Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/65361 
Year of Publication: 
2002
Series/Report no.: 
SFB 373 Discussion Paper No. 2002,67
Publisher: 
Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes, Berlin
Abstract: 
We discuss how to assess the performance for credit scores under the assumption that for credit data only a part of the defaults and nondefaults is observed. The paper introduces a criterion that is based on the difference of the score distributions under default and nondefault. We show how to estimate bounds for this criterion, the Gini coefficient and the accuracy ratio.
Subjects: 
credit rating
credit score
discriminatory power
sample selection
Gini coefficient
accuracy ratio
JEL: 
G21
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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