Protiviti’s Model Risk & Risk Analytics practice builds and validates quantitative risk assessment systems, while also assisting client management understand the value - and limitations - of their models. The outcomes of work are better informed business decisions; improved operational control of the business; and alignment with regulatory requirements.
Models are simplified and idealised representations of the real world and are prone to errors when built or applied incorrectly. Furthermore, as models are driven by assumptions and limited data inputs, which require a degree of human interpretation, model risk is inescapable. The increasingly widespread use and reliance on quantitative models creates the requirement to consider the degree to which model risk is understood, monitored and managed. Regulators mandate model validation under such pronouncements as the OCC 2011-12/FRB SR 11-7 regulations in the US, variations of which are increasingly being adopted internationally. Other key stakeholders, such as auditors, investors and rating agencies, also require improved governance over the ever-expanding inventory of quantitative models and their associated usage.
Protiviti’s Model Risk team consists of quantitative analysts with experience developing, validating and auditing all types of quantitative models, including those covering:
Also covered is the validation of financial crime detection models, such as anti-money-laundering and fraud detection systems.
The practice works with a broad spectrum of clients and also leverages other Protiviti practices covering Risk & Compliance, Internal Audit, Information Technology, and Business Process Re-engineering.
Our independent, holistic, validation process helps control model risk, prevents losses associated with such risk and enhances key stakeholders' understanding of analyses and decisions based on such models. We also help organisations manage their portfolio of model risks by assessing, designing and implementing model governance programmes.