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Recalibrating scorecards

Author

Listed:
  • L C Thomas

    (University of Southampton)

  • J Banasik

    (University of Edinburgh)

  • J N Crook

    (University of Edinburgh)

Abstract

Many credit scoring systems depend on scorecards which order applicants by credit risk. However the scorecards may also have other properties with certain scores reflecting certain good:bad odds or differences in scores having the same property throughout the score range. Other properties like positivity of attribute points may be required for palatability or internal marketing reasons. The paper outlines the results of a small survey of what properties scorecard builders require of their scorecards. It then discusses how these properties can be obtained and describes a linear programming formulation which recalibrates scorecards so as to produce the best approximate scorecard with the properties required.

Suggested Citation

  • L C Thomas & J Banasik & J N Crook, 2001. "Recalibrating scorecards," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(9), pages 981-988, September.
    • Handle: RePEc:pal:jorsoc:v:52:y:2001:i:9:d:10.1057_palgrave.jors.2601192
    DOI: 10.1057/palgrave.jors.2601192
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    Citations

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    Cited by:

    1. S M Finlay, 2006. "Predictive models of expenditure and over-indebtedness for assessing the affordability of new consumer credit applications," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(6), pages 655-669, June.
    2. J Whittaker & C Whitehead & M Somers, 2007. "A dynamic scorecard for monitoring baseline performance with application to tracking a mortgage portfolio," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(7), pages 911-921, July.
    3. D J Hand, 2005. "Good practice in retail credit scorecard assessment," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(9), pages 1109-1117, September.

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