A Logical Analysis of Banks’ Financial Strength Ratings

34 Pages Posted: 31 Aug 2010 Last revised: 5 Sep 2016

See all articles by Peter L. Hammer

Peter L. Hammer

Rutgers, The State University of New Jersey

Alexander Kogan

Rutgers, The State University of New Jersey

Miguel Lejeune

George Washington University

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

Suggested Citation

Hammer, Peter L. and Kogan, Alexander and Lejeune, Miguel, A Logical Analysis of Banks’ Financial Strength Ratings (2009). Available at SSRN: https://ssrn.com/abstract=975572 or http://dx.doi.org/10.2139/ssrn.975572

Peter L. Hammer

Rutgers, The State University of New Jersey ( email )

311 North 5th Street
New Brunswick, NJ 08854
United States

Alexander Kogan

Rutgers, The State University of New Jersey ( email )

311 North 5th Street
New Brunswick, NJ 08854
United States

Miguel Lejeune (Contact Author)

George Washington University ( email )

Washington, DC 20052
United States

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