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A Markov Decision Model for Selecting Optimal Credit Control Policies


  • Leon H. Liebman

    (University of Pennsylvania)


The rapid growth of consumer credit has created a need for improved credit control policies which result in lower total credit costs. This paper investigates one approach for achieving that objective. The credit control problem is formulated as one of developing optimal policies for an infinite horizon Markov decision model. The model utilizes standard financial data; it also requires the measurement of the costs and returns from alternative credit control policies. The Markov model is transformed into an equivalent linear program. A sample problem is solved and the resulting policies analyzed.

Suggested Citation

  • Leon H. Liebman, 1972. "A Markov Decision Model for Selecting Optimal Credit Control Policies," Management Science, INFORMS, vol. 18(10), pages 519-525, June.
  • Handle: RePEc:inm:ormnsc:v:18:y:1972:i:10:p:b519-b525

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    References listed on IDEAS

    1. M. E. Salveson, 1956. "A Problem in Optimal Machine Loading," Management Science, INFORMS, vol. 2(3), pages 232-260, April.
    2. M. Beckman & R. Muth, 1956. "An Inventory Policy for a Case of Lagged Delivery," Management Science, INFORMS, vol. 2(2), pages 145-155, January.
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    Cited by:

    1. Robert Till & David Hand, 2003. "Behavioural models of credit card usage," Journal of Applied Statistics, Taylor & Francis Journals, vol. 30(10), pages 1201-1220.
    2. 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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