影响借贷成功率的因素,并进行蒙特卡洛模拟。研究结果表明:借款利率、借款人历史失败次数对借款成功率有负的影响,而借款金额、借款人历史成功次数、信用积分、审核项目数对借款结果有正的影响。同时,借款人的性别、住宅情况也对借款结果有影响。在金融市场化改革过程中,与传统金融相比,P2P网络借贷除应重视模式创新之外,更要充分运用大数据的优势进行有效的信用评估和风险评估,从而为征信体系建设和借贷双方服务提供有利条件。

Paipai Lending, the largest P2P network lending website in China, is used as a sample in this paper. Based on the Binary Logistic Regression model, the paper presents a network lending model for the research of factors to influence successful borrowing rate, and makes a Monte Carlo simulation. The results of the paper show that the interest rate of borrowing and the times of borrower＇s failure borrowing in the past negatively influence successful borrowing rate, while the amount of borrowing, times of borrower＇s successful borrowing in the past, credit scores, number of censored items positively influence successful borrowing rate. In addition, borrower＇s gender and residential status also influence successful borrowing rate. In the process of financial market-oriented reform, the P2P network lending, compared with conventional finance, should innovate its own mode, but what is the more important is to make full use of the advantages of big data for effective credit evaluation and risk assessment, so as to help the construction of credit system and the lender-borrower service.