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Non-linearity of scorecard log-odds

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  • McDonald, Ross A.
  • Sturgess, Matthew
  • Smith, Keith
  • Hawkins, Michael S.
  • Huang, Edward Xiao-Ming

Abstract

The use of linear and log-linear models for scorecard construction is nearly universal. In this paper we address the question of non-linearity in the distribution of a scorecard’s inferred log-odds to score relationship. Linear scorecards are excellent and robust ranking tools, but the inferred default probabilities are increasingly used in day-to-day business operations — within account-level strategies, for cutoff setting, and for capital allocation. All of these uses are dependent upon the accurate estimation of the probability of default, which is a quality independent of a model’s ranking performance.

Suggested Citation

  • McDonald, Ross A. & Sturgess, Matthew & Smith, Keith & Hawkins, Michael S. & Huang, Edward Xiao-Ming, 2012. "Non-linearity of scorecard log-odds," International Journal of Forecasting, Elsevier, vol. 28(1), pages 239-247.
    • Handle: RePEc:eee:intfor:v:28:y:2012:i:1:p:239-247
    DOI: 10.1016/j.ijforecast.2011.01.001
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    References listed on IDEAS

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    1. Thomas, Lyn C., 2009. "Consumer Credit Models: Pricing, Profit and Portfolios," OUP Catalogue, Oxford University Press, number 9780199232130.
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    Cited by:

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