IDEAS home Printed from https://ideas.repec.org/p/jrp/jrpwrp/2016-023.html
   My bibliography  Save this paper

Determinants of borrowers' default in P2P lending under consideration of the loan risk class

Author

Listed:
  • Michal Polena

    (School of Economics and Business Administration, Friedrich-Schiller-University Jena)

  • Tobias Regner

    (School of Economics and Business Administration, Friedrich-Schiller-University Jena)

Abstract

We study the determinants of borrowers' default in P2P lending with a new data set consisting of 70,673 loan observations from Lending Club. Previous research identified a number of default determining variables but did not distinguish between different loan risk levels. We define four loan risk classes and test the significance of the default determining variables within each loan risk class. Our findings suggest that the significance of most variables depends on the loan risk class. Only few variables are consistently significant across all risk classes. The debt-to-income ratio, inquiries in the past 6 months and a loan intended for a small business are positively correlated with the default rate. Annual income and credit card as loan purpose are negatively correlated.

Suggested Citation

  • Michal Polena & Tobias Regner, 2016. "Determinants of borrowers' default in P2P lending under consideration of the loan risk class," Jena Economic Research Papers 2016-023, Friedrich-Schiller-University Jena.
  • Handle: RePEc:jrp:jrpwrp:2016-023
    as

    Download full text from publisher

    File URL: http://www2.wiwi.uni-jena.de/Papers/jerp2016/wp_2016_023.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Adam Nowak & Amanda Ross & Christopher Yencha, 2018. "Small Business Borrowing And Peer‐To‐Peer Lending: Evidence From Lending Club," Contemporary Economic Policy, Western Economic Association International, vol. 36(2), pages 318-336, April.
    2. Nataliya Barasinska & Dorothea Schäfer, 2014. "Is Crowdfunding Different? Evidence on the Relation between Gender and Funding Success from a German Peer-to-Peer Lending Platform," German Economic Review, Verein für Socialpolitik, vol. 15(4), pages 436-452, November.
    3. Herzenstein, Michal & Dholakia, Utpal M. & Andrews, Rick L., 2011. "Strategic Herding Behavior in Peer-to-Peer Loan Auctions," Journal of Interactive Marketing, Elsevier, vol. 25(1), pages 27-36.
    4. Freedman, Seth & Jin, Ginger Zhe, 2017. "The information value of online social networks: Lessons from peer-to-peer lending," International Journal of Industrial Organization, Elsevier, vol. 51(C), pages 185-222.
    5. Riza Emekter & Yanbin Tu & Benjamas Jirasakuldech & Min Lu, 2015. "Evaluating credit risk and loan performance in online Peer-to-Peer (P2P) lending," Applied Economics, Taylor & Francis Journals, vol. 47(1), pages 54-70, January.
    6. Mingfeng Lin & Nagpurnanand R. Prabhala & Siva Viswanathan, 2013. "Judging Borrowers by the Company They Keep: Friendship Networks and Information Asymmetry in Online Peer-to-Peer Lending," Management Science, INFORMS, vol. 59(1), pages 17-35, August.
    7. Khwaja, Asim Ijaz & Iyer, Rajkamal & Luttmer, Erzo F.P. & Shue, Kelly, 2009. "Screening in New Credit Markets: Can Individual Lenders Infer Borrower Creditworthiness in Peer-to-Peer Lending?," Scholarly Articles 4448882, Harvard Kennedy School of Government.
    8. Juanjuan Zhang & Peng Liu, 2012. "Rational Herding in Microloan Markets," Management Science, INFORMS, vol. 58(5), pages 892-912, May.
    9. Carlos Serrano-Cinca & Begoña Gutiérrez-Nieto & Luz López-Palacios, 2015. "Determinants of Default in P2P Lending," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-22, October.
    10. Karen Mills & Brayden McCarthy, 2014. "The State of Small Business Lending: Credit Access during the Recovery and How Technology May Change the Game," Harvard Business School Working Papers 15-004, Harvard Business School.
    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. Teply, Petr & Polena, Michal, 2020. "Best classification algorithms in peer-to-peer lending," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    2. Serena Gallo, 2021. "Fintech platforms: Lax or careful borrowers’ screening?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-33, December.
    3. Lu, Haitian & Wang, Bo & Wang, Haizhi & Zhao, Tianyu, 2020. "Does social capital matter for peer-to-peer-lending? Empirical evidence," Pacific-Basin Finance Journal, Elsevier, vol. 61(C).
    4. Ji-Yoon Kim & Sung-Bae Cho, 2019. "Towards Repayment Prediction in Peer-to-Peer Social Lending Using Deep Learning," Mathematics, MDPI, vol. 7(11), pages 1-17, November.
    5. 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).
    6. Marta Kłosok & Marcin Chlebus, 2020. "Towards better understanding of complex machine learning models using Explainable Artificial Intelligence (XAI) - case of Credit Scoring modelling," Working Papers 2020-18, Faculty of Economic Sciences, University of Warsaw.
    7. 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.
    8. Yan Wang & Xuelei Sherry Ni, 2020. "Improving Investment Suggestions for Peer-to-Peer (P2P) Lending via Integrating Credit Scoring into Profit Scoring," Papers 2009.04536, arXiv.org.

    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. Xueru Chen & Xiaoji Hu & Shenglin Ben, 2021. "How do reputation, structure design and FinTech ecosystem affect the net cash inflow of P2P lending platforms? Evidence from China," Electronic Commerce Research, Springer, vol. 21(4), pages 1055-1082, December.
    2. Xia, Yufei & Zhao, Junhao & He, Lingyun & Li, Yinguo & Yang, Xiaoli, 2021. "Forecasting loss given default for peer-to-peer loans via heterogeneous stacking ensemble approach," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1590-1613.
    3. Serena Gallo, 2021. "Fintech platforms: Lax or careful borrowers’ screening?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-33, December.
    4. Lu, Haitian & Wang, Bo & Wang, Haizhi & Zhao, Tianyu, 2020. "Does social capital matter for peer-to-peer-lending? Empirical evidence," Pacific-Basin Finance Journal, Elsevier, vol. 61(C).
    5. Gaigalienė Asta & Česnys Dovydas, 2018. "Determinants of Default in Lithuanian Peer-To-Peer Platforms," Management of Organizations: Systematic Research, Sciendo, vol. 80(1), pages 19-36, December.
    6. Andreas Hoegen & Dennis M. Steininger & Daniel Veit, 2018. "How do investors decide? An interdisciplinary review of decision-making in crowdfunding," Electronic Markets, Springer;IIM University of St. Gallen, vol. 28(3), pages 339-365, August.
    7. Pankaj Kumar Maskara & Emre Kuvvet & Gengxuan Chen, 2021. "The role of P2P platforms in enhancing financial inclusion in the United States: An analysis of peer‐to‐peer lending across the rural–urban divide," Financial Management, Financial Management Association International, vol. 50(3), pages 747-774, September.
    8. Teply, Petr & Polena, Michal, 2020. "Best classification algorithms in peer-to-peer lending," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    9. Wang, Qi & Xiong, Xiong & Zheng, Zunxin, 2021. "Platform Characteristics and Online Peer-to-Peer Lending: Evidence from China," Finance Research Letters, Elsevier, vol. 38(C).
    10. Eid, Nourhan & Maltby, Josephine & Talavera, Oleksandr, 2016. "Income Rounding and Loan Performance in the Peer-to-Peer Market," MPRA Paper 72852, University Library of Munich, Germany.
    11. 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.
    12. Wang, Congcong & Tong, Lin, 2020. "Lender rationality and trade-off behavior: Evidence from Lending Club and Renrendai," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 55-66.
    13. Adam Nowak & Amanda Ross & Christopher Yencha, 2018. "Small Business Borrowing And Peer‐To‐Peer Lending: Evidence From Lending Club," Contemporary Economic Policy, Western Economic Association International, vol. 36(2), pages 318-336, April.
    14. Yingxiu Zhao & Wei Zhang & Xiangyu Kong, 2019. "Dynamic Cross-Correlations between Participants’ Attentions to P2P Lending and Offline Loan in the Private Lending Market," Complexity, Hindawi, vol. 2019, pages 1-8, December.
    15. Qun Chen & Ji-Wen Li & Jian-Guo Liu & Jing-Ti Han & Yun Shi & Xun-Hua Guo, 2021. "Borrower Learning Effects: Do Prior Experiences Promote Continuous Successes in Peer-to-Peer Lending?," Information Systems Frontiers, Springer, vol. 23(4), pages 963-986, August.
    16. Qun Chen & Ji-Wen Li & Jian-Guo Liu & Jing-Ti Han & Yun Shi & Xun-Hua Guo, 0. "Borrower Learning Effects: Do Prior Experiences Promote Continuous Successes in Peer-to-Peer Lending?," Information Systems Frontiers, Springer, vol. 0, pages 1-24.
    17. Demir, Tolga & Mohammad, Ali & Shafi, Kourosh, 2019. "Crowdfunding as Gambling: Evidence from Repeated Natural Experiments," Working Paper Series in Economics and Institutions of Innovation 481, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies.
    18. 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.
    19. Mengyin Li & Phillip H. Phan & Xian Sun, 2021. "Business Friendliness: A Double-Edged Sword," Sustainability, MDPI, vol. 13(4), pages 1-22, February.
    20. Mingfeng Tang & Mei Mei & Cuiwen Li & Xingyang Lv & Xushuang Li & Lihao Wang, 2020. "How does an individual’s default behavior on an online peer-to-peer lending platform influence an observer’s default intention?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-20, December.

    More about this item

    Keywords

    crowdfunding; peer-to-peer lending; P2P; credit grade; FICO score; default risk;
    All these keywords.

    JEL classification:

    • D14 - Microeconomics - - Household Behavior - - - Household Saving; Personal Finance
    • E41 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Demand for Money
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:jrp:jrpwrp:2016-023. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: http://www.wiwiss.uni-jena.de/ .

    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: Markus Pasche (email available below). General contact details of provider: http://www.wiwiss.uni-jena.de/ .

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.