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“Time-to-profit scorecards for revolving credit”

Author

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  • Sanchez-Barrios, Luis Javier
  • Andreeva, Galina
  • Ansell, Jake

Abstract

This paper defines and models time-to-profit for the first time for credit acceptance decisions within the context of revolving credit. This requires the definition of a time-related event: A customer is profitable when monthly cumulative return is at least one (i.e. cumulative profits cover the outstanding balance). Time-to-profit scorecards were produced for a data set of revolving credit from a Colombian lending institution which included socio-demographic and first purchase individual characteristics. Results show that it is possible to obtain good classification accuracy and improve portfolio returns which are continuous by definition through the use of survival models for binary events (i.e. either being profitable or not). It is also shown how predicting time-to-profit can be used for investment planning purposes of credit programmes. It is possible to identify the earliest point in time in which a customer is profitable and hence, generates internal (organic) funds for a credit programme to continue growing and become sustainable. For survival models the effect of segmentation on loan duration was explored. Results were similar in terms of classification accuracy and identifying organic growth opportunities. In particular, loan duration and credit limit usage have a significant economic impact on time-to-profit. This paper confirms that high risk credit programmes can be profitable at different points in time depending on loan duration. Furthermore, existing customers may provide internal funds for the credit programme to continue growing.

Suggested Citation

  • Sanchez-Barrios, Luis Javier & Andreeva, Galina & Ansell, Jake, 2016. "“Time-to-profit scorecards for revolving credit”," European Journal of Operational Research, Elsevier, vol. 249(2), pages 397-406.
    • Handle: RePEc:eee:ejores:v:249:y:2016:i:2:p:397-406
    DOI: 10.1016/j.ejor.2015.09.052
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    References listed on IDEAS

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    1. P Ma & J Crook & J Ansell, 2010. "Modelling take-up and profitability," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(3), pages 430-442, March.
    2. G Andreeva & J Ansell & J N Crook, 2005. "Modelling the purchase propensity: analysis of a revolving store card," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(9), pages 1041-1050, September.
    3. Luis Javier Sánchez Barrios & Galina Andreeva & Jake Ansell, 2014. "Monetary and relative scorecards to assess profits in consumer revolving credit," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(3), pages 443-453, March.
    4. D J Hand & M G Kelly, 2001. "Lookahead scorecards for new fixed term credit products," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(9), pages 989-996, September.
    5. Finlay, Steven, 2010. "Credit scoring for profitability objectives," European Journal of Operational Research, Elsevier, vol. 202(2), pages 528-537, April.
    6. J Banasik & J N Crook & L C Thomas, 1999. "Not if but when will borrowers default," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 50(12), pages 1185-1190, December.
    7. Andreeva, Galina & Ansell, Jake & Crook, Jonathan, 2007. "Modelling profitability using survival combination scores," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1537-1549, December.
    8. Solo, Tova Maria & Manroth, Astrid, 2006. "Access to financial services in Colombia : the"unbanked"in Bogota," Policy Research Working Paper Series 3834, The World Bank.
    9. S M Finlay, 2008. "Towards profitability: a utility approach to the credit scoring problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(7), pages 921-931, July.
    10. Audzeyeva, Alena & Summers, Barbara & Schenk-Hoppé, Klaus Reiner, 2012. "Forecasting customer behaviour in a multi-service financial organisation: A profitability perspective," International Journal of Forecasting, Elsevier, vol. 28(2), pages 507-518.
    11. Alan Lucas, 2001. "Statistical challenges in credit card issuing," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 17(1), pages 83-92, January.
    12. M Stepanova & L C Thomas, 2001. "PHAB scores: proportional hazards analysis behavioural scores," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(9), pages 1007-1016, September.
    13. Maria Stepanova & Lyn Thomas, 2002. "Survival Analysis Methods for Personal Loan Data," Operations Research, INFORMS, vol. 50(2), pages 277-289, April.
    14. 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.
    15. Somers, Mark & Whittaker, Joe, 2007. "Quantile regression for modelling distributions of profit and loss," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1477-1487, December.
    16. Chae Woo Nam & Tong Suk Kim & Nam Jung Park & Hoe Kyung Lee, 2008. "Bankruptcy prediction using a discrete-time duration model incorporating temporal and macroeconomic dependencies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(6), pages 493-506.
    17. R T Stewart, 2011. "A profit-based scoring system in consumer credit: making acquisition decisions for credit cards," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(9), pages 1719-1725, September.
    18. J Banasik & J Crook, 2010. "Reject inference in survival analysis by augmentation," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(3), pages 473-485, March.
    19. Thomas, Lyn C., 2009. "Consumer Credit Models: Pricing, Profit and Portfolios," OUP Catalogue, Oxford University Press, number 9780199232130, Decembrie.
    20. Zhang, Jie & Thomas, Lyn C., 2012. "Comparisons of linear regression and survival analysis using single and mixture distributions approaches in modelling LGD," International Journal of Forecasting, Elsevier, vol. 28(1), pages 204-215.
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    Cited by:

    1. Kaveh Bastani & Elham Asgari & Hamed Namavari, 2018. "Wide and Deep Learning for Peer-to-Peer Lending," Papers 1810.03466, arXiv.org, revised Oct 2018.

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