Name
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 compliant, allowing for their use in the decisions pertaining to the determination of the amount of regulatory capital. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1016/j.eswa.2012.01.087 | Expert Syst. Appl. |
Keywords | Field | DocType |
support vector machine,internal rating system,fitch risk rating,logistic regression,lad rating,logic-based methodology,basel compliant,lad rating approach,financial strength rating,logical analysis,regulatory capital,data mining,decision support systems | Data mining,Ordered logit,Computer science,Decision support system,Logical analysis of data,Support vector machine,Artificial intelligence,Capital requirement,Granularity,Machine learning,Logical analysis | Journal |
Volume | Issue | ISSN |
39 | 9 | 0957-4174 |
Citations | PageRank | References |
5 | 0.43 | 22 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Peter L. Hammer | 1 | 1996 | 288.93 |
| A. Kogan | 2 | 142 | 12.92 |
| Miguel A. Lejeune | 3 | 253 | 21.95 |