The Validation Of Risk Models

This book is a one-stop-shop reference for risk management practitioners involved in the validation of risk models. It is a comprehensive manual about the tools, techniques and processes to be followed, focused on all the models that are relevant in the capital requirements and supervisory review of large international banks.

Risk model validation is an emerging and important area of research, and has arisen because of Basel I and II. These regulatory initiatives require trading institutions and lending institutions to compute their reserve capital in a highly analytic way, based on the use of internal risk models. It is part of the regulatory structure that these risk models be validated both internally and externally, and there is a great shortage of information as to best practise. Editors Christodoulakis and Satchell collect papers that are beginning to appear by regulators, consultants, and academics, to provide the first collection that focuses on the quantitative side of model validation. The book covers the three main areas of risk: Credit Risk and Market and Operational Risk. *Risk model validation is a requirement of Basel I and II *The first collection of papers in this new and developing area of research *International authors cover model validation in credit, market, and operational risk

The practice of quantitative risk management has reached unprecedented levels of refinement. The pricing, the assessment of risk as well as the computation of the capital requirements for highly complex transactions are performed through equally complex mathematical models, running on advanced computer systems, developed and operated by dedicated, highly qualified specialists. With this sophistication, however, come risks that are unpredictable, globally challenging and difficult to manage. Model risk is a prime example and precisely the kind of risk that those tasked with managing financial institutions as well as those overseeing the soundness and stability of the financial system should worry about. This book starts with setting the problem of the validation of risk models within the context of banking governance and proposes a comprehensive methodological framework for the assessment of models against compliance, qualitative and quantitative benchmarks. It provides a comprehensive guide to the tools and techniques required for the qualitative and quantitative validation of the key categories of risk models, and introduces a practical methodology for the measurement of the resulting model risk and its translation into prudent adjustments to capital requirements and other estimates.

IFRS 9 and CECL Credit Risk Modelling and Validation covers a hot topic in risk management. Both IFRS 9 and CECL accounting standards require Banks to adopt a new perspective in assessing Expected Credit Losses. The book explores a wide range of models and corresponding validation procedures. The most traditional regression analyses pave the way to more innovative methods like machine learning, survival analysis, and competing risk modelling. Special attention is then devoted to scarce data and low default portfolios. A practical approach inspires the learning journey. In each section the theoretical dissertation is accompanied by Examples and Case Studies worked in R and SAS, the most widely used software packages used by practitioners in Credit Risk Management. Offers a broad survey that explains which models work best for mortgage, small business, cards, commercial real estate, commercial loans and other credit products Concentrates on specific aspects of the modelling process by focusing on lifetime estimates Provides an hands-on approach to enable readers to perform model development, validation and audit of credit risk models

A comprehensive book on validation with coverage of all the risk management models.

This book explains how a proper credit risk management framework enables banks to identify, assess and manage the risk proactively.

The estimation and the validation of the Basel II risk parameters PD (default probability), LGD (loss given fault), and EAD (exposure at default) is an important problem in banking practice. These parameters are used on the one hand as inputs to credit portfolio models and in loan pricing frameworks, on the other to compute regulatory capital according to the new Basel rules. This book covers the state-of-the-art in designing and validating rating systems and default probability estimations. Furthermore, it presents techniques to estimate LGD and EAD and includes a chapter on stress testing of the Basel II risk parameters. The second edition is extended by three chapters explaining how the Basel II risk parameters can be used for building a framework for risk-adjusted pricing and risk management of loans.