AN ALGORITHM FOR SCORE CALIBRATION BASED ON CUMULATIVE BAD RATES

Otto Schwalb (), Timothy H. Lee () and Shen Zheng ()
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Otto Schwalb: Equifax Decision Solutions, 1525 Windward Concourse MD-42S, Alpharetta, GA 30005, USA
Timothy H. Lee: Equifax Decision Solutions, 1525 Windward Concourse MD-42S, Alpharetta, GA 30005, USA
Shen Zheng: Equifax Decision Solutions, 1525 Windward Concourse MD-42S, Alpharetta, GA 30005, USA

International Journal of Information Technology & Decision Making (IJITDM), 2003, vol. 02, issue 01, 93-103

Abstract: In credit scoring, it is sometimes desirable to implement a new score in place of an existing score. LetYdenote the existing score and letXdenote the new score. It is almost always the case that the score ranges forXandYare different. For example, the score range forXmight be 0 to 100, while the score range forYmight be 300 to 600. It follows from this difference in score ranges that a major difficulty in implementing any new score will be in training those who use the existing score to use the new score.Score calibration is the process of constructing a calibration functiong (·)in such a way that the calibrated score,g (X), is a score which mimics the behavior ofY. In applications, it is commonly found that problems in the distribution ofg (X)arise as the result of the calibration process. There is a great need in production for an agorithm which automates the task of discovering these problems and correcting them. In this paper, we propose such a fully automatic algorithm. This algorithm has been successfully tested in many applications.

Keywords: Monotone smoothing; nonparametric smoothing; portfolio management; credit risk (search for similar items in EconPapers)
Date: 2003
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DOI: 10.1142/S0219622003000513

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