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Time will tell: Behavioural Scoring and the Dynamics of Consumer Credit Assessment

Author

Listed:
  • Thomas, L.C.
  • Ho, J.
  • Scherer, W.T.

Abstract

This paper discusses the use of dynamic modelling in consumer credit risk assessment. It surveys the approaches and objectives of behavioural scoring, customer scoring and profit scoring. It then investigates how Markov chain stochastic processes can be used to model the dynamics of the delinquency status and behavioural scores of consumers.

Suggested Citation

  • Thomas, L.C. & Ho, J. & Scherer, W.T., 2001. "Time will tell: Behavioural Scoring and the Dynamics of Consumer Credit Assessment," Papers 01-174, University of Southampton - Department of Accounting and Management Science.
    • Handle: RePEc:fth:sotoam:01-174
    as

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    Citations

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    Cited by:

    1. G Verstraeten & D Van den Poel, 2005. "The impact of sample bias on consumer credit scoring performance and profitability," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(8), pages 981-992, August.
    2. Medina-Olivares, Victor & Calabrese, Raffaella & Crook, Jonathan & Lindgren, Finn, 2023. "Joint models for longitudinal and discrete survival data in credit scoring," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1457-1473.
    3. K Rajaratnam & P Beling & G Overstreet, 2010. "Scoring decisions in the context of economic uncertainty," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(3), pages 421-429, March.
    4. Kim, Hyeongjun & Cho, Hoon & Ryu, Doojin, 2018. "An empirical study on credit card loan delinquency," Economic Systems, Elsevier, vol. 42(3), pages 437-449.
    5. So, Meko M.C. & Thomas, Lyn C., 2011. "Modelling the profitability of credit cards by Markov decision processes," European Journal of Operational Research, Elsevier, vol. 212(1), pages 123-130, July.
    6. Finlay, Steven, 2011. "Multiple classifier architectures and their application to credit risk assessment," European Journal of Operational Research, Elsevier, vol. 210(2), pages 368-378, April.
    7. Bellotti, Tony & Crook, Jonathan, 2011. "Forecasting and Stress Testing Credit Card Default Using Dynamic Models," Working Papers 11-34, University of Pennsylvania, Wharton School, Weiss Center.
    8. Malik, Madhur & Thomas, Lyn C., 2012. "Transition matrix models of consumer credit ratings," International Journal of Forecasting, Elsevier, vol. 28(1), pages 261-272.
    9. Bellotti, Tony & Crook, Jonathan, 2013. "Forecasting and stress testing credit card default using dynamic models," International Journal of Forecasting, Elsevier, vol. 29(4), pages 563-574.
    10. Régis, Daniel E. & Artes, Rinaldo, 2008. "Modelo Multi-Estado de Markov em Cartões de Crédito," Insper Working Papers wpe_129, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    11. Gustavo Henrique Araujo Pereira & Rinaldo Artes, 2016. "A comparison of strategies to develop a customer default scoring model," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(11), pages 1341-1352, November.
    12. Finlay, Steven, 2010. "Credit scoring for profitability objectives," European Journal of Operational Research, Elsevier, vol. 202(2), pages 528-537, April.
    13. Chrysovalantis Gaganis & Panagiota Papadimitri & Fotios Pasiouras & Menelaos Tasiou, 2023. "Social traits and credit card default: a two-stage prediction framework," Annals of Operations Research, Springer, vol. 325(2), pages 1231-1253, June.

    More about this item

    Keywords

    RISK ; CONSUMERS ; CREDIT;
    All these keywords.

    JEL classification:

    • C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods
    • D11 - Microeconomics - - Household Behavior - - - Consumer Economics: Theory

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