Measuring 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%2F09%3A00036504" target="_blank" >RIV/00216224:14310/09:00036504 - 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
Measuring the Quality of Credit Scoring Models
Original language description
In the current strong competitive environment it is quite fundamental good care of the quality of client portfolio. Credit scoring models are widely used to achieve this business aim. For a measurement of quality of the scoring models it is possible to use quantitative indexes such as Gini index, K-S statistics, Lift, Mahalanobis distance and Information statistics. They can be used for comparison of several developed models at the moment of development. It is possible to use them for monitoring of quality of models after the deployment into real business as well. Figures like ROC curve (Lorenz curve), Lift chart (Gains chart) can be used as well. This paper deals with definition of good/bad client, which is crucial for further computations. Parametersaffecting this definition are discussed. The main part is devoted to quality indexes based on distribution functions (Gini, K-S and Lift) and on density functions (Mahalanobis distance, Information statistics).
Czech name
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Czech description
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Classification
Type
O - Miscellaneous
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
2009
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů