Giacomo de laurentis developing validating and using internal ratings dating tours china
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 Panalp Bank 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. 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?
Key Features: * Presents an accessible framework for bank managers, students and quantitative analysts, combining strategic issues, management needs, regulatory requirements and statistical bases.
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.
Preface 1 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 the dataset4.3 Case study: dataset and preliminary analysis4.4 Defining an analysis sample4.5 Univariate and bivariate analyses4.6 Estimating a model and assessing its discriminatory power4.7 From scores to ratings and from ratings to probabilities of default5 Validating rating models5.1 Validation profiles5.2 Roles of internal validation units5.3 Qualitative and quantitative validation6 Case Study.
Validating Panalp Bank’s statistical based rating system for Financial Institutions 2116.1 Case study objectives and context6.2 The ‘Development report’ for the validation unit6.3 The ‘Validation report’ by the validation unit7 Conclusions.
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