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Who can get money? Evidence from the Chinese peer-to-peer lending platform

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  • Qizhi Tao

    (Southwestern University of Finance and Economics)

  • Yizhe Dong

    (University of Aberdeen)

  • Ziming Lin

    (Southwestern University of Finance and Economics)

Abstract

This paper explores how borrowers’ financial and personal information, loan characteristics and lending models affect peer-to-peer (P2P) loan funding outcomes. Using a large sample of listings from one of the largest Chinese online P2P lending platforms, we find that those borrowers earning a higher income or who own a car are more likely to receive a loan, pay lower interest rates, and are less likely to default. The credit grade assigned by the lending platform may not represent the creditworthiness of potential borrowers. We also find that the unique offline process in the Chinese P2P online lending platform exerts significant influence on the lending decision. We discuss the implications of our results for the design of big data-based lending markets.

Suggested Citation

  • Qizhi Tao & Yizhe Dong & Ziming Lin, 2017. "Who can get money? Evidence from the Chinese peer-to-peer lending platform," Information Systems Frontiers, Springer, vol. 19(3), pages 425-441, June.
    • Handle: RePEc:spr:infosf:v:19:y:2017:i:3:d:10.1007_s10796-017-9751-5
    DOI: 10.1007/s10796-017-9751-5
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    as
    1. Guo, Yanhong & Zhou, Wenjun & Luo, Chunyu & Liu, Chuanren & Xiong, Hui, 2016. "Instance-based credit risk assessment for investment decisions in P2P lending," European Journal of Operational Research, Elsevier, vol. 249(2), pages 417-426.
    2. Rajkamal Iyer & Asim Ijaz Khwaja & Erzo F. P. Luttmer & Kelly Shue, 2016. "Screening Peers Softly: Inferring the Quality of Small Borrowers," Management Science, INFORMS, vol. 62(6), pages 1554-1577, June.
    3. Belleflamme, Paul & Omrani, Nessrine & Peitz, Martin, 2015. "The economics of crowdfunding platforms," Information Economics and Policy, Elsevier, vol. 33(C), pages 11-28.
    4. Mild, Andreas & Waitz, Martin & Wöckl, Jürgen, 2015. "How low can you go? — Overcoming the inability of lenders to set proper interest rates on unsecured peer-to-peer lending markets," Journal of Business Research, Elsevier, vol. 68(6), pages 1291-1305.
    5. Massimo G. Colombo & Chiara Franzoni & Cristina Rossi–Lamastra, 2015. "Internal Social Capital and the Attraction of Early Contributions in Crowdfunding," Entrepreneurship Theory and Practice, , vol. 39(1), pages 75-100, January.
    6. Chittaranjan Hota & Shambhu Upadhyaya & Jamal Nazzal Al-Karaki, 2015. "Advances in secure knowledge management in the big data era," Information Systems Frontiers, Springer, vol. 17(5), pages 983-986, October.
    7. Dorfleitner, Gregor & Priberny, Christopher & Schuster, Stephanie & Stoiber, Johannes & Weber, Martina & de Castro, Ivan & Kammler, Julia, 2016. "Description-text related soft information in peer-to-peer lending – Evidence from two leading European platforms," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 169-187.
    8. Nataliya Barasinska & Dorothea Schäfer, 2010. "Are Women More Credit-Constrained than Men?: Evidence from a Rising Credit Market," Working Paper / FINESS 6.3, DIW Berlin, German Institute for Economic Research.
    9. Cumming, Douglas & Zhang, Yelin, 2016. "Alternative investments in emerging markets: A review and new trends," Emerging Markets Review, Elsevier, vol. 29(C), pages 1-23.
    10. Douglas W. Diamond, 1984. "Financial Intermediation and Delegated Monitoring," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 51(3), pages 393-414.
    11. Devin G. Pope & Justin R. Sydnor, 2011. "What’s in a Picture?: Evidence of Discrimination from Prosper.com," Journal of Human Resources, University of Wisconsin Press, vol. 46(1), pages 53-92.
    12. Iyer, Rajkamal & Khwaja, Asim Ijaz & Luttmer, Erzo F. P. & Shue, Kelly, 2009. "Screening in New Credit Markets: Can Individual Lenders Infer Borrower Creditworthiness in Peer-to-Peer Lending?," Working Paper Series rwp09-031, Harvard University, John F. Kennedy School of Government.
    13. repec:diw:diwfin:diwfin06030 is not listed on IDEAS
    14. Nguyen Hoang Thuan & Pedro Antunes & David Johnstone, 2016. "Factors influencing the decision to crowdsource: A systematic literature review," Information Systems Frontiers, Springer, vol. 18(1), pages 47-68, February.
    15. Stiglitz, Joseph E & Weiss, Andrew, 1981. "Credit Rationing in Markets with Imperfect Information," American Economic Review, American Economic Association, vol. 71(3), pages 393-410, June.
    16. Soe-Tsyr Daphne Yuan & Ching-Fang Hsieh, 0. "An impactful crowdsourcing intermediary design - a case of a service imagery crowdsourcing system," Information Systems Frontiers, Springer, vol. 0, pages 1-22.
    17. Marta Poblet & Esteban García-Cuesta & Pompeu Casanovas, 0. "Crowdsourcing roles, methods and tools for data-intensive disaster management," Information Systems Frontiers, Springer, vol. 0, pages 1-17.
    18. Ladd, Helen F, 1982. "Equal Credit Opportunity: Women and Mortgage Credit," American Economic Review, American Economic Association, vol. 72(2), pages 166-170, May.
    19. Seth Freedman & Ginger Zhe Jin, 2008. "Do Social Networks Solve Information Problems for Peer-to-Peer Lending? Evidence from Prosper.com," Working Papers 08-43, NET Institute.
    20. Bram Klievink & Bart-Jan Romijn & Scott Cunningham & Hans Bruijn, 0. "Big data in the public sector: Uncertainties and readiness," Information Systems Frontiers, Springer, vol. 0, pages 1-17.
    21. Mingfeng Lin & Nagpurnanand R. Prabhala & Siva Viswanathan, 2013. "Judging Borrowers by the Company They Keep: Friendship Networks and Information Asymmetry in Online Peer-to-Peer Lending," Management Science, INFORMS, vol. 59(1), pages 17-35, August.
    22. Atreyi Kankanhalli & Jungpil Hahn & Sharon Tan & Gordon Gao, 2016. "Big data and analytics in healthcare: Introduction to the special section," Information Systems Frontiers, Springer, vol. 18(2), pages 233-235, April.
    23. Jefferson Duarte & Stephan Siegel & Lance Young, 2012. "Trust and Credit: The Role of Appearance in Peer-to-peer Lending," The Review of Financial Studies, Society for Financial Studies, vol. 25(8), pages 2455-2484.
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    Cited by:

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    21. Yanhong Guo & Shuai Jiang & Wenjun Zhou & Chunyu Luo & Hui Xiong, 2021. "A predictive indicator using lender composition for loan evaluation in P2P lending," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-24, December.

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