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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. Parameters affecting 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).
- 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. Parameters affecting 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). (en)
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Title
| - Measuring the Quality of Credit Scoring Models
- Measuring the Quality of Credit Scoring Models (en)
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skos:prefLabel
| - Measuring the Quality of Credit Scoring Models
- Measuring the Quality of Credit Scoring Models (en)
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skos:notation
| - RIV/00216224:14310/09:00036504!RIV10-MSM-14310___
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http://linked.open...avai/riv/aktivita
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http://linked.open...avai/riv/aktivity
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http://linked.open...vai/riv/dodaniDat
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http://linked.open...aciTvurceVysledku
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http://linked.open.../riv/druhVysledku
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http://linked.open...iv/duvernostUdaju
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http://linked.open...titaPredkladatele
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http://linked.open...dnocenehoVysledku
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http://linked.open...ai/riv/idVysledku
| - RIV/00216224:14310/09:00036504
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http://linked.open...riv/jazykVysledku
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http://linked.open.../riv/klicovaSlova
| - Predictive modeling; Quality indexes; Credit scoring; Normally distributed scores (en)
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http://linked.open.../riv/klicoveSlovo
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http://linked.open...ontrolniKodProRIV
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http://linked.open...in/vavai/riv/obor
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http://linked.open...ichTvurcuVysledku
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http://linked.open...cetTvurcuVysledku
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http://linked.open...UplatneniVysledku
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http://linked.open...iv/tvurceVysledku
| - Řezáč, František
- Řezáč, Martin
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http://localhost/t...ganizacniJednotka
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