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Behavioural models of credit card usage

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  • Robert Till
  • David Hand

Abstract

Behavioural models characterize the way customers behave in their use of a credit product. In this paper, we examine repayment and transaction behaviour with credit cards. In particular, we describe the development of Markov chain models for late repayment, investigate the extent to which there are different classes of behaviour pattern, and explore the extent to which distinct behaviours can be predicted. We also develop overall models for transaction time distributions. Once such models have been built to summarize the data, they can be used to predict likely future behaviour, and can also serve as the basis of predictions of what one might expect when economic circumstances change.

Suggested Citation

  • Robert Till & David Hand, 2003. "Behavioural models of credit card usage," Journal of Applied Statistics, Taylor & Francis Journals, vol. 30(10), pages 1201-1220.
    • Handle: RePEc:taf:japsta:v:30:y:2003:i:10:p:1201-1220
    DOI: 10.1080/0266476032000107196
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    References listed on IDEAS

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    Cited by:

    1. Jonathan K. Budd & Peter G. Taylor, 2015. "Calculating optimal limits for transacting credit card customers," Papers 1506.05376, arXiv.org, revised Aug 2015.
    2. Thomas, Lyn C., 2009. "Modelling the credit risk for portfolios of consumer loans: Analogies with corporate loan models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2525-2534.
    3. Maha Bakoben & Tony Bellotti & Niall Adams, 2017. "Identification of Credit Risk Based on Cluster Analysis of Account Behaviours," Papers 1706.07466, arXiv.org.
    4. 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.

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