Model risk represents the potential that a financial institution may experience adverse consequences based on a decision reached by using a model. It may originate due to fundamental model errors or due to incorrect or inappropriate use of an otherwise sound model. An organisation's exposure to model risk varies given its unique mix of business activities and level of model usage; greater complexity and broader use indicate higher risk.
Our management and boards of directors understand the value – and limitations – of their models so they can make confident business decisions, advance business strategies and achieve regulatory compliance.
Models are simplified and idealised representations of the real world and are prone to errors in some cases. Further, because models are driven by assumptions and finite data inputs and then interpreted by people, model risk is inescapable. The use and reliance on quantitative models creates the need to consider the degree to which model risks are understood, monitored and managed. Regulators mandate model validation under such pronouncements as OCC 2011-12/FRB SR 11-7 and comparable regulatory guidance. Other stakeholders, such as auditors, investors and rating agencies, are also demanding improved governance over the ever-expanding inventory of quantitative models.
Protiviti provides a full spectrum of services to financial service industry and insurance clients through value-added capabilities needed to support business strategies and continuously improve operational performance while effectively managing risk. Our practice includes specialists in specific risks and processes that are important to the financial services industry. Working together, the people, processes, technologies and knowledge sharing we provide help our clients improve their operations to face the future with confidence.
Our Model Risk team brings Ph.D.-level “quant” experience to developing and validating all types of quantitative models, including asset-liability management, credit risk, economic capital, market risk, pricing and operational risk models. We also validate AML transaction monitoring systems and Fraud models. Our independent, holistic validation process helps control model risk, prevents losses associated with model risk and enhances key stakeholders' understanding of models. We also help organisations manage their portfolio of model risks by assessing, designing and implementing model governance programs.
We can develop customised quantitative models, refine and calibrate existing models, and design stress testing and scenario analysis programs to supplement existing analytics. Our model risk experts can help with the following:
Our areas of expertise:
Model teams are facing increased efforts to move faster and perform more efficiently to deliver and support projects and programmes. They need high-quality frameworks, policies and procedures that meet regulatory standards and pass regulatory scrutiny. We can help you assess, perform gap analysis and roadmap development in these model-related areas.
Building a successful model that allows you to make confident business decisions, advance business strategies and achieve regulatory compliance can be a complex process. Our team has developed models to address a wide range of financial issues including credit risk, operational risk, market risk, and stress testing and forecasting.
Proper model validation is a must to mitigate model risk. Independent model validations play a key role in assurance that model risk is properly understood and well-managed. We have performed validations for numerous banking institutions and have validation models for multiple lines of business.
Undergoing a CCAR & DFAST review can be a rigorous process. Our experts have performed a large number of model validations and model developments for just this scenario. Our expertise spans all relevant business units and purposes, including models used to project credit losses, revenues, income, allowance, risk-weighted assets and more.
Today’s Internal Audit teams are facing the challenge of tracking more and more quantitative areas. Our highly qualified experts can provide your Internal Audit teams with in-depth support in areas such as data selection and processing, the model conceptual soundness review and performance testing, reporting and model use, and other complex areas.