A logical analysis of banks’ financial strength ratings

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摘要

We evaluate the creditworthiness of banks using statistical, as well as combinatorics-, optimization-, and logic-based methodologies. We reverse-engineer the Fitch risk ratings of banks using ordered logistic regression, support vector machine, and Logical Analysis of Data (LAD). The LAD ratings are shown to be the most accurate and most successfully cross-validated. The study shows that the LAD rating approach is (i) objective, (ii) transparent, and (iii) generalizable. It can be used to build internal rating systems that (iv) have varying levels of granularity, and (v) are Basel compliant, allowing for their use in the decisions pertaining to the determination of the amount of regulatory capital.

论文关键词:Data mining,Logical Analysis of Data,Credit risk rating,Decision support systems

论文评审过程:Available online 7 February 2012.

论文官网地址:https://doi.org/10.1016/j.eswa.2012.01.087