A Logical Analysis of Banks’ Financial Strength Ratings
34 Pages Posted: 31 Aug 2010 Last revised: 5 Sep 2016
Date Written: 2009
Abstract
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 2 compliant, allowing for their use in the decisions pertaining to the determination of the amount of regulatory capital.
Keywords: credit risk rating, bank creditworthiness, Logical Analysis of Data, combinatorial pattern extraction
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