How to Measure the Quality of Credit Scoring Models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F11%3A00053814" target="_blank" >RIV/00216224:14310/11:00053814 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
How to Measure the Quality of Credit Scoring Models
Original language description
Credit scoring models are widely used to predict the probability of client default. To measure the quality of such scoring models it is possible to use quantitative indices such as the Gini index, Kolmogorov-Smirnov statistics (KS), Lift, the Mahalanobisdistance, and information statistics. This paper reviews and illustrates the use of these indices in practice.
Czech name
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Czech description
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Classification
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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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Finance a úvěr - Czech Journal of Economics and Finance
ISSN
0015-1920
e-ISSN
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Volume of the periodical
61
Issue of the periodical within the volume
5
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
22
Pages from-to
486-507
UT code for WoS article
000296909200009
EID of the result in the Scopus database
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