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 estimates.
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Today we will start from something very important: Some guidance for model risk management, Board of Governors of the Federal Reserve System, Office of the Comptroller of the Currency
SUPERVISORY GUIDANCE ON MODEL RISK MANAGEMENT
Banks rely heavily on quantitative analysis and models in most aspects of financial decision making.
They routinely use models for a broad range of activities, including underwriting credits; valuing exposures, instruments, and positions;
measuring risk; managing and safeguarding client assets; determining capital and reserve adequacy; and many other activities.
In recent years, banks have applied models to more complex products and with more ambitious scope, such as enterprise-wide risk measurement, while the markets in which they are used have also broadened and changed.
Changes in regulation have spurred some of the recent developments, particularly the U.S. regulatory capital rules for market, credit, and operational risk based on the framework developed by the Basel Committee on Banking Supervision.
Even apart from these regulatory considerations, however, banks have been increasing the use of data-driven, quantitative decision-making tools for a number of years.
The expanding use of models in all aspects of banking reflects the extent to which models can improve business decisions, but models also come with costs.
There is the direct cost of devoting resources to develop and implement models properly.
There are also the potential indirect costs of relying on models, such as the possible adverse consequences (including financial loss) of decisions based on models that are incorrect or misused.
Those consequences should be addressed by active management of model risk.
II. PURPOSE AND SCOPE
The purpose of this document is to provide comprehensive guidance for banks on effective model risk management.
Rigorous model validation plays a critical role in model risk management; however, sound development, implementation, and use of models are also vital elements.
Furthermore, model risk management encompasses governance and control mechanisms such as board and senior management oversight, policies and procedures, controls and compliance, and an appropriate incentive and organizational structure.
Previous guidance and other publications issued by the OCC and the Federal Reserve on the use of models pay particular attention to model validation.
Based on supervisory and industry experience over the past several years, this document expands on existing guidance—most importantly by broadening the scope to include all aspects of model risk management.
Many banks may already have in place a large portion of these practices, but all banks should ensure that internal policies and procedures are consistent with the risk management principles and supervisory expectations contained in this guidance.
Details may vary from bank to bank, as practical application of this guidance should be customized to be commensurate with a bank’s risk exposures, its business activities, and the complexity and extent of its model use.
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.
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 estimates.
A model consists of three components:
1. An information input component, which delivers assumptions and data to the model;
2. A processing component, which transforms inputs into estimates;
3. A reporting component, which translates the estimates into useful business information.
Models meeting this definition might be used for analyzing business strategies, informing business decisions, identifying and measuring risks, valuing exposures, instruments or positions, conducting stress testing, assessing adequacy of capital, managing client assets, measuring compliance with internal limits, maintaining the formal control apparatus of the bank, or meeting financial or regulatory reporting requirements and issuing public disclosures.
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