Computation of Information Value for Credit Scoring Models

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Authors	ŘEZÁČ Martin KOLÁČEK Jan
Year of publication	2011
Type	Article in Proceedings
Conference	Workshop of the Jaroslav Hájek Center and Financial Mathematics in Practice I, Book of short papers
MU Faculty or unit	Faculty of Science
Citation
Field	Applied statistics, operation research
Keywords	Credit scoring; Quality indexes; Information value; ESIS; ESIS1; ESIS2
Description	Empirical estimate using deciles of scores is the classical way how to compute the Information value for credit scoring models. It is easy to implement, but may lead to strongly biased results. Kernel estimate or empirical estimates with supervised interval selection (ESIS) seems to be more appropriate to use. The main contribution of this paper is a proposal of new algorithms for computation the Information value. They are based on concept of ESIS. The properties of all listed Information value estimators are discussed in the simulation study.
Related projects:	Jaroslav Hájek Center for Theoretical and Applied Statistics