Computation of Information Value for Credit Scoring Models
| Authors | |
|---|---|
| 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 | |
| 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: |