The Validation of Risk Models 2016

The Validation of Risk Models 2016 : A Handbook for Practitioners

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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.
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Product details

  • Paperback | 400 pages
  • 155 x 235mm
  • Basingstoke, United Kingdom
  • English
  • 2016 ed.
  • biography
  • 1349683523
  • 9781349683529

About Sergio Scandizzo

Sergio Scandizzo is Head of Model Validation at the European Investment Bank (EIB) in Luxembourg. He is the author of Risk and Governance: A Framework for Banking Organisations; The Operational Risk Manager's Guide, now in its second edition, and of Validation and Use Test in AMA. He is Associate Editor of The Journal of Operational Risk and was recognized as one of the "Top 50" Face of Operational Risk by OpRisk & Compliance Magazine. He has published several journal papers on fuzzy logic, genetic algorithms and risk management. Before joining the EIB he was a principal in the London office of PricewaterhouseCoopers and, prior to that, a senior manager in the Operational Risk Group at the Canadian Imperial Bank of Commerce in Toronto. He studied in Italy and the United States and holds master degrees in computer science and finance. His website is
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Table of contents

Introduction A Model Risk Primer Part 1 A Framework for Risk Model Validation Chapter 1 The role of validation in banking governance Chapter 2 Validation from a supervisory perspective Chapter 3 A model validation framework for risk management Part 2 Credit Risk Chapter 4 Probability of default models Chapter 5 Loss Given Default models Chapter 6 Credit Conversion Factor models Part 3 Counterparty Credit Risk Chapter 7 Derivatives valuation models Chapter 8 Expected Future Exposure models Chapter 9 Credit Valuation Adjustment models Part 4 Market risk Chapter 10 Trading market risk models Chapter 11 Hedging and model validation Chapter 12 Interest rate risk on the banking book Part 5 Operational risk Chapter 13 The validation of AMA models Chapter 14 Use test for operational risk Part 6 Validation of Pillar 2 Models Chapter 15 Economic capital models Chapter 16 Stress testing models Conclusion
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