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The construction of empirical credit scoring rules based on maximization principles

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  • Lieli, Robert P.
  • White, Halbert

Abstract

We examine the econometric implications of the decision problem faced by a profit/utility-maximizing lender operating in a simple "double-binary" environment, where the two actions available are "approve" or "reject", and the two states of the world are "pay back" or "default". In practice, such decisions are often made by applying a fixed cutoff to the maximum likelihood estimate of a parametric model of the default probability. Following (Elliott and Lieli, 2007), we argue that this practice might contradict the lender's economic objective and, using German loan data, we illustrate the use of "context-specific" cutoffs and an estimation method derived directly from the lender's problem. We also provide a brief discussion of how to incorporate legal constraints, such as the prohibition of disparate treatment of potential borrowers, into the lender's problem.

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  • 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.
    • Handle: RePEc:eee:econom:v:157:y:2010:i:1:p:110-119
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    References listed on IDEAS

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    Cited by:

    1. Toru Kitagawa & Aleksey Tetenov, 2018. "Who Should Be Treated? Empirical Welfare Maximization Methods for Treatment Choice," Econometrica, Econometric Society, vol. 86(2), pages 591-616, March.
    2. Chen, Le-Yu & Lee, Sokbae, 2018. "Best subset binary prediction," Journal of Econometrics, Elsevier, vol. 206(1), pages 39-56.
    3. Robert P. Lieli & Yu-Chin Hsu, 2019. "Using the area under an estimated ROC curve to test the adequacy of binary predictors," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 31(1), pages 100-130, January.
    4. Toru Kitagawa & Shosei Sakaguchi & Aleksey Tetenov, 2021. "Constrained Classification and Policy Learning," Papers 2106.12886, arXiv.org, revised Jul 2023.
    5. Rafał Balina & Marta Idasz-Balina, 2021. "Drivers of Individual Credit Risk of Retail Customers—A Case Study on the Example of the Polish Cooperative Banking Sector," Risks, MDPI, vol. 9(12), pages 1-26, December.
    6. Toru Kitagawa & Aleksey Tetenov, 2015. "Who should be treated? Empirical welfare maximization methods for treatment choice," CeMMAP working papers 10/15, Institute for Fiscal Studies.
    7. Halbert White & Karim Chalak, 2008. "Identifying Structural Effects in Nonseparable Systems Using Covariates," Boston College Working Papers in Economics 734, Boston College Department of Economics.
    8. Maria Patricia Durango‐Gutiérrez & Juan Lara‐Rubio & Andrés Navarro‐Galera, 2023. "Analysis of default risk in microfinance institutions under the Basel III framework," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 1261-1278, April.
    9. 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).

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