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Towards profitability: a utility approach to the credit scoring problem

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  • S M Finlay

    (Lancaster University)

Abstract

Since credit scoring was first applied in the 1940s the standard methodology has been to treat consumer lending decisions as binary classification problems, where the goal has been to make the best possible ‘good/bad’ classification of accounts on the basis of their eventual delinquency status. However, the real goal of commercial lending organizations is to forecast continuous financial measures such as contribution to profit, but there has been little research in this area. In this paper, continuous models of customer worth are compared to binary models of customer repayment behaviour. Empirical results show that while models of customer worth do not perform well in terms of classifying accounts by their good/bad status, they significantly outperform standard classification methodologies when ranking accounts based on their financial worth to lenders.

Suggested Citation

  • 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.
    • Handle: RePEc:pal:jorsoc:v:59:y:2008:i:7:d:10.1057_palgrave.jors.2602394
    DOI: 10.1057/palgrave.jors.2602394
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    References listed on IDEAS

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    Cited by:

    1. R Fildes & K Nikolopoulos & S F Crone & A A Syntetos, 2008. "Forecasting and operational research: a review," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(9), pages 1150-1172, September.
    2. Krivorotov, George, 2023. "Machine learning-based profit modeling for credit card underwriting - implications for credit risk," Journal of Banking & Finance, Elsevier, vol. 149(C).
    3. Kaveh Bastani & Elham Asgari & Hamed Namavari, 2018. "Wide and Deep Learning for Peer-to-Peer Lending," Papers 1810.03466, arXiv.org, revised Oct 2018.
    4. Samuel Ribeiro-Navarrete & Juan Piñeiro-Chousa & M. Ángeles López-Cabarcos & Daniel Palacios-Marqués, 2022. "Crowdlending: mapping the core literature and research frontiers," Review of Managerial Science, Springer, vol. 16(8), pages 2381-2411, November.
    5. Sanchez-Barrios, Luis Javier & Andreeva, Galina & Ansell, Jake, 2016. "“Time-to-profit scorecards for revolving credit”," European Journal of Operational Research, Elsevier, vol. 249(2), pages 397-406.
    6. Finlay, Steven, 2010. "Credit scoring for profitability objectives," European Journal of Operational Research, Elsevier, vol. 202(2), pages 528-537, April.
    7. 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.
    8. Selcuk Bayraci, 2017. "Application of profit-based credit scoring models using R," Romanian Statistical Review, Romanian Statistical Review, vol. 65(4), pages 3-28, December.
    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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