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User Data Can Tell Defaulters in P2P Lending

Author

Listed:
  • Jackson J. Mi

    (Fudan University)

  • Tianxiao Hu

    (Fudan University)

  • Luke Deer

    (The University of Sydney
    The University of Cambridge)

Abstract

Online peer-to-peer (P2P) lending service is a new type of financial platforms that enables individuals borrow and lend money directly from one to another. As P2P lending service is rapidly developing, a number of rating systems of borrowers’ creditworthiness are published by different P2P lending companies. However, whether these rating systems could truly reflect the creditworthiness and loan risk of borrowers is unconfirmed. In this paper, we analyzed the differences between credit levels and users’ distribution of CPLP to evaluate if the credit levels can truly reflect the borrowers’ credit. We used soft factors to establish a model that can find borrowers who are likely to default. Further, we proposed some strategies to construct and improve the risk-control of P2P lending platforms according to the result of our research.

Suggested Citation

  • Jackson J. Mi & Tianxiao Hu & Luke Deer, 2018. "User Data Can Tell Defaulters in P2P Lending," Annals of Data Science, Springer, vol. 5(1), pages 59-67, March.
    • Handle: RePEc:spr:aodasc:v:5:y:2018:i:1:d:10.1007_s40745-017-0134-z
    DOI: 10.1007/s40745-017-0134-z
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    References listed on IDEAS

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    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. Nataliya Barasinska & Dorothea Schäfer, 2010. "Does Gender Affect Funding Success at the Peer-to-Peer Credit Markets?: Evidence from the Largest German Lending Platform," Discussion Papers of DIW Berlin 1094, DIW Berlin, German Institute for Economic Research.
    3. 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.
    4. Milne, Alistair & Parboteeah, Paul, 2016. "The Business Models and Economics of Peer-to-Peer Lending," ECRI Papers 11594, Centre for European Policy Studies.
    5. 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.
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    Cited by:

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