IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v212y2011i1p123-130.html
   My bibliography  Save this article

Modelling the profitability of credit cards by Markov decision processes

Author

Listed:
  • So, Meko M.C.
  • Thomas, Lyn C.

Abstract

This paper derives a Markov decision process model for the profitability of credit cards, which allows lenders to find an optimal dynamic credit limit policy. The states of the system are based on the borrower's behavioural score and the decisions are what credit limit to give the borrower each period. In determining which Markov chain best describes the borrower's performance, second order as well as first order Markov chains are considered and estimation procedures developed that deal with the low default levels that may exist in the data. A case study is given in which the optimal credit limit is derived and the results compared with the actual outcomes.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ejores:v:212:y:2011:i:1:p:123-130
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(11)00051-8
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. D. J. White, 1988. "Further Real Applications of Markov Decision Processes," Interfaces, INFORMS, vol. 18(5), pages 55-61, October.
    2. A Matuszyk & C Mues & L C Thomas, 2010. "Modelling LGD for unsecured personal loans: decision tree approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(3), pages 393-398, March.
    3. Dilip Soman & Amar Cheema, 2002. "The Effect of Credit on Spending Decisions: The Role of the Credit Limit and Credibility," Marketing Science, INFORMS, vol. 21(1), pages 32-53, September.
    4. 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.
    5. Yvo M. I. Dirickx & Lee Wakeman, 1976. "An Extension of the Bierman-Hausman Model for Credit Granting," Management Science, INFORMS, vol. 22(11), pages 1229-1237, July.
    6. Harold Bierman, Jr. & Warren H. Hausman, 1970. "The Credit Granting Decision," Management Science, INFORMS, vol. 16(8), pages 519-532, April.
    7. Margaret S. Trench & Shane P. Pederson & Edward T. Lau & Lizhi Ma & Hui Wang & Suresh K. Nair, 2003. "Managing Credit Lines and Prices for Bank One Credit Cards," Interfaces, INFORMS, vol. 33(5), pages 4-21, October.
    8. W-K Ching & M K Ng & K-K Wong & E Altman, 2004. "Customer lifetime value: stochastic optimization approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(8), pages 860-868, August.
    9. Douglas J. White, 1985. "Real Applications of Markov Decision Processes," Interfaces, INFORMS, vol. 15(6), pages 73-83, December.
    10. Halina Frydman & Jarl G. Kallberg & Duen-Li Kao, 1985. "Testing the Adequacy of Markov Chain and Mover-Stayer Models as Representations of Credit Behavior," Operations Research, INFORMS, vol. 33(6), pages 1203-1214, December.
    11. Thomas, Lyn C., 2009. "Consumer Credit Models: Pricing, Profit and Portfolios," OUP Catalogue, Oxford University Press, number 9780199232130, Decembrie.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. Dimitrov, Nedialko B. & Dimitrov, Stanko & Chukova, Stefanka, 2014. "Robust decomposable Markov decision processes motivated by allocating school budgets," European Journal of Operational Research, Elsevier, vol. 239(1), pages 199-213.
    3. Guo, Yanhong & Zhou, Wenjun & Luo, Chunyu & Liu, Chuanren & Xiong, Hui, 2016. "Instance-based credit risk assessment for investment decisions in P2P lending," European Journal of Operational Research, Elsevier, vol. 249(2), pages 417-426.
    4. Lessmann, Stefan & Baesens, Bart & Seow, Hsin-Vonn & Thomas, Lyn C., 2015. "Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research," European Journal of Operational Research, Elsevier, vol. 247(1), pages 124-136.
    5. van der Heijden, Hans & Garn, Wolfgang, 2013. "Profitability in the car industry: New measures for estimating targets and target directions," European Journal of Operational Research, Elsevier, vol. 225(3), pages 420-428.
    6. Özlem Çavuş & Andrzej Ruszczyński, 2014. "Computational Methods for Risk-Averse Undiscounted Transient Markov Models," Operations Research, INFORMS, vol. 62(2), pages 401-417, April.
    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Margaret S. Trench & Shane P. Pederson & Edward T. Lau & Lizhi Ma & Hui Wang & Suresh K. Nair, 2003. "Managing Credit Lines and Prices for Bank One Credit Cards," Interfaces, INFORMS, vol. 33(5), pages 4-21, October.
    3. Malik, Madhur & Thomas, Lyn C., 2012. "Transition matrix models of consumer credit ratings," International Journal of Forecasting, Elsevier, vol. 28(1), pages 261-272.
    4. Jonathan K. Budd & Peter G. Taylor, 2015. "Calculating optimal limits for transacting credit card customers," Papers 1506.05376, arXiv.org, revised Aug 2015.
    5. Ha-Thu Nguyen, 2014. "Default Predictors in Credit Scoring - Evidence from France’s Retail Banking Institution," EconomiX Working Papers 2014-26, University of Paris Nanterre, EconomiX.
    6. Victoria C. P. Chen & David Ruppert & Christine A. Shoemaker, 1999. "Applying Experimental Design and Regression Splines to High-Dimensional Continuous-State Stochastic Dynamic Programming," Operations Research, INFORMS, vol. 47(1), pages 38-53, February.
    7. Karl Waldmann, 1998. "On granting credit in a random environment," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 47(1), pages 99-115, February.
    8. Kao, Jih-Forg, 1995. "Optimal recovery strategies for manufacturing systems," European Journal of Operational Research, Elsevier, vol. 80(2), pages 252-263, January.
    9. Matuszyk, Anna & So, Mee Chi & Mues, Christophe & Moore, Angela, 2016. "Modelling repayment patterns in the collections process for unsecured consumer debt: A case studyAuthor-Name: Thomas, Lyn C," European Journal of Operational Research, Elsevier, vol. 249(2), pages 476-486.
    10. 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.
    11. Ha Thu Nguyen, 2014. "Default Predictors in Credit Scoring - Evidence from France’s Retail Banking Institution," Working Papers hal-04141336, HAL.
    12. Naveed Chehrazi & Peter W. Glynn & Thomas A. Weber, 2019. "Dynamic Credit-Collections Optimization," Management Science, INFORMS, vol. 67(6), pages 2737-2769, June.
    13. 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.
    14. 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.
    15. Chen, Victoria C. P., 1999. "Application of orthogonal arrays and MARS to inventory forecasting stochastic dynamic programs," Computational Statistics & Data Analysis, Elsevier, vol. 30(3), pages 317-341, May.
    16. Zong-Zhi Lin & James C. Bean & Chelsea C. White, 2004. "A Hybrid Genetic/Optimization Algorithm for Finite-Horizon, Partially Observed Markov Decision Processes," INFORMS Journal on Computing, INFORMS, vol. 16(1), pages 27-38, February.
    17. Epaminondas G. Kyriakidis & Theodosis D. Dimitrakos, 2005. "Computation of the Optimal Policy for the Control of a Compound Immigration Process through Total Catastrophes," Methodology and Computing in Applied Probability, Springer, vol. 7(1), pages 97-118, March.
    18. Fourgeaud Claude & Gourieroux Christian & Pradel Jacqueline, 1990. "Sélection de clientèle et tarification de prêt bancaire," CEPREMAP Working Papers (Couverture Orange) 9004, CEPREMAP.
    19. Jonathan Crook & Tony Bellotti, 2010. "Time varying and dynamic models for default risk in consumer loans," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(2), pages 283-305, April.
    20. Rolando Cavazos-Cadena & Mario Cantú-Sifuentes & Imelda Cerda-Delgado, 2021. "Nash equilibria in a class of Markov stopping games with total reward criterion," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 94(2), pages 319-340, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:212:y:2011:i:1:p:123-130. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.