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On the confusion matrix in credit scoring and its analytical properties

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  • Guoping Zeng

Abstract

Confusion Matrix is an important measure to evaluate the accuracy of credit scoring models. However, the literature about Confusion Matrix is limited. The analytical properties of Confusion Matrix are ignored. Moreover, the concept of Confusion Matrix is confusing. In this article, we systematically study Confusion Matrix and its analytical properties. We enumerate 16 possible variants of Confusion Matrix and show that only 8 are reasonable. We study the relationship between Confusion Matrix and 2 other performance measures: the receiver operating characteristic curve (ROC) and Kolmogorov-Smirnov statistic (KS). We show that an optimal cutoff score can be attained by KS.

Suggested Citation

  • Guoping Zeng, 2020. "On the confusion matrix in credit scoring and its analytical properties," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 49(9), pages 2080-2093, May.
    • Handle: RePEc:taf:lstaxx:v:49:y:2020:i:9:p:2080-2093
    DOI: 10.1080/03610926.2019.1568485
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    Cited by:

    1. Maria Siranova & Karol Zelenak, 2023. "Every crisis does matter: Comparing the databases of financial crisis events," Review of International Economics, Wiley Blackwell, vol. 31(2), pages 652-686, May.

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