IDEAS home Printed from https://ideas.repec.org/a/inm/orinte/v33y2003i5p4-21.html
   My bibliography  Save this article

Managing Credit Lines and Prices for Bank One Credit Cards

Author

Listed:
  • Margaret S. Trench

    (Bank One Card Services, Inc., 3 Christina Centre, Wilmington, Delaware 19801)

  • Shane P. Pederson

    (Bank One Card Services, Inc., 2500 Westfield Drive, Elgin, Illinois 60123)

  • Edward T. Lau

    (Bank One Card Services, Inc., 3 Christina Centre, Wilmington, Delaware 19801)

  • Lizhi Ma

    (Bank One Card Services, Inc., 3 Christina Centre, Wilmington, Delaware 19801)

  • Hui Wang

    (Bank One Card Services, Inc., 3 Christina Centre, Wilmington, Delaware 19801)

  • Suresh K. Nair

    (School of Business, University of Connecticut, Storrs, Connecticut 06269)

Abstract

We developed a method for managing the characteristics of a bank's card holder portfolio in an optimal manner. The annual percentage rate (APR) and credit line of an account influence card use and bank profitability. Consumers find low APRs and high credit lines attractive. However, low APRs may reduce bank profitability, while indiscriminate increases in credit lines increase the bank's exposure to credit loss. We designed the PORTICO (portfolio control and optimization) system using Markov decision processes (MDP) to select price points and credit lines for each card holder that maximize net present value (NPV) for the portfolio. PORTICO uses account-level historical information on purchases, payments, profitability, and delinquency risk to determine pricing and credit-line changes. In competitive benchmark tests over more than a year, the PORTICO model outperforms the bank's current method and may increase annual profits by over $75 million.

Suggested Citation

  • 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.
    • Handle: RePEc:inm:orinte:v:33:y:2003:i:5:p:4-21
    DOI: 10.1287/inte.33.5.4.19245
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/inte.33.5.4.19245
    Download Restriction: no
    File URL: https://libkey.io/10.1287/inte.33.5.4.19245?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Eric Rosenberg & Alan Gleit, 1994. "Quantitative Methods in Credit Management: A Survey," Operations Research, INFORMS, vol. 42(4), pages 589-613, August.
    2. 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.
    3. Suresh K. Nair, 1995. "Modeling Strategic Investment Decisions Under Sequential Technological Change," Management Science, INFORMS, vol. 41(2), pages 282-297, February.
    4. 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.
    5. Harold Bierman, Jr. & Warren H. Hausman, 1970. "The Credit Granting Decision," Management Science, INFORMS, vol. 16(8), pages 519-532, April.
    6. Suresh K. Nair & Ravi Bapna, 2001. "An application of yield management for Internet Service Providers," Naval Research Logistics (NRL), John Wiley & Sons, vol. 48(5), pages 348-362, August.
    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. Conor B. Hamill & Raad Khraishi & Simona Gherghel & Jerrard Lawrence & Salvatore Mercuri & Ramin Okhrati & Greig A. Cowan, 2023. "Agent-based Modelling of Credit Card Promotions," Papers 2311.01901, arXiv.org, revised Nov 2023.
    2. Mohammad G Nejad & Sertan Kabadayi, 2016. "Optimal introductory pricing for new financial services," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 21(1), pages 34-50, March.
    3. Suting Hong & Robert M. Hunt & Konstantinos Serfes, 2023. "Dynamic Pricing of Credit Cards and the Effects of Regulation," Journal of Financial Services Research, Springer;Western Finance Association, vol. 64(1), pages 81-131, August.
    4. Ramasubramanian Sundararajan & Tarun Bhaskar & Abhinanda Sarkar & Sridhar Dasaratha & Debasis Bal & Jayanth K. Marasanapalle & Beata Zmudzka & Karolina Bak, 2011. "Marketing Optimization in Retail Banking," Interfaces, INFORMS, vol. 41(5), pages 485-505, October.
    5. Malik, Madhur & Thomas, Lyn C., 2012. "Transition matrix models of consumer credit ratings," International Journal of Forecasting, Elsevier, vol. 28(1), pages 261-272.
    6. Jason R. W. Merrick & Jill R. Hardin & Russell Walker, 2006. "Partnerships in Training," Interfaces, INFORMS, vol. 36(4), pages 359-370, August.
    7. Lapshin, Viktor & Anton, Markov, 2022. "MCMC-based credit rating aggregation algorithm to tackle data insufficiency," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 68, pages 50-72.
    8. 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.
    9. 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.
    10. 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.
    11. Crook, Jonathan N. & Edelman, David B. & Thomas, Lyn C., 2007. "Recent developments in consumer credit risk assessment," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1447-1465, December.
    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. Raad Khraishi & Ramin Okhrati, 2022. "Offline Deep Reinforcement Learning for Dynamic Pricing of Consumer Credit," Papers 2203.03003, arXiv.org.
    14. 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. Jonathan K. Budd & Peter G. Taylor, 2015. "Calculating optimal limits for transacting credit card customers," Papers 1506.05376, arXiv.org, revised Aug 2015.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Naveed Chehrazi & Thomas A. Weber, 2015. "Dynamic Valuation of Delinquent Credit-Card Accounts," Management Science, INFORMS, vol. 61(12), pages 3077-3096, December.
    7. Seifert, Daniel & Seifert, Ralf W. & Protopappa-Sieke, Margarita, 2013. "A review of trade credit literature: Opportunities for research in operations," European Journal of Operational Research, Elsevier, vol. 231(2), pages 245-256.
    8. Ha Thu Nguyen, 2014. "Default Predictors in Credit Scoring - Evidence from France’s Retail Banking Institution," Working Papers hal-04141336, HAL.
    9. Naveed Chehrazi & Peter W. Glynn & Thomas A. Weber, 2019. "Dynamic Credit-Collections Optimization," Management Science, INFORMS, vol. 67(6), pages 2737-2769, June.
    10. Li Gan & Roberto Mosquera, 2008. "An Empirical Study of the Credit Market with Unobserved Consumer Typers," NBER Working Papers 13873, National Bureau of Economic Research, Inc.
    11. Fourgeaud Claude & Gourieroux Christian & Pradel Jacqueline, 1990. "Sélection de clientèle et tarification de prêt bancaire," CEPREMAP Working Papers (Couverture Orange) 9004, CEPREMAP.
    12. Thomas, Lyn C., 2000. "A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers," International Journal of Forecasting, Elsevier, vol. 16(2), pages 149-172.
    13. Hang Miao & Kui Zhao & Zhun Wang & Linbo Jiang & Quanhui Jia & Yanming Fang & Quan Yu, 2020. "Intelligent Credit Limit Management in Consumer Loans Based on Causal Inference," Papers 2007.05188, arXiv.org.
    14. Xinhua Gu & Yang Zhang & Xiao Chang, 2017. "The role of financial systems for cross-country differences in the link between income and consumption inequality," Applied Economics, Taylor & Francis Journals, vol. 49(24), pages 2365-2378, May.
    15. Till Treeck, 2014. "Did Inequality Cause The U.S. Financial Crisis?," Journal of Economic Surveys, Wiley Blackwell, vol. 28(3), pages 421-448, July.
    16. Thomas Wainwright, 2011. "Elite Knowledges: Framing Risk and the Geographies of Credit," Environment and Planning A, , vol. 43(3), pages 650-665, March.
    17. Irene Ng & Nick K.T. Yip, 2009. "Mechanism design in an integrated approach towards revenue management: the case of Empress Cruise Lines," The Service Industries Journal, Taylor & Francis Journals, vol. 31(3), pages 469-482, February.
    18. Nenita B. Nagarit, DBA & Susana C. Bautista, EdD & Ferdinand C. Somido, PhD & Pedrito Jose V. Bermudo, PhD & Antonio D.Yango, PhD & Leomar S. Galicia, PhD, 2018. "Transforming Online Negative Blogs in the Use of Credit Cards in Electronics Transactions into Constructive Action: Basis of Creating Business Spend Analyzer Model," Journal of Business & Management (COES&RJ-JBM), , vol. 6(1), pages 66-83, January.
    19. Asadi, Amin & Nurre Pinkley, Sarah, 2021. "A stochastic scheduling, allocation, and inventory replenishment problem for battery swap stations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 146(C).
    20. Robert B. Avery & Kenneth P. Brevoort & Glenn Canner, 2012. "Does Credit Scoring Produce a Disparate Impact?," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 40, pages 65-114, December.

    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:inm:orinte:v:33:y:2003:i:5:p:4-21. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.