Developing, Validating and Using Internal Ratings – Methodologies and Case Studies

Giacomo De Laurentis, Full Professor of Banking and Finance, Bocconi University. Director of Executive Education Open Programs Division of SDA Bocconi School of Management, Italy. Renato Maino, Professor at Bocconi University and Turin University, Consultant on Risk Management issues for commercial banks, asset Management companies and corporate, Italy. Luca Molteni, Assistant Professor of Statistics, Bocconi University, CEO of Target Research, Italy.

Preface 1 Introduction 2 Classifications and key concepts of credit risk 2.1 A classification 2.2 Key concepts 3 Rating assignment methodologies 3.1 Experts based approaches 3.2 Statistical based models 3.3 Heuristic and numerical approaches 3.4 Involving qualitative information 4 Developing a statistical based rating system 4.1 The process 4.2 Setting model's objectives and generating the dataset 4.3 Case study: dataset and preliminary analysis 4.4 Defining an analysis sample 4.5 Univariate and bivariate analyses 4.6 Estimating a model and assessing its discriminatory power 4.7 From scores to ratings and from ratings to probabilities of default 5 Validating rating models 5.1 Validation profiles 5.2 Roles of internal validation units 5.3 Qualitative and quantitative validation 6 Case Study. Validating PanalpBank's statistical based rating system for Financial Institutions 211 6.1 Case study objectives and context 6.2 The 'Development report' for the validation unit 6.3 The 'Validation report' by the validation unit 7 Conclusions. Ratings usage opportunities and warnings. 7.1 Internal ratings are critical to credit risk management 7.2 Internal ratings assignment trends 7.3 Statistical based ratings and regulation: conflicting objectives? 7.4 Statistical based ratings and customers: needs and fears 7.5 Limits of statistical based ratings 7.6 Statistical based ratings and the theory of financial intermediation 7.7 Statistical based ratings usage: guidelines Bibliography Subject Index