IDEAS home Printed from https://ideas.repec.org/a/eee/reveco/v72y2021icp334-348.html
   My bibliography  Save this article

Determinants of defaults on P2P lending platforms in China

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S105905602030280X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.iref.2020.11.012?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Tykvová, Tereza & Borell, Mariela, 2012. "Do private equity owners increase risk of financial distress and bankruptcy?," Journal of Corporate Finance, Elsevier, vol. 18(1), pages 138-150.
    2. Morris, Stephen & Shin, Hyun Song, 1998. "Unique Equilibrium in a Model of Self-Fulfilling Currency Attacks," American Economic Review, American Economic Association, vol. 88(3), pages 587-597, June.
    3. Psillaki, Maria & Tsolas, Ioannis E. & Margaritis, Dimitris, 2010. "Evaluation of credit risk based on firm performance," European Journal of Operational Research, Elsevier, vol. 201(3), pages 873-881, March.
    4. repec:bla:jfinan:v:55:y:2000:i:4:p:1655-1703 is not listed on IDEAS
    5. Scott, James, 1981. "The probability of bankruptcy: A comparison of empirical predictions and theoretical models," Journal of Banking & Finance, Elsevier, vol. 5(3), pages 317-344, September.
    6. Ferson, Wayne & Mo, Haitao, 2016. "Performance measurement with selectivity, market and volatility timing," Journal of Financial Economics, Elsevier, vol. 121(1), pages 93-110.
    7. Berger, Allen N. & DeYoung, Robert, 1997. "Problem loans and cost efficiency in commercial banks," Journal of Banking & Finance, Elsevier, vol. 21(6), pages 849-870, June.
    8. Freeman, Richard B, 1984. "Longitudinal Analyses of the Effects of Trade Unions," Journal of Labor Economics, University of Chicago Press, vol. 2(1), pages 1-26, January.
    9. Fortin, Nicole & Lemieux, Thomas & Firpo, Sergio, 2011. "Decomposition Methods in Economics," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 1, pages 1-102, Elsevier.
    10. Douglas W. Diamond & Philip H. Dybvig, 2000. "Bank runs, deposit insurance, and liquidity," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 24(Win), pages 14-23.
    11. Oaxaca, Ronald, 1973. "Male-Female Wage Differentials in Urban Labor Markets," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(3), pages 693-709, October.
    12. Grinblatt, Mark & Titman, Sheridan, 1992. "The Persistence of Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 47(5), pages 1977-1984, December.
    13. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    14. Merton, Robert C, 1974. "On the Pricing of Corporate Debt: The Risk Structure of Interest Rates," Journal of Finance, American Finance Association, vol. 29(2), pages 449-470, May.
    15. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
    16. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    17. Alan S. Blinder, 1973. "Wage Discrimination: Reduced Form and Structural Estimates," Journal of Human Resources, University of Wisconsin Press, vol. 8(4), pages 436-455.
    18. Kerry D. Vandell, 1993. "Handing Over the Keys: A Perspective on Mortgage Default Research," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 21(3), pages 211-246, September.
    19. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure - Reply," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 123-127.
    20. 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.
    21. Daniel, Kent & Titman, Sheridan, 1997. "Evidence on the Characteristics of Cross Sectional Variation in Stock Returns," Journal of Finance, American Finance Association, vol. 52(1), pages 1-33, March.
    22. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 71-111.
    23. Yeujun Yoon & Yu Li & Yan Feng, 2019. "Factors affecting platform default risk in online peer-to-peer (P2P) lending business: an empirical study using Chinese online P2P platform data," Electronic Commerce Research, Springer, vol. 19(1), pages 131-158, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. Ho, Kung-Cheng & Gu, Yan & Yan, Cheng & Gozgor, Giray, 2024. "Peer effects in the online peer-to-peer lending market: Ex-ante selection and ex-post learning," International Review of Financial Analysis, Elsevier, vol. 92(C).
    5. 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).
    6. 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).
    7. Kgoroeadira, Reabetswe & Burke, Andrew & Di Pietro, Francesca & van Stel, André, 2023. "Determinants of firms’ default on unsecured loans in the P2P crowdfunding market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 89(C).
    8. 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.
    9. Evangelos Katsamakas & J. Manuel Sanchez-Cartas, 2024. "A computational model of the effects of borrower default on the stability of P2P lending platforms," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 14(3), pages 597-618, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ahsan Habib & Mabel D' Costa & Hedy Jiaying Huang & Md. Borhan Uddin Bhuiyan & Li Sun, 2020. "Determinants and consequences of financial distress: review of the empirical literature," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(S1), pages 1023-1075, April.
    2. Serrano-Cinca, Carlos & Gutiérrez-Nieto, Begoña & Bernate-Valbuena, Martha, 2019. "The use of accounting anomalies indicators to predict business failure," European Management Journal, Elsevier, vol. 37(3), pages 353-375.
    3. Adler Haymans Manurung & Derwin Suhartono & Benny Hutahayan & Noptovius Halimawan, 2023. "Probability Bankruptcy Using Support Vector Regression Machines," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 13(1), pages 1-3.
    4. Sumaira Ashraf & Elisabete G. S. Félix & Zélia Serrasqueiro, 2019. "Do Traditional Financial Distress Prediction Models Predict the Early Warning Signs of Financial Distress?," JRFM, MDPI, vol. 12(2), pages 1-17, April.
    5. Katarina Valaskova & Dominika Gajdosikova & Jaroslav Belas, 2023. "Bankruptcy prediction in the post-pandemic period: A case study of Visegrad Group countries," Oeconomia Copernicana, Institute of Economic Research, vol. 14(1), pages 253-293, March.
    6. Jackson, Richard H.G. & Wood, Anthony, 2013. "The performance of insolvency prediction and credit risk models in the UK: A comparative study," The British Accounting Review, Elsevier, vol. 45(3), pages 183-202.
    7. Christian Lohmann & Thorsten Ohliger, 2020. "Bankruptcy prediction and the discriminatory power of annual reports: empirical evidence from financially distressed German companies," Journal of Business Economics, Springer, vol. 90(1), pages 137-172, February.
    8. Zhou, Fanyin & Fu, Lijun & Li, Zhiyong & Xu, Jiawei, 2022. "The recurrence of financial distress: A survival analysis," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1100-1115.
    9. Trueck, Stefan & Rachev, Svetlozar T., 2008. "Rating Based Modeling of Credit Risk," Elsevier Monographs, Elsevier, edition 1, number 9780123736833.
    10. Mousavi, Mohammad M. & Ouenniche, Jamal & Xu, Bing, 2015. "Performance evaluation of bankruptcy prediction models: An orientation-free super-efficiency DEA-based framework," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 64-75.
    11. Yung-Ho Chiu & Yu-Chuan Chen & Yu Han Hung, 2009. "Basel II and bank bankruptcy analysis," Applied Economics Letters, Taylor & Francis Journals, vol. 16(18), pages 1843-1847.
    12. Mohammad Mahdi Mousavi & Jamal Ouenniche & Kaoru Tone, 2023. "A dynamic performance evaluation of distress prediction models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 756-784, July.
    13. du Jardin, Philippe, 2015. "Bankruptcy prediction using terminal failure processes," European Journal of Operational Research, Elsevier, vol. 242(1), pages 286-303.
    14. Marielle de Jong & Lauren Stagnol, 2016. "A fundamental bond index including solvency criteria," Journal of Asset Management, Palgrave Macmillan, vol. 17(4), pages 280-294, July.
    15. Zhang, Xuan & Ouyang, Ruolan & Liu, Ding & Xu, Liao, 2020. "Determinants of corporate default risk in China: The role of financial constraints," Economic Modelling, Elsevier, vol. 92(C), pages 87-98.
    16. Catherine Refait, 2000. "Estimation du risque de défaut par une modélisation stochastique du bilan : Application à des firmes industrielles françaises," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-03718527, HAL.
    17. Duc Hong Vo & Binh Ninh Vo Pham & Chi Minh Ho & Michael McAleer, 2019. "Corporate Financial Distress of Industry Level Listings in Vietnam," JRFM, MDPI, vol. 12(4), pages 1-17, September.
    18. Frieda Rikkers & Andre E. Thibeault, 2009. "A Structural form Default Prediction Model for SMEs, Evidence from the Dutch Market," Multinational Finance Journal, Multinational Finance Journal, vol. 13(3-4), pages 229-264, September.
    19. Oliver Lukason & Art Andresson, 2019. "Tax Arrears Versus Financial Ratios in Bankruptcy Prediction," JRFM, MDPI, vol. 12(4), pages 1-13, December.
    20. Ampudia, Miguel & Busetto, Filippo & Fornari, Fabio, 2022. "Chronicle of a death foretold: does higher volatility anticipate corporate default?," Working Paper Series 2749, European Central Bank.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reveco:v:72:y:2021:i:c:p:334-348. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620165 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.