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Determinants of defaults on P2P lending platforms in China

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  • Gao, M.
  • Yen, J.
  • Liu, M.

Abstract

Chinese P2P lending platforms have an astonishing default rate of 87.2% based on data available in 2019, which indicates the seriousness of the problem this industry faces. Insufficient regulation has resulted in generation of risky services, such as margin finance in 2015 for stock markets and zero down-payment mortgages in 2016 for real estate buyers. Such services are prone to resulting in dramatic losses to investors with the following potential causes: adverse selection caused by information asymmetry of the P2P platform operators, lack of financial knowledge or expertise of the investors, insufficient regulation on P2P platforms, and changes in policies related to stock and real estate markets.

Suggested Citation

  • Gao, M. & Yen, J. & Liu, M., 2021. "Determinants of defaults on P2P lending platforms in China," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 334-348.
    • Handle: RePEc:eee:reveco:v:72:y:2021:i:c:p:334-348
    DOI: 10.1016/j.iref.2020.11.012
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    Cited by:

    1. Hui Zheng & Xuexu Piao & Sangmoon Park, 2021. "The Role of Founder-CEO, Human Capital and Legitimacy in Venture Capital Financing in China’s P2P Lending Industry," Sustainability, MDPI, vol. 13(4), pages 1-14, February.
    2. Wang, Jin & Li, Rui, 2023. "Asymmetric information in peer-to-peer lending: empirical evidence from China," Finance Research Letters, Elsevier, vol. 51(C).
    3. Li, Jianwen, 2023. "MSMEs meet FinTech: Chance or challenge?," Finance Research Letters, Elsevier, vol. 57(C).
    4. Sha, Yezhou, 2022. "Rating manipulation and creditworthiness for platform economy: Evidence from peer-to-peer lending," International Review of Financial Analysis, Elsevier, vol. 84(C).
    5. Jen-Yin Yeh & Hsin-Yu Chiu & Jhih-Huei Huang, 2023. "Predicting Failure of P2P Lending Platforms through Machine Learning: The Case in China," Papers 2311.14577, arXiv.org.

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