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An Operations-Research Study of the Collection of Defaulted Loans

Author

Listed:
  • Morton Mitchner

    (Arthur D. Little, Inc., San Francisco, California)

  • Raymond P. Peterson

    (Operations Research Section, Controllers Department, Bank of America Headquarters, San Francisco, California)

Abstract

Statistical decision techniques are developed for loan screening that provide a guide as to how long nonpaying defaulted loans of various types should be pursued by adjusters or collectors before they are completely dropped as uncollectible. A mathematical model yields the optimum pursuit duration and maximum expected net profit for each type of delinquent loan considered and which, if followed, will maximize the over-all net profit of a loan adjustment or collection department. The application of these rules by simulation to a random sample of defaulted loans indicates a potential increase in net profit of approximately 33 per cent.

Suggested Citation

  • Morton Mitchner & Raymond P. Peterson, 1957. "An Operations-Research Study of the Collection of Defaulted Loans," Operations Research, INFORMS, vol. 5(4), pages 522-545, August.
    • Handle: RePEc:inm:oropre:v:5:y:1957:i:4:p:522-545
    DOI: 10.1287/opre.5.4.522
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    Cited by:

    1. Nazemi, Abdolreza & Rezazadeh, Hani & Fabozzi, Frank J. & Höchstötter, Markus, 2022. "Deep learning for modeling the collection rate for third-party buyers," International Journal of Forecasting, Elsevier, vol. 38(1), pages 240-252.
    2. Naveed Chehrazi & Thomas A. Weber, 2015. "Dynamic Valuation of Delinquent Credit-Card Accounts," Management Science, INFORMS, vol. 61(12), pages 3077-3096, December.
    3. Shoghi , Amirhossein, 2019. "Debt Collection Industry: Machine Learning Approach," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 14(4), pages 453-473, October.
    4. Arno Botha & Conrad Beyers & Pieter de Villiers, 2020. "Simulation-based optimisation of the timing of loan recovery across different portfolios," Papers 2009.11064, arXiv.org, revised Apr 2021.
    5. Arno Botha & Conrad Beyers & Pieter de Villiers, 2020. "The loss optimisation of loan recovery decision times using forecast cash flows," Papers 2010.05601, arXiv.org.
    6. Naveed Chehrazi & Peter W. Glynn & Thomas A. Weber, 2019. "Dynamic Credit-Collections Optimization," Management Science, INFORMS, vol. 67(6), pages 2737-2769, June.
    7. He, Ping & Hua, Zhongsheng & Liu, Zhixin, 2015. "A quantification method for the collection effect on consumer term loans," Journal of Banking & Finance, Elsevier, vol. 57(C), pages 17-26.

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