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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:

    1. Andras Viktor Szabo, 2022. "Credit Risk Modelling of Mortgage Loans in the Supervisory Stress Test of the Magyar Nemzeti Bank," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 21(1), pages 56-94.

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