计算机科学 ›› 2018, Vol. 45 ›› Issue (5): 97-101.doi: 10.11896/j.issn.1002-137X.2018.05.017

• 信息安全 • 上一篇    下一篇

基于短时多源回归算法的P2P平台风险观测方法

刘盼,李华康,孙国梓   

  1. 南京邮电大学计算机学院软件学院 南京210003,南京邮电大学计算机学院软件学院 南京210003,南京邮电大学计算机学院软件学院 南京210003
  • 出版日期:2018-05-15 发布日期:2018-07-25
  • 基金资助:
    本文受国家自然科学基金青年项目(61502247),公安部重点实验室开放课题(2015DSJSYS001),江苏省高校自然科学研究面上项目(14KJB520028)资助

Risk Observing Method Based on Short-time Multi-source Regression Algorithm on P2P Platform

LIU Pan, LI Hua-kang and SUN Guo-zi   

  • Online:2018-05-15 Published:2018-07-25

摘要: P2P网络借贷作为当代互联网金融领域中流行的借贷方式,具有借款金额小、还款周期长短不一的特点,导致传统的年度风险评估方法因时间粒度过粗而容易给 平台投资者造成损失。基于此,提出一种基于短时多源回归算法的网络借贷平台运营风险的动态评估方法。通过动态时间窗对借贷记录进行切分,并以线性回归来量化平台的动态风险指数。实验结果表明,该方法能够及时反映P2P平台的风险宏观运营情况,并向投资者提供平台的动态风险评估和预测指标。

关键词: P2P网络借贷,运营风险,时间窗,短时多源回归算法

Abstract: Peer-to-Peer(P2P) lending is a popular lending way in the field of contemporary Internet finance.There are small lending amount and different repayment cyclelengths,which may easily cause the loss of platform investors due to annual risk assessment.This paper proposed a method to dynamically evaluate the operation risk of P2P platforms based on short-time multi-source regression algorithm.In this algorithm,dynamic time windows are used to split up the len-ding records and linear regression method is used to quantify the dynamic risk index of P2P platforms.The experimental results show the method can reflect the visible operation situation of platforms,and can provide dynamic risk assessment and forecast indicators of the platforms to investors.

Key words: P2P lending,Operation risk,Time window,Short-time multi-source regression

[1] BERGER S C,GLEISNER F.Emergence of financial intermedia-ries in electronic markets:The case of online P2P lending[J].BuR-Business Research,2009,2(1):39-65.
[2] QIAN J Y,YANG F,The Development Status and Prospects of Chinese P2P Network Lending[J].Finance Forum,2012(1):46-51.(in Chinese) 钱金叶,杨飞.中国 P2P 网络借贷的发展现状及前景[J].金融论坛,2012(1):46-51.
[3] EMEKTER R,TU Y,JIRASAKULDECH B,et al.Evaluating credit risk and loan performance in online Peer-to-Peer(P2P) lending[J].Applied Economics,2015,47(1):54-70.
[4] 董峰.我国P2P网络借贷平台模式及其风险研究[D].昆明:云南财经大学,2015.
[5] 陈作章,赵敏.P2P网络借贷平台风险控制研究[J].现代商业,2014(20):39-42.
[6] FREEDMAN S M,JIN G Z.Learning by Doing with Asymmetric Information:evidence from Prosper.com[R].National Bureau of Economic Research,2011.
[7] YE X R.The Risks of China’s P2P Lending Models and Related Regulations[J].Financial Regulation Research,2014,2(1):175-194.
[8] MACH T,CARTER C,SLATTERY C R.Peer-to-Peer Lending to Small Businesses[J].Social Science Electronic Publishing ,2014,0(96):945-975.
[9] FANG Z,ZHANG J,ZHIYUAN F.Study on P2P E-FinancePlatform System: A Case in China[C]∥ 2014 IEEE 11th International Conference on E-Business Engineering(ICEBE).IEEE,2014:331-337.
[10] 李龙.我国P2P网络借贷的风险与监管探讨[D].杭州:浙江大学,2014.
[11] FUNK B,BACHMANN A,BECKER A,et al.Online Peer-to-Peer Lending-A Literature Review[J].Journal of Internet Ban-king and Commerce,2011,16(2):1-18.
[12] ZHAO H,LIU Q,WANG G,et al.Portfolio Selections in P2P Lending:A Multi-Objective Perspective[C]∥ACM SIGKDD International Conference on Knowledge Discovery and Data Mi-ning.ACM,2016:2075-2084.
[13] EVERETT C R.Group Membership,Relationship Banking and Loan Default Risk:The Case of Online Social Lending[J].Ban-king & Finance Review,2015,7(2):1-31.
[14] FAN J,PENG L,DU Y,et al.A study on the users’ behaviors of P2P online lending platforms[C]∥2015 12th International Conference on Service Systems and Service Management(ICSSSM).IEEE,2015:1-4.
[15] HERRERO-LOPEZ S.Social interactions in P2P lending[C]//Proceedings of the 3rd Workshop on Social Network Mining and Analysis.ACM,2009:3.
[16] LUO B,LIN Z.A decision tree model for herd behavior and empirical evidence from the online P2P lending market[J].Information Systems and e-Business Management,2013,11(1):141-160.
[17] BARASINSKA N,SCHFER D.Does gender affect fundingsuccess at the peer-to-peer credit markets? Evidence from the largest German lending platform[J/OL].http://hdl.handle.net/10419/52541.
[18] TAN J,DE SILVA D G.Better off or worse off:An economic analysis of online P2P lending market[C]∥ICSSSM11.IEEE,2011:1-3.
[19] SHEN D,KRUMME C,LIPPMAN A.Follow the profit or the herd? Exploring social effects in peer-to-peer lending[C]∥2010 IEEE Second International Conference on Social Computing(SocialCom).IEEE,2010:137-144.
[20] WIGINTON J C.A note on the comparison of logit and discriminant models of consumer credit behavior[J].Journal of Financial and Quantitative Analysis,1980,15(3):757-770.
[21] JIN Y,ZHU Y.A Data-Driven Approach to Predict Default Risk of Loan for Online Peer-to-Peer(P2P) Lending[C]∥ 2015 Fifth International Conference on Communication Systems and Network Technologies(CSNT).IEEE,2015:609-613.
[22] KLAFFT M.Peer to peer lending:auctioning microcredits over the internet[C]∥International Conference on Information Systems,Technology and Management.2008.
[23] 莫易娴.国内P2P网络借贷平台发展模式比较分析[J].开发研究,2014,172(3):126-130.
[24] BYANJANKAR A,HEIKKIL M,MEZEI J.Predicting Credit Risk in Peer-to-Peer Lending:A Neural Network Approach[C]∥2015 IEEE Symposium Series on Computational Intelligence.IEEE,2015:719-725.
[25] WANG Y,LI S,LIN Z.Revealing Key Non-financial Factors for Online Credit-Scoring in e-Financing[C]∥2013 10th International Conference on Service Systems and Service Management.IEEE,2013:547-552.
[26] XU L J,LIU Y.A study on choosing network lending platforms by grey clustering method based on the sight of investors[C]∥2015 IEEE International Conference on Grey Systems and Intelligent Services(GSIS).Leicester,2015:647-653.
[27] Data.Knowledge.Intelligence.http://www.trs.com.cn.
[28] LI X.Analysis on The Development and Alienation of China’s P2P Lending From the Perspective of Financial Regulation and Supervision[J].Finance & Economics,2016,1(5):32-40.

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