A Conservative Approach to Assessment of Discriminatory Models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F11%3A00056400" target="_blank" >RIV/00216224:14310/11:00056400 - 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
A Conservative Approach to Assessment of Discriminatory Models
Original language description
Lenders, such as banks and credit card companies, use credit scoring to evaluate the potential risk posed by lending money to consumers. Once a scoring model is available, it is natural to measure its quality. To evaluate the effectiveness of credit scoring models, it is possible to use quantitative indexes such as Gini index, K-S statistics, Lift, Information statistics etc. The paper deals with mentioned quality indexes, their properties and relationships. Finally, a new approach to measure power of scoring models is discussed and a new quality index is proposed. Also an application of mentioned theory on simulated data set is demonstrated.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
BA - General mathematics
OECD FORD branch
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Result continuities
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)
Others
Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Workshop of the Jaroslav Hájek Center and Financial Mathematics in Practice I, Book of short papers
ISBN
978-80-210-5778-4
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
30-36
Publisher name
Masaryk University
Place of publication
Brno
Event location
Jedovnice
Event date
Jan 1, 2011
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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