PwC offers a full range of advisory services to assist you in identifying and managing the model risks associated with models used for risk management, valuation, and financial/regulatory reporting purposes.
MRM program design: Design and development of model risk management / model governance programs ― including:
- Organizational design for the model risk management organization
- Development of model risk management policies and frameworks as well as detailed procedures and standards covering the full model life cycle
- Resource planning and analysis
MRM program assessment: Evaluation of existing model risk management programs for effectiveness and for consistency with regulatory expectations and industry leading practices
Internal audit: Testing of model risk management framework design and operating effectiveness for internal audit
Model validation: Assistance with independent model validations for a wide range of model types ― including:
- Consumer and commercial credit models ― including CCAR/DFAST stress testing models, credit scorecards, credit loss forecasting models, allowance for loan loss models, and models used to support Basel capital estimates
- Pre Provision Net Revenue (PPNR) models used in CCAR/DFAST stress testing
- Mortgage loan prepayment and valuation models
- Financial instrument valuation models
- Financial reporting models ― including ASC 310-20 (formerly FAS 91) amortization, ASC 450 (formerly FAS 5) reserves, CECL, IFRS 9, and ASC 310-30 (formerly SOP 03-3)
We are well qualified to deliver industry-leading model risk management services:
Highly-experienced team of model risk management specialists: We have a broad and deep team of model risk professionals whose experience covers virtually all financial model types – including those used to manage credit risk, market risk, operational risk, and compliance risk – as well as those used for financial reporting, valuations, and economic capital estimation.
Significant exposure to, and driver of, industry leading practices: Our combination of advisory and audit-related model risk management and validation work for many of the largest global financial services firms provides us with significant exposure to leading practices in the areas of model risk management. Since the year 2000, PwC has been at the forefront of the professional services industry in developing and refining approaches to implement the Office of the Comptroller of the Currency’s (“OCC’s”) 2000-16 guidance on Model Validation for various model types and, subsequently, OCC’s 2011-12 model risk management guidance (issued jointly with the Federal Reserve as bulletin SR 11-7).
Deep knowledge of regulatory expectations: PwC has developed strong relationships with the US bank regulatory agencies and has met regularly with the OCC to discuss both existing and emerging model risk issues. PwC has also provided training to both Federal Reserve and OCC examiners in the area of model risk and model validation.
Extensive thought leadership: PwC is an industry leader in sharing our point-of-view on model risk management issues through published articles in American Banker and Bank Accounting & Finance, through our FS Regulatory white paper series, and through invited presentations at industry conferences.
What is model risk?
Financial institutions rely heavily on financial and economic models for a wide range of applications ― such as risk management, valuation, stress testing, and financial / regulatory reporting. The level of sophistication of models used for such applications varies widely from relatively simple spreadsheet tools to complex statistical models applied to millions of transactions.
Regardless of the level of sophistication, model usage exposes a financial institution to model risk ― which typically involves the possibility of a financial loss, incorrect business decisions, misstatement of external financial disclosures, or damage to the company’s reputation arising from:
- Possible errors in the model design and development process (including the design and development of changes to existing models) ― such as errors in the data, theory, statistical analysis, assumptions, or computer code underlying a model
- Misapplication of models, or model results, by model users
- Use of models whose performance does not meet company standards
- Possible errors in the model production process ― such as errors in data inputs and assumptions, or errors in model execution