Publication details

Computation of Information Value for Credit Scoring Models



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

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.
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