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Kalman filtering as a performance monitoring technique for a propensity scorecard

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  • K Bijak

    (University of Southampton
    Biuro Informacji Kredytowej S.A.)

Abstract

Propensity scorecards allow forecasting, which bank customers would like to be granted new credits in the near future, through assessing their willingness to apply for new loans. Kalman filtering can help to monitor scorecard performance. Data from successive months are used to update the baseline model. The updated scorecard is the output of the Kalman filter. There is no assumption concerning the scoring model specification and no specific estimation method is presupposed. Thus, the estimator covariance is derived from the bootstrap. The focus is on a relationship between the score and the natural logarithm of the odds for that score, which is used to determine a customer's propensity level. The propensity levels corresponding to the baseline and updated scores are compared. That comparison allows for monitoring whether the scorecard is still up-to-date in terms of assigning the odds. The presented technique is illustrated with an example of a propensity scorecard developed on the basis of credit bureau data.

Suggested Citation

  • K Bijak, 2011. "Kalman filtering as a performance monitoring technique for a propensity scorecard," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(1), pages 29-37, January.
    • Handle: RePEc:pal:jorsoc:v:62:y:2011:i:1:d:10.1057_jors.2009.183
    DOI: 10.1057/jors.2009.183
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    References listed on IDEAS

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    1. Harvey,Andrew C., 1991. "Forecasting, Structural Time Series Models and the Kalman Filter," Cambridge Books, Cambridge University Press, number 9780521405737.
    2. Thomas, Lyn C. & Edelman, David B. & Crook, Jonathan, 2004. "Readings in Credit Scoring: Foundations, Developments, and Aims," OUP Catalogue, Oxford University Press, number 9780198527978.
    3. Thomas, Lyn C., 2009. "Consumer Credit Models: Pricing, Profit and Portfolios," OUP Catalogue, Oxford University Press, number 9780199232130.
    4. 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.
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