Online P2P lending industry: an international analysis

  • Meijing LAN

    Student thesis: PhD Thesis


    This thesis comprises three essays that explore a number of research questions in the online peer-to-peer (P2P) lending industry from an international perspective. The first essay highlights an intriguing phenomenon in the Chinese online P2P lending market, whereby investors keep lending in platforms when the majority of them fail. This essay shows that investors are able to leverage nonstandard information, especially social capital information, in screening platforms and making investment decisions. Using a hand-collected sample of 6,190 Chinese platforms from June 2007 to June 2017, this essay provides robust evidence that social capital plays a significant role in platform survival inference and its economic significance is stronger than standard information such as financial capital. The findings highlight the contribution of social capital in reducing information asymmetry for investors, and offer policy and practical implications for regulators and risk managers in this innovative and fast-growing industry. The second essay explores the diversity of borrowers’ default behavior across credit grades in the online P2P lending market using data from the US P2P platform— In this essay, prediction models are developed based on flexible parametric functions to separately capture the default probability for different credit grade borrowers. Using a comprehensive list of prediction variables, this essay identifies different sets of predictors affecting the loan default probability for borrowers in different credit grade groups. The findings highlight the importance of differential borrower credit grades on prospective loan default and are relevant to investors and regulators alike in this market. The third essay empirically explores the indicators behind the survival of Chinese P2P platforms comprehensively from four perspectives, including investment, borrowing, platform background and operation environment, and further discusses their economic implications, using monthly data of 1,274 platforms during 2007-2016. Empirical results suggest the following: (i) good-quality assets is critical for platform survival; (ii) higher registered capital and stronger shareholder background infer higher survival probabilities; and (iii) government policy, the outstanding loan amount, interest rate, and location all play a significant role. Based on these findings, this essay’s policy recommendations are to strengthen the regulation of loan quality, pay attention to industry entrance requirement, and establish day-to-day regulation system on those impact factors to improve platform survival.
    Date of Award8 Jul 2019
    Original languageEnglish
    Awarding Institution
    • Univerisity of Nottingham
    SupervisorXiaoquan Liu (Supervisor) & Xiuping Hua (Supervisor)


    • Crowdfunding
    • Credit Risk
    • Proportional Odds Model

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