Abstract
We consider methods for incorporating forecasts of future economic conditions into acquisition decisions for scored retail credit and loan portfolios. We suppose that a portfolio manager is faced with two possible future economic scenarios, each characterised by a known probability of occurrence and by known performance functions that give expected profit and volume. We suppose further that he must choose in advance the scoring strategy and score cutoffs to optimise performance. We show that, despite the uncertainty of performance induced by economic conditions, every efficient policy consists of a single cutoff, provided the expected profit and volume performance curves in each scenario are concave. If these curves are not concave, efficient operating points can be characterised as cutoffs on a redefined score. In cases in which two scorecards are available, we show that it may be advantageous to randomly choose the scorecard to be employed, and we provide methods for selecting efficient operating points. Discussion is limited to cases with two scorecards and two economic scenarios, but our approach and results generalise to more scorecards and more economic scenarios.
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Acknowledgements
The authors are grateful to the anonymous reviewers, who provided many helpful comments and suggestions for improvement, particularly with regard to variance derivations included in the original draft.
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Rajaratnam, K., Beling, P. & Overstreet, G. Scoring decisions in the context of economic uncertainty. J Oper Res Soc 61, 421–429 (2010). https://doi.org/10.1057/jors.2009.99
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DOI: https://doi.org/10.1057/jors.2009.99