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The mechanism of credit risk contagion among internet P2P lending platforms based on a SEIR model with time-lag

Author

Listed:
  • Zhao, Chengguo
  • Li, Meng
  • Wang, Jun
  • Ma, Shujian

Abstract

The credit risk contagion of Internet peer-to-peer (P2P) lending platforms is an important part of Internet financial risk management and supervision. This study analyzes the contagion path of credit risk in Internet P2P lending. Based on complex network theory and the theory of infectious disease dynamics, the characteristics of Internet P2P lending development are combined to construct a SEIR model of credit risk transmission among Internet P2P lending platforms with time lag, and the robustness of the model is analyzed and proven. The influence of platform correlations, the susceptible immune rate, the platform elimination rate, contagion latency, the saturation coefficient, and the susceptibility input rate on credit risk contagion behavior among Internet P2P lending platforms is analyzed, using the equilibrium point and threshold value. The impact of each variable is analyzed by simulation. Corresponding countermeasures and suggestions are proposed to prevent and control credit risk contagion among these platforms.

Suggested Citation

  • Zhao, Chengguo & Li, Meng & Wang, Jun & Ma, Shujian, 2021. "The mechanism of credit risk contagion among internet P2P lending platforms based on a SEIR model with time-lag," Research in International Business and Finance, Elsevier, vol. 57(C).
    • Handle: RePEc:eee:riibaf:v:57:y:2021:i:c:s0275531921000283
    DOI: 10.1016/j.ribaf.2021.101407
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    References listed on IDEAS

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    1. Chen, Wang & Ho, Kung-Cheng & Yang, Lu, 2020. "Network structures and idiosyncratic contagion in the European sovereign credit default swap market," International Review of Financial Analysis, Elsevier, vol. 72(C).
    2. Wimboh Santoso & Irwan Trinugroho & Tastaftiyan Risfandy, 2020. "What Determine Loan Rate and Default Status in Financial Technology Online Direct Lending? Evidence from Indonesia," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 56(2), pages 351-369, January.
    3. Tsung-Pao Wu & Hung-Che Wu & Shu-Bing Liu & Hsin-Pei Hsueh & Chien-Ming Wang, 2020. "Causality Between Peer-To-Peer Lending And Bank Lending In China: Evidence From A Panel Data Approach," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 65(06), pages 1537-1557, December.
    4. Jianrong Yao & Jiarui Chen & June Wei & Yuangao Chen & Shuiqing Yang, 2019. "The relationship between soft information in loan titles and online peer-to-peer lending: evidence from RenRenDai platform," Electronic Commerce Research, Springer, vol. 19(1), pages 111-129, March.
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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. Nigmonov, Asror & Shams, Syed & Alam, Khorshed, 2022. "Macroeconomic determinants of loan defaults: Evidence from the U.S. peer-to-peer lending market," Research in International Business and Finance, Elsevier, vol. 59(C).
    3. Mauro Aliano & Lucianna Cananà & Greta Cestari & Stefania Ragni, 2023. "A Dynamical Model with Time Delay for Risk Contagion," Mathematics, MDPI, vol. 11(2), pages 1-19, January.
    4. Yuan, Kunpeng & Chi, Guotai & Zhou, Ying & Yin, Hailei, 2022. "A novel two-stage hybrid default prediction model with k-means clustering and support vector domain description," Research in International Business and Finance, Elsevier, vol. 59(C).

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    More about this item

    Keywords

    Internet P2P lending platform; credit risk contagion; SEIR model with time lag; simulation analysis;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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