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Managing Consumer Credit Delinquency in the US Economy: A Multi-Billion Dollar Management Science Application

Author

Listed:
  • William M. Makuch

    (Corporate Research and Development, General Electric Company, Schenectady, New York 12301)

  • Jeffrey L. Dodge

    (General Electric Capital, 1600 Summer Street, Stamford, Connecticut 06905)

  • Joseph G. Ecker

    (Rensselaer Polytechnic Institute, Troy, New York 12180)

  • Donna C. Granfors

    (General Electric Capital, 1221 Post Road East, West Port, Connecticut 06880)

  • Gerald J. Hahn

    (Corporate Research and Development, General Electric Company, Schenectady, New York 12301)

Abstract

GE Capital provides credit card services for a consumer credit business exceeding $12 billion in total outstanding dollars. Its objective is to optimally manage delinquency by improving the allocation of limited collection resources to maximize net collections over multiple billing periods. We developed a probabilistic account flow model and statistically designed programs to provide accurate data on collection resource performance. A linear programming formulation produces optimal resource allocations that have been implemented across the business. The PAYMENT system has permanently changed the way GE Capital manages delinquent consumer credit, reduced annual losses by approximately $37 million, and improved customer goodwill.

Suggested Citation

  • William M. Makuch & Jeffrey L. Dodge & Joseph G. Ecker & Donna C. Granfors & Gerald J. Hahn, 1992. "Managing Consumer Credit Delinquency in the US Economy: A Multi-Billion Dollar Management Science Application," Interfaces, INFORMS, vol. 22(1), pages 90-109, February.
    • Handle: RePEc:inm:orinte:v:22:y:1992:i:1:p:90-109
    DOI: 10.1287/inte.22.1.90
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    Citations

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    Cited by:

    1. Peter C. Bell & Chris K. Anderson, 2002. "In Search of Strategic Operations Research/Management Science," Interfaces, INFORMS, vol. 32(2), pages 28-40, April.
    2. Zhixin Liu & Ping He & Bo Chen, 2019. "A Markov decision model for consumer term-loan collections," Review of Quantitative Finance and Accounting, Springer, vol. 52(4), pages 1043-1064, May.
    3. Lukasz A. Drozd & Ricardo Serrano-Padial, 2017. "Modeling the Revolving Revolution: The Debt Collection Channel," American Economic Review, American Economic Association, vol. 107(3), pages 897-930, March.
    4. Thomas, L.C. & Matuszyk, A. & Moore, A., 2012. "Comparing debt characteristics and LGD models for different collections policies," International Journal of Forecasting, Elsevier, vol. 28(1), pages 196-203.
    5. Gerard Miller & Melissa Weatherwax & Timothy Gardinier & Naoki Abe & Prem Melville & Cezar Pendus & David Jensen & Chandan K. Reddy & Vince Thomas & James Bennett & Gary Anderson & Brent Cooley, 2012. "Tax Collections Optimization for New York State," Interfaces, INFORMS, vol. 42(1), pages 74-84, February.
    6. Peter C. Bell & Chris K. Anderson & Stephen P. Kaiser, 2003. "Strategic Operations Research and the Edelman Prize Finalist Applications 1989--1998," Operations Research, INFORMS, vol. 51(1), pages 17-31, February.
    7. Johannes Kriebel & Kevin Yam, 2020. "Forecasting recoveries in debt collection: Debt collectors and information production," European Financial Management, European Financial Management Association, vol. 26(3), pages 537-559, June.

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