SR 11-7 SUPERVISORY GUIDANCE ON MODEL RISK MANAGEMENT

SR Letter 11-7 Attachment Board of Governors of the Federal Reserve System Office of the Comptroller of the Currency April 4, 2011 SUPERVISORY GUIDANCE ON MODEL RISK MANAGEMENT CONTENTS I. Introduction, page II. Purpose and Scope, page III. Overview of Model Risk Management, page IV. Model Development, Implementation, and Use, page V. Model Validation, page VI. Governance, Policies, and Controls, page VII. Conclusion, page 1 2 3 5 9 16 21 I. INTRODUCTION Banks rely heavily on quantitative analysis and models in most aspects of financial decision making.[Fo tn1oe They routinely use models for a broad range of activities, including underwriting credits; valuing exposures, instruments, and positions; measuring risk; managing and†¦show more content†¦For example, steps taken to apply this guidance at a community bank using relatively few models of only moderate complexity might be significantly less involved than those at a larger bank where use of models is more extensive or complex.[PageBreak] - For instance, the OCC provided guidance on model risk, focusing on model validation, in OCC 2000-16 (May 30, 2000), other bulletins, and certain subject matter booklets of the Comptrollers Handbook. The Federal Reserve issued SR Letter 09-01, Application of the Market Risk Rule in Bank Holding Companies and State Member Banks, which highlights various concepts pertinent to model risk management, including standards for validation and review, model validation documentation, and back-testing. The Federal Reserves Trading and Capital-Markets Activities Manual also discusses validation and model risk management. In addition, the advanced-approaches risk-based capital rules (12 CFR 3, Appendix C; 12 CFR 208, Appendix F; and 12 CFR 225, Appendix G) contain explicit validation requirements for subject banking organizations.EndofFootnote2.] Page 2 III. OVERVIEW OF MODEL RISK MANAGEMENT For the purposes of this document, the term model refers to a quantitative method, system, or approach that applies statistical, economic, financial, or mathematical theories, techniques, and assumptions to process input data into quantitative