Principles and Practices of Model Risk Management (MRM)

Erscheinungsjahr 2027
ISBN: 978-0-443-27733-7
Verlag: Elsevier Science & Technology

Buch, Englisch, Format (B × H): 191 mm x 235 mm, Gewicht: 450 g

Principles and Practices of Model Risk Management (MRM) offers a thorough yet practical introduction to MRM, helping modern enterprises and financial engineers successfully navigate evolving, global markets. Initially developed within the financial industry, the advent of increasingly sophisticated computer models and AI have broadened the scope and necessity of model risk management. This textbook fills a critical gap by guiding readers in designing and implementing robust model risk frameworks across evolving scenarios and data landscapes. Authored by experts with extensive quantitative backgrounds and significant experience in model risk management within major banks, this book articulates modern MRM concepts and shares best practices from industry practitioners. Relevant for students of financial engineering, financial mathematics, and beyond, this essential resource is designed to benefit risk management professionals, financial analysts, regulatory compliance officers, and anyone involved in the development, validation, and oversight of financial models, providing them with the tools and understanding necessary to navigate and mitigate model risks effectively. Online hosted Jupyter notebooks offer various examples and datasets to put skills into practice across chapters. This book covers the regulatory background of model risk management across different jurisdictions, delves into the various types of model risk, and elucidates the tools and methodologies used for identifying, measuring, monitoring, and reporting model risk. It includes detailed sections on the principles of model risk management, enterprise risk management frameworks, model risk regulations and guidance, the three lines of defense in model risk management, and practical applications within the financial industry. Additionally, it addresses emerging trends and challenges, particularly in the context of generative AI models and future regulatory developments.

Autoren/Hrsg.

Lu, Charlie

Russo, Peter

Fachgebiete

• Wirtschaftswissenschaften Wirtschaftswissenschaften Wirtschaft: Sachbuch, Ratgeber
• Wirtschaftswissenschaften Betriebswirtschaft Unternehmensfinanzen Controlling, Wirtschaftsprüfung, Revision

Inhaltsverzeichnis

Part I – Principles of Model Risk Management
1. Introduction to Model Risk Management
2. The Risk Management Framework- The Enterprise Risk Management Framework
3. Model Risk Regulations and Guidance in the US, EU, and UK
4. 1st Line - Model Development/Model Owners
5. 2nd Line - Independent Model Risk Management
6. 3rd Line Model Risk Management Audit

Part II – Practices of Model Risk Managements
7. Causes of Model Risk
8. Model Risk Management in the Financial Industry
9. Emerging Trends and Challenges
10. Conclusion Appendices - Glossary of Terms - References and Further Reading - Templates and Checklists

Über Autor(innen)

Russo, Peter
Peter Russo is a risk professional in the model risk management space with expertise in multiple areas, including operational risk, wholesale credit risk, stress testing, liquidity stress, economic scenario generation, and market risk. Additionally, he has extensive experience in developing production-grade deep learning models for the e-commerce space. He is also a course designer and instructor for the Introduction to Model Risk Management course in Columbia University’s ERM program, which has been offered in the Columbia ERM program since January 2022.

Lu, Charlie
Charlie Lu is an industry-leader with extensive experience in building model and model risk management areas, including consumer credit cards, wholesale credits, counterparty credits, liquidity stress, IRRBB, market risk, derivatives pricing, operational risk, stress testing, and scenario expansion. Additional modeling experience spans across AI/ML in fraud detection, surveillance and compliance, marketing, valuation, and customer maintenance. He has helped establish respected brand names and served as an ultimate gatekeeper and arbitrager to resolve disagreements in model validation. Recognized as key contributor in building model risk management frameworks, including policy, standards, procedures, risk assessment, and large model frameworks to address aggregated model risk, Charlie Lu has also contributed significantly to regulatory mandates, including CCAR, LST, RRP, IRRBB, and CECL.