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Developing a measure of risk adjusted revenue (RAR) in credit cards market: Implications for customer relationship management

  • Singh, Shweta
  • Murthi, B.P.S.
  • Steffes, Erin
Registered author(s):

    Current models of customer lifetime value (CLV) consider the discounted value of profits that a customer generates over an expected lifetime of relationship with the firm. This practice can be misleading in the financial services markets because it ignores the risk posed by the customer (such as delinquency and default). Specifically, in the credit card market, the correlation between revenue and risk is positive. Therefore, firms need to adjust a customer’s profits for the associated risk before developing a measure of customer lifetime value. We propose a new measure, risk adjusted revenue (RAR), that can incorporate multiple sources of risk and demonstrate the usefulness of the proposed measure in correctly assessing the value of a customer in the credit card market. The model can be extended to compute risk adjusted lifetime value (RALTV). We use the RAR metric to understand the effectiveness of different modes of acquisition, and of retention strategies such as affinity cards and reward cards. We find that both reward- and affinity-cardholders generate higher RAR than non-reward and non-affinity cardholders respectively. The ordering of different modes of acquisition with respect to RAR (in decreasing order) is as follows: Internet, direct mail, telesales, and direct selling.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0377221712006078
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    Article provided by Elsevier in its journal European Journal of Operational Research.

    Volume (Year): 224 (2013)
    Issue (Month): 2 ()
    Pages: 425-434

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    Handle: RePEc:eee:ejores:v:224:y:2013:i:2:p:425-434
    Contact details of provider: Web page: http://www.elsevier.com/locate/eor

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    1. Joanna Stavins, 2000. "Credit card borrowing, delinquency, and personal bankruptcy," New England Economic Review, Federal Reserve Bank of Boston, issue Jul, pages 15-30.
    2. Banker, Rajiv D. & Thrall, R. M., 1992. "Estimation of returns to scale using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 62(1), pages 74-84, October.
    3. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    4. Meeusen, Wim & van den Broeck, J, 1977. "Technical Efficiency and Dimension of the Firm: Some Results on the Use of Frontier Production Functions," Empirical Economics, Springer, vol. 2(2), pages 109-22.
    5. Dyson, R. G. & Allen, R. & Camanho, A. S. & Podinovski, V. V. & Sarrico, C. S. & Shale, E. A., 2001. "Pitfalls and protocols in DEA," European Journal of Operational Research, Elsevier, vol. 132(2), pages 245-259, July.
    6. D. J. Hand & W. E. Henley, 1997. "Statistical Classification Methods in Consumer Credit Scoring: a Review," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 160(3), pages 523-541.
    7. Rajiv D. Banker & Robert F. Conrad & Robert P. Strauss, 1986. "A Comparative Application of Data Envelopment Analysis and Translog Methods: An Illustrative Study of Hospital Production," Management Science, INFORMS, vol. 32(1), pages 30-44, January.
    8. Simar, L. & Wilson, P.W., 1998. "A General Methodology for Bootstrapping in Nonparametric Frontier Models," Papers 9811, Catholique de Louvain - Institut de statistique.
    9. Simar, L. & Wilson, P.W., . "Sensitivity analysis of efficiency scores: how to bootstrap in nonparametric frontier models," CORE Discussion Papers RP -1304, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    10. David B. Gross, 2002. "An Empirical Analysis of Personal Bankruptcy and Delinquency," Review of Financial Studies, Society for Financial Studies, vol. 15(1), pages 319-347, March.
    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. 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. Kinsey, Jean, 1981. " Determinants of Credit Card Accounts: An Application of Tobit Analysis," Journal of Consumer Research, University of Chicago Press, vol. 8(2), pages 172-82, September.
    14. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    15. Insik Min & Jong-Ho Kim, 2003. "Modeling Credit Card Borrowing: A Comparison of Type I and Type II Tobit Approaches," Southern Economic Journal, Southern Economic Association, vol. 70(1), pages 128-143, July.
    16. Garcia, Gillian, 1980. " Credit Cards: An Interdisciplinary Survey," Journal of Consumer Research, University of Chicago Press, vol. 6(4), pages 327-37, March.
    17. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    18. Peter S. Fader & Bruce G. S. Hardie & Ka Lok Lee, 2005. "“Counting Your Customers” the Easy Way: An Alternative to the Pareto/NBD Model," Marketing Science, INFORMS, vol. 24(2), pages 275-284, August.
    19. David C. Schmittlein & Robert A. Peterson, 1994. "Customer Base Analysis: An Industrial Purchase Process Application," Marketing Science, INFORMS, vol. 13(1), pages 41-67.
    20. Lucia Dunn & TaeHyung Kim, 1999. "Empirical Investigation of Credit Card Default," Working Papers 99-13, Ohio State University, Department of Economics.
    21. David C. Schmittlein & Donald G. Morrison & Richard Colombo, 1987. "Counting Your Customers: Who-Are They and What Will They Do Next?," Management Science, INFORMS, vol. 33(1), pages 1-24, January.
    22. Cielen, Anja & Peeters, Ludo & Vanhoof, Koen, 2004. "Bankruptcy prediction using a data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 154(2), pages 526-532, April.
    23. Mahajan, Jayashree, 1991. "A data envelopment analytic model for assessing the relative efficiency of the selling function," European Journal of Operational Research, Elsevier, vol. 53(2), pages 189-205, July.
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