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借款人特征对网络借贷风险的影响研究 被引量:5

The Impact of Borrower Characteristics on Network Loan Risk
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摘要 针对借款人特征对借款成功、贷款违约风险的影响机理进行研究,采用Logistic模型和Cox回归模型,使用某网络平台2013~2015年的网贷数据进行实证分析。研究结果表明:利率并不是P2P借贷中投资者唯一关注的指标,借款人特征对借款成功有显著影响。投资者在出借资金时,青睐于年龄偏大、已婚、高学历、工作一段时间的借款人。文章同时应用生存分析方法,得到研究结论:年龄大的借款者更容易发生违约;婚姻状况并不能有效影响贷款违约;高学历和工作时间长的借款人不容易违约。另外,贷款利率与贷款违约存在正U型关系,而贷款金额与贷款违约存在倒U型关系。该研究结论表明P2P借贷市场上的投资者在通过借款人特征识别信用风险方面存在一定的偏差。 This paper studies the mechanism of the borrower characteristics on the loan success and the default risk of the loan.Using the logistic model and the Cox regression model as the research method, this paper uses the online loan data of an internet platform from 2013 to 2015 to conduct an empirical analysis.The research results show that interest rate is not the only indicator that investors pay attention to in P2P lending, and the borrower characteristics have a significant impact on the borrowing success.When lenders borrow funds, they favor older, married, highly educated, and working borrowers.At the same time, by applying the survival analysis method, this paper concludes that the older borrowers are more likely to default;the marital status cannot effectively affect the loan default;borrowers with high academic qualifications and working hours are not easy to default.In addition, there is a positive U-shaped relationship between loan interest rate and loan default, and an inverted U-shaped relationship between loan amount and loan default.The findings demonstrate that investors in the P2P lending market have a certain degree of bias in identifying credit risk through borrower characteristics.
作者 李延喜 孙大同 赛骞 LI Yanxi;SUN Datong;SAI Qian(Faculty of Management and Economics,Dalian University of Technology,Dalian 116024,China)
出处 《大连理工大学学报(社会科学版)》 CSSCI 北大核心 2019年第1期15-22,共8页 Journal of Dalian University of Technology(Social Sciences)
基金 国家自然科学基金重点项目:"大数据环境下的微观信用评价理论与方法研究"(71731003) 辽宁省哲学社会科学规划基金重点项目:"辽宁省区域金融生态环境评价及优化路径研究"(L15AGL018) 辽宁省哲学社会科学规划基金一般项目:"金融生态多样性视角下辽宁省对‘一带一路’国家海外投资效率研究"(L17BGL018)
关键词 P2P网络借贷 借款人特征 信用风险识别 P2P Lending borrower’s characteristics credit risk identification
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