Developing, Validating and Using Internal Ratings

This book provides a thorough analysis of internal rating systems. Two case studies are devoted to building and validating statistical-based models for borrowers ratings, using SPSS-PASW and SAS statistical packages. Mainstream approaches to building and validating models for assigning counterpart ratings to small and medium enterprises are discussed, together with their implications on lending strategy. Key Features: Presents an accessible framework for bank managers, students and quantitative analysts, combining strategic issues, management needs, regulatory requirements and statistical bases. Discusses available methodologies to build, validate and use internal rate models. Demonstrates how to use statistical packages for building statistical-based credit rating systems. Evaluates sources of model risks and strategic risks when using statistical-based rating systems in lending. This book will prove to be of great value to bank managers, credit and loan officers, quantitative analysts and advanced students on credit risk management courses.

This book provides a thorough analysis of internal rating systems. Two case studies are devoted to building and validating statistical-based models for borrowers' ratings, using SPSS-PASW and SAS statistical packages. Mainstream approaches to building and validating models for assigning counterpart ratings to small and medium enterprises are discussed, together with their implications on lending strategy.Key Features:* Presents an accessible framework for bank managers, students and quantitative analysts, combining strategic issues, management needs, regulatory requirements and statistical bases.* Discusses available methodologies to build, validate and use internal rate models.* Demonstrates how to use statistical packages for building statistical-based credit rating systems.* Evaluates sources of model risks and strategic risks when using statistical-based rating systems in lending.This book will prove to be of great value to bank managers, credit and loan officers, quantitative analysts and advanced students on credit risk management courses.

Preface1 Introduction2 Classifications and key concepts of credit risk2.1 A classification2.2 Key concepts3 Rating assignment methodologies3.1 Experts based approaches3.2 Statistical based models3.3 Heuristic and numerical approaches3.4 Involving qualitative information4 Developing a statistical based rating system4.1 The process4.2 Setting model's objectives and generating thedataset4.3 Case study: dataset and preliminary analysis4.4 Defining an analysis sample4.5 Univariate and bivariate analyses4.6 Estimating a model and assessing its discriminatorypower4.7 From scores to ratings and from ratings to probabilities ofdefault5 Validating rating models5.1 Validation profiles5.2 Roles of internal validation units5.3 Qualitative and quantitative validation6 Case Study. Validating PanalpBank's statistical basedrating system for Financial Institutions 2116.1 Case study objectives and context6.2 The 'Development report' for the validationunit6.3 The 'Validation report' by the validationunit7 Conclusions. Ratings usage opportunities andwarnings.7.1 Internal ratings are critical to credit risk management7.2 Internal ratings assignment trends7.3 Statistical based ratings and regulation: conflictingobjectives?7.4 Statistical based ratings and customers: needs and fears7.5 Limits of statistical based ratings7.6 Statistical based ratings and the theory of financialintermediation7.7 Statistical based ratings usage: guidelinesBibliographySubject Index