IDEAS home Printed from https://ideas.repec.org/a/eee/beexfi/v32y2021ics2214635021001222.html
   My bibliography  Save this article

Profit-based credit models with lender’s attitude towards risk and loss

Author

Listed:
  • Baidoo, Edwin
  • Natarajan, Ramachandran

Abstract

Profit scoring represents a shift from default risk modeling. Here, lenders align their lending strategies to reflect their profitability objective. This paper proposes models that address the lender’s profit maximization objective. We develop varying cutoff functions that inform lending decisions while considering a lender’s attitude towards risk and loss. We derive two propositions about the properties of the variable cutoff functions for risk-averse and loss-averse lenders. Using a proprietary consumer loan data set, we show the effect of cutoff functions in lending decisions and find that both risk-averse and loss-averse lenders are profitable if they use parameter estimators that support their profitability objective.

Suggested Citation

  • Baidoo, Edwin & Natarajan, Ramachandran, 2021. "Profit-based credit models with lender’s attitude towards risk and loss," Journal of Behavioral and Experimental Finance, Elsevier, vol. 32(C).
    • Handle: RePEc:eee:beexfi:v:32:y:2021:i:c:s2214635021001222
    DOI: 10.1016/j.jbef.2021.100578
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S2214635021001222
    Download Restriction: no
    File URL: https://libkey.io/10.1016/j.jbef.2021.100578?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
    ---><---

    References listed on IDEAS

    as
    1. Verbraken, Thomas & Bravo, Cristián & Weber, Richard & Baesens, Bart, 2014. "Development and application of consumer credit scoring models using profit-based classification measures," European Journal of Operational Research, Elsevier, vol. 238(2), pages 505-513.
    2. William Adams & Liran Einav & Jonathan Levin, 2009. "Liquidity Constraints and Imperfect Information in Subprime Lending," American Economic Review, American Economic Association, vol. 99(1), pages 49-84, March.
    3. Dirk Brounen & Abe de Jong & Kees Koedijk, 2004. "Corporate Finance in Europe: Confronting Theory with Practice," Financial Management, Financial Management Association, vol. 33(4), Winter.
    4. Michael S. Haigh & John A. List, 2005. "Do Professional Traders Exhibit Myopic Loss Aversion? An Experimental Analysis," Journal of Finance, American Finance Association, vol. 60(1), pages 523-534, February.
    5. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    6. David Genesove & Christopher Mayer, 2001. "Loss Aversion and Seller Behavior: Evidence from the Housing Market," The Quarterly Journal of Economics, Oxford University Press, vol. 116(4), pages 1233-1260.
    7. Elliott, Graham & Lieli, Robert P., 2013. "Predicting binary outcomes," Journal of Econometrics, Elsevier, vol. 174(1), pages 15-26.
    8. Binswanger, Hans P, 1981. "Attitudes toward Risk: Theoretical Implications of an Experiment in Rural India," Economic Journal, Royal Economic Society, vol. 91(364), pages 867-890, December.
    9. Khandani, Amir E. & Kim, Adlar J. & Lo, Andrew W., 2010. "Consumer credit-risk models via machine-learning algorithms," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2767-2787, November.
    10. Luis Javier Sánchez Barrios & Galina Andreeva & Jake Ansell, 2014. "Monetary and relative scorecards to assess profits in consumer revolving credit," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(3), pages 443-453, March.
    11. Charles A. Holt & Susan K. Laury, 2002. "Risk Aversion and Incentive Effects," American Economic Review, American Economic Association, vol. 92(5), pages 1644-1655, December.
    12. Zanin, Luca, 2020. "Combining multiple probability predictions in the presence of class imbalance to discriminate between potential bad and good borrowers in the peer-to-peer lending market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 25(C).
    13. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    14. Levy, Haim, 1994. "Absolute and Relative Risk Aversion: An Experimental Study," Journal of Risk and Uncertainty, Springer, vol. 8(3), pages 289-307, May.
    15. S M Finlay, 2008. "Towards profitability: a utility approach to the credit scoring problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(7), pages 921-931, July.
    16. Lieli, Robert P. & White, Halbert, 2010. "The construction of empirical credit scoring rules based on maximization principles," Journal of Econometrics, Elsevier, vol. 157(1), pages 110-119, July.
    17. Pasqual, Joan & Padilla, Emilio & Jadotte, Evans, 2013. "Technical note: Equivalence of different profitability criteria with the net present value," International Journal of Production Economics, Elsevier, vol. 142(1), pages 205-210.
    18. Maria Stepanova & Lyn Thomas, 2002. "Survival Analysis Methods for Personal Loan Data," Operations Research, INFORMS, vol. 50(2), pages 277-289, April.
    19. Lessmann, Stefan & Baesens, Bart & Seow, Hsin-Vonn & Thomas, Lyn C., 2015. "Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research," European Journal of Operational Research, Elsevier, vol. 247(1), pages 124-136.
    20. Brounen, D. & de Jong, A. & Koedijk, C.G., 2004. "Corporate Finance In Europe Confronting Theory With Practice," ERIM Report Series Research in Management ERS-2004-002-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    21. R T Stewart, 2011. "A profit-based scoring system in consumer credit: making acquisition decisions for credit cards," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(9), pages 1719-1725, September.
    22. Kachelmeier, Steven J & Shehata, Mohamed, 1992. "Examining Risk Preferences under High Monetary Incentives: Experimental Evidence from the People's Republic of China," American Economic Review, American Economic Association, vol. 82(5), pages 1120-1141, December.
    23. 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.
    Full references (including those not matched with items on IDEAS)

    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. Stefano DellaVigna, 2009. "Psychology and Economics: Evidence from the Field," Journal of Economic Literature, American Economic Association, vol. 47(2), pages 315-372, June.
    2. Patrick DeJarnette & David Dillenberger & Daniel Gottlieb & Pietro Ortoleva, 2020. "Time Lotteries and Stochastic Impatience," Econometrica, Econometric Society, vol. 88(2), pages 619-656, March.
    3. Galarza, Francisco, 2009. "Choices under Risk in Rural Peru," MPRA Paper 17708, University Library of Munich, Germany.
    4. Georgalos, Konstantinos & Paya, Ivan & Peel, David A., 2021. "On the contribution of the Markowitz model of utility to explain risky choice in experimental research," Journal of Economic Behavior & Organization, Elsevier, vol. 182(C), pages 527-543.
    5. Simon Gächter & Eric J. Johnson & Andreas Herrmann, 2022. "Individual-level loss aversion in riskless and risky choices," Theory and Decision, Springer, vol. 92(3), pages 599-624, April.
    6. James Cox & Vjollca Sadiraj & Ulrich Schmidt, 2015. "Paradoxes and mechanisms for choice under risk," Experimental Economics, Springer;Economic Science Association, vol. 18(2), pages 215-250, June.
    7. Jakusch, Sven Thorsten, 2017. "On the applicability of maximum likelihood methods: From experimental to financial data," SAFE Working Paper Series 148, Leibniz Institute for Financial Research SAFE, revised 2017.
    8. Kaveh Bastani & Elham Asgari & Hamed Namavari, 2018. "Wide and Deep Learning for Peer-to-Peer Lending," Papers 1810.03466, arXiv.org, revised Oct 2018.
    9. Gächter, Simon & Johnson, Eric J. & Herrmann, Andreas, 2007. "Individual-Level Loss Aversion in Riskless and Risky Choices," IZA Discussion Papers 2961, Institute of Labor Economics (IZA).
    10. Veld, Chris & Veld-Merkoulova, Yulia V., 2008. "The risk perceptions of individual investors," Journal of Economic Psychology, Elsevier, vol. 29(2), pages 226-252, April.
    11. D. A. Peel & Jie Zhang & D. Law, 2008. "The Markowitz model of utility supplemented with a small degree of probability distortion as an explanation of outcomes of Allais experiments over large and small payoffs and gambling on unlikely outc," Applied Economics, Taylor & Francis Journals, vol. 40(1), pages 17-26.
    12. Bouchouicha, Ranoua & Martinsson, Peter & Medhin, Haileselassie & Vieider, Ferdinand M., 2017. "Stake effects on ambiguity attitudes for gains and losses," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 83(1), pages 19-35.
    13. Tamás Csermely & Alexander Rabas, 2016. "How to reveal people’s preferences: Comparing time consistency and predictive power of multiple price list risk elicitation methods," Journal of Risk and Uncertainty, Springer, vol. 53(2), pages 107-136, December.
    14. Holden , Stein, 2014. "Risky Choices of Poor People: Comparing Risk Preference Elicitation Approaches in Field Experiments," CLTS Working Papers 10/14, Norwegian University of Life Sciences, Centre for Land Tenure Studies, revised 10 Oct 2019.
    15. Peter Wakker & Veronika Köbberling & Christiane Schwieren, 2007. "Prospect-theory’s Diminishing Sensitivity Versus Economics’ Intrinsic Utility of Money: How the Introduction of the Euro can be Used to Disentangle the Two Empirically," Theory and Decision, Springer, vol. 63(3), pages 205-231, November.
    16. Charness, Gary & Gneezy, Uri & Imas, Alex, 2013. "Experimental methods: Eliciting risk preferences," Journal of Economic Behavior & Organization, Elsevier, vol. 87(C), pages 43-51.
    17. Brice Corgnet & Roberto Hernán González, 2023. "On The Appeal Of Complexity," Working Papers 2312, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    18. Julius Pahlke & Sebastian Strasser & Ferdinand Vieider, 2015. "Responsibility effects in decision making under risk," Journal of Risk and Uncertainty, Springer, vol. 51(2), pages 125-146, October.
    19. Ferdinand M. Vieider & Peter Martinsson & Pham Khanh Nam & Nghi Truong, 2019. "Risk preferences and development revisited," Theory and Decision, Springer, vol. 86(1), pages 1-21, February.
    20. Weber, Martin & Welfens, Frank, 2007. "How do markets react to fundamental shocks? : An experimental analysis on underreaction and momentum," Papers 07-42, Sonderforschungsbreich 504.

    More about this item

    Keywords

    Credit scoring; Profit scoring; Risk-aversion; Loss-aversion; Prospect theory; Cumulative prospect theory;
    All these keywords.

    JEL classification:

    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • G51 - Financial Economics - - Household Finance - - - Household Savings, Borrowing, Debt, and Wealth

    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:eee:beexfi:v:32:y:2021:i:c:s2214635021001222. 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: https://www.journals.elsevier.com/journal-of-behavioral-and-experimental-finance .

    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.