ESIS2 - Information Value Estimator for Credit scoring models

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F15%3A00081966" target="_blank" >RIV/00216224:14310/15:00081966 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/s10614-014-9424-0" target="_blank" >http://dx.doi.org/10.1007/s10614-014-9424-0</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s10614-014-9424-0" target="_blank" >10.1007/s10614-014-9424-0</a>

Result language
angličtina
Original language name
ESIS2 - Information Value Estimator for Credit scoring models
Original language description
Information value is widely used to assess discriminatory power of credit scoring models, i.e. models that try to predict a probability of client?s default. Moreover it is very often used to assess the discriminatory power of variables that enter into these models. This means that the Information value is used as a filter for variable selection. However, empirical estimate using deciles of scores, which is the common way how to compute it, may lead to strongly biased results. The main aim of this paperis to give an alternative estimator of the Information value, named ESIS2, which leads to lowered bias and MSE. The implication of this is better credit scoring model. And what is essential, the direct consequence of having better credit scoring model issignificantly higher profitability of credit business.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
BB - Applied statistics, operational research
OECD FORD branch
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Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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