Optimization of Post-Scoring Classification and Impact on Regulatory Capital for Low Default Portfolios

Genest, benoit and Fares, Ziad (2014): Optimization of Post-Scoring Classification and Impact on Regulatory Capital for Low Default Portfolios.

Abstract

After the crisis of 2008, new regulatory requirements have emerged with supervisors strengthening their position in terms of requirements to meet IRBA standards. Low Default Portfolios (LDP) present specific characteristics that raise challenges for banks when building and implementing credit risk models. In this context, where banks are looking to improve their Return On Equity and supervisors strengthening their positions, this paper aims to provide clues for optimizing Post-Scoring classification as well as analyzing the relationship between the number of classes in a rating scale and the impact on regulatory capital for LDPs.

• Item Type: MPRA Paper
• Language: English
• Keywords: Basel II, Return On Equity, RWA, Classification trees, Rating scale, Gini, LDP
• Subjects: C - Mathematical and Quantitative Methods > C4 - Econometric and Statistical Methods: Special Topics; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling; G - Financial Economics > G2 - Financial Institutions and Services > G21 - Banks ; Depository Institutions ; Micro Finance Institutions ; Mortgages

References

Breiman, L., Friedman, J., Olshen, R., & Stone, C. (1984). Classification and Regression Trees.

Kass, G. (1980). An Exploratory Technique for Investigating Large Quantities of Categorical Data. Applied Statistics, Vol. 29, No. 2., 119-127.

Loh, W.-Y., & Shih, Y.-S. (1997). Split Selection Methods for Classification Trees. Statistica Sinica, Vol. 7, 815-840. Rakotomalala, R. (2005). Arbres de décision. Modulad,33, 163-187.

Rakotomalala, R. Les méthodes d'induction d'arbres, CHAID, CART, C4, C5.

Ritschard, G. (2010). CHAID and Earlier Supervised Tree.

Rokach, L., & Maimon, O. (2010). Data Mining and Knowledge Discovery Handbook. Springer. Fovea. La segmentation (2010).

Stéphane Tufféery, Data Mining and Statistics for Decision Making, University of Rennes, France Techniques of Decision Trees Induction, Chapter 2.

Lior Rokah, Oded Maimon, Data Mining And Knowledge Discovery Handbook, Decision Trees, Chapter 9.

Jerome Frugier, Benoit Genest, Optimization of Post-Scoring Classication Methods and their Impact on the Assessment of Probabilities of Default and on RegulatoryCapital. 2005