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
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摘要
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.
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.
引文
[1] MICHELS J. Do unverifiable disclosures matters? Evidence from peer-to-peer lending[J].Accounting Review,2012,87(4):36-41.
[2] LEE E,LEE B. Herding behaviorin online P2P lending:An empirical investigation[J].Electronic Commerce Research and Applications,2012,11(5):495-503.
[3]杨宇焰,陈倩,田忠成.P2P网络信贷平台的主要模式、风险及政策建议[J].西南金融,2014(1):29-31.
[4]卢馨,李慧敏.P2P网络借贷的运行模式与风险管控[J].改革,2015(2):60-68.
[5] LIN M,NAGPURNANAND R P,VISWANATHAN S. Judging borrowers by the company they keep:Friendship Net-works and information asymmetry in online peer-to-peer lending[J].Management Science,2013,59(1):17-35.
[6] GONZALEZ L,LOUREIRO Y K. When can a photo increasecredit? The impact of lender and borrower profiles online peer-topeer Loans[J].Journal of Behavioral&Ex-perimental Finance,2014(2):44-58.
[7] EMEKTER R,TU Y,JIRASAKULDECH B. Evaluating credit riskand loan performance in online peer-to-peer(P2P)Lending[J].Applied Economics,2015,47(1):54-70.
[8]董梁,胡明雅.基于Logistic回归模型的网贷平台新进借款人信用风险研究[J].江苏科技大学学报(社会科学版),2016,16(3):102-108.
[9]肖曼君,欧缘媛,李颖.我国P2P网络借贷信用风险影响因素研究———基于排序选择模型的实证分析[J].财经理论与实践,2015(1):2-6.
[10]王会娟,廖理.中国P2P网络借贷平台信用认证机制研究———来自“人人贷”的经验证据[J].中国工业经济,2014(4):136-147.
[11] BEKHET H A,ELETTER S F K. Credit risk assessment modelfor jordanian commercial banks:Neural scoring approach[J].Review of Development Finance,2014,4(1):20-28.
[12] ORESKI S,ORESKI G. Genetic algorithm-based heuristic for feature selection in credit risk assessment[J].Expert Systems With Applications,2014,41(4):2052-2064.
[13]宋丽平,张利坤,徐玮.P2P网络借贷个人信用风险评估[J].财会月刊,2015(35):94-96.
[14]姚凤阁,隋昕.P2P网络借贷平台借款人信用风险影响因素研究———来自“拍拍贷”的经验依据[J].哈尔滨商业大学学报(社会科学版),2016(1):3-10.
[2] LEE E,LEE B. Herding behaviorin online P2P lending:An empirical investigation[J].Electronic Commerce Research and Applications,2012,11(5):495-503.
[3]杨宇焰,陈倩,田忠成.P2P网络信贷平台的主要模式、风险及政策建议[J].西南金融,2014(1):29-31.
[4]卢馨,李慧敏.P2P网络借贷的运行模式与风险管控[J].改革,2015(2):60-68.
[5] LIN M,NAGPURNANAND R P,VISWANATHAN S. Judging borrowers by the company they keep:Friendship Net-works and information asymmetry in online peer-to-peer lending[J].Management Science,2013,59(1):17-35.
[6] GONZALEZ L,LOUREIRO Y K. When can a photo increasecredit? The impact of lender and borrower profiles online peer-topeer Loans[J].Journal of Behavioral&Ex-perimental Finance,2014(2):44-58.
[7] EMEKTER R,TU Y,JIRASAKULDECH B. Evaluating credit riskand loan performance in online peer-to-peer(P2P)Lending[J].Applied Economics,2015,47(1):54-70.
[8]董梁,胡明雅.基于Logistic回归模型的网贷平台新进借款人信用风险研究[J].江苏科技大学学报(社会科学版),2016,16(3):102-108.
[9]肖曼君,欧缘媛,李颖.我国P2P网络借贷信用风险影响因素研究———基于排序选择模型的实证分析[J].财经理论与实践,2015(1):2-6.
[10]王会娟,廖理.中国P2P网络借贷平台信用认证机制研究———来自“人人贷”的经验证据[J].中国工业经济,2014(4):136-147.
[11] BEKHET H A,ELETTER S F K. Credit risk assessment modelfor jordanian commercial banks:Neural scoring approach[J].Review of Development Finance,2014,4(1):20-28.
[12] ORESKI S,ORESKI G. Genetic algorithm-based heuristic for feature selection in credit risk assessment[J].Expert Systems With Applications,2014,41(4):2052-2064.
[13]宋丽平,张利坤,徐玮.P2P网络借贷个人信用风险评估[J].财会月刊,2015(35):94-96.
[14]姚凤阁,隋昕.P2P网络借贷平台借款人信用风险影响因素研究———来自“拍拍贷”的经验依据[J].哈尔滨商业大学学报(社会科学版),2016(1):3-10.