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Behavioural aspects of China's P2P lending

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  • Shuai Shao
  • Hong Bo

Abstract

In this paper, we argue that China's P2P lending is influenced by the behavioural factors of P2P platforms. This is because severe information asymmetry results in high uncertainty surrounding China's P2P lending industry. Specifically, we examine three behavioural aspects of P2P lending: lending sentiments, herding, and speculation. Using a sample of 918 P2P platforms from October 2015-September 2019, we document that positive P2P news release in the media (sentiments) encourages P2P lending; P2P platforms herd on their peers in making lending decisions; and P2P lending contains speculative elements and is driven by real estate bubbles. Moreover, we find that these behavioural effects are less profound if P2P platforms adopt a fund custody mechanism in which commercial banks provide custodian services for investor funds used for P2P lending. This result suggests that behavioural factors are more important in explaining P2P lending when information asymmetry is more severe. We obtain these results by controlling for other usual factors that can explain P2P lending, including characteristics of P2P platforms, macroeconomic variables, and other variables reflecting features of P2P operating environment. Our results suggest that regulators should monitor risk management of P2P platforms and reduce asymmetric information faced by participants in China's P2P lending market.

Suggested Citation

  • Shuai Shao & Hong Bo, 2022. "Behavioural aspects of China's P2P lending," The European Journal of Finance, Taylor & Francis Journals, vol. 28(1), pages 30-45, January.
  • Handle: RePEc:taf:eurjfi:v:28:y:2022:i:1:p:30-45
    DOI: 10.1080/1351847X.2021.1880459
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    Cited by:

    1. Chong, Zhaohui & Wei, Xiaolin, 2023. "Exploring the spatial linkage network of peer-to-peer lending in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    2. Yeh, Jen-Yin & Chiu, Hsin-Yu & Huang, Jhih-Huei, 2024. "Predicting failure of P2P lending platforms through machine learning: The case in China," Finance Research Letters, Elsevier, vol. 59(C).

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