Adjusted Empirical Estimate of Information Value for Credit Scoring Models

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F11%3A00052732" target="_blank" >RIV/00216224:14310/11:00052732 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Adjusted Empirical Estimate of Information Value for Credit Scoring Models
Original language description
To measure the quality of scoring models it is possible to use quantitative indexes such as Gini index, K-S and Information value. The paper deals with the Information value, mainly with issues connected to its computation. The classical way of computation, i.e. empirical estimate using deciles of scores, 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 an adjusted procedure for estimation of the Information value. It is based on ideas of ESIS with adjustment for choice of required number of observations in constructed intervals. The properties of all listed Informationvalue estimators are discussed in the simulation study.
Czech name
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Czech description
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Project
<a href="/en/project/LC06024" target="_blank" >LC06024: Jaroslav Hájek Center for Theoretical and Applied Statistics</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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