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Kelly Criterion for Optimal Credit Allocation

Author

Listed:
  • Son Tran

    (Faculty of Science and Engineering, Queensland University of Technology, Brisbane, QLD 4000, Australia)

  • Peter Verhoeven

    (Faculty of Law and Business, Queensland University of Technology, Brisbane, QLD 4000, Australia)

Abstract

The purpose of this study is to address the critical issue of optimal credit allocation. Predicting a borrower’s probability of default is a key requirement of any credit allocation system but turning it into labeled classes leads to problems in performance measurement. In this paper the connection between the probability of default and optimal credit allocation is established through a conceptual construct called the Kelly criterion. Conflicting performance measures in dichotomous classification are replaced with coherent criteria for judging the performance of credit allocation decisions. Extensive testing on peer-to-peer lending data shows that the Kelly strategy enables consistent outperformance and efficiency in processing information relative to alternative credit allocation approaches.

Suggested Citation

  • Son Tran & Peter Verhoeven, 2021. "Kelly Criterion for Optimal Credit Allocation," JRFM, MDPI, vol. 14(9), pages 1-16, September.
    • Handle: RePEc:gam:jjrfmx:v:14:y:2021:i:9:p:434-:d:631915
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    References listed on IDEAS

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    3. Kaposty, Florian & Kriebel, Johannes & Löderbusch, Matthias, 2020. "Predicting loss given default in leasing: A closer look at models and variable selection," International Journal of Forecasting, Elsevier, vol. 36(2), pages 248-266.
    4. 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.
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    6. Willem Daniel Schutte & Tanja Verster & Derek Doody & Helgard Raubenheimer & Peet Jacobus Coetzee & David McMillan, 2020. "A proposed benchmark model using a modularised approach to calculate IFRS 9 expected credit loss," Cogent Economics & Finance, Taylor & Francis Journals, vol. 8(1), pages 1735681-173, January.
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    Keywords

    credit allocation; Kelly criterion;

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