Assessing the discriminatory power of credit scores - Holger Kraft; Gerald Kroisandt; Marlene Müller (Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes, 2002)
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.
urn:nbn:de:kobv:11-10049306
Keywords: G21; 330; credit rating; credit score; discriminatory power; sample selection; Gini coefficient; accuracy ratio