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《Finance Forum》 2014-03
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An Analysis of the Factors to Influence Successful Borrowing Rate in P2P Network Lending——A Case Study of the Paipai Lending

WEN Xiao-ni;WU Xiao-juan;  
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.
【Fund】: 陕西省金融学会重点研究课题项目 重点课题之三互联网金融服务模式创新研究(2013ZD03)
【CateGory Index】: F724.6;F832.4
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