Model risk is the sleeping giant of risk management. Risk, pricing, and performance models that financial institutions rely on can fall prey to errors. All models can only be mathematical approximations of reality and therefore have only limited accuracy and reliability.
Although this is a well-recognized fact, model risk management has not been a major risk management discipline until recently. The sense of complacency that led to an over-reliance on models in the run-up to the financial crisis has begun to dissipate. As a result, firms are now looking for systems to manage the risks associated with their models.
Increased regulatory requirements: Multiple regulators are making model risk management mandatory, including requirements under Solvency II, Basel 3, and Dodd-Frank. Additionally, regulators, including the OCC, Federal Reserve, and PRA are requiring firms to demonstrate evidence of controls and governance for models.
Stakeholder pressure: Shareholders and other stakeholders are demanding improved model risk management in response to losses caused by inaccurate or misused models. In particular, they are pressuring boards and senior management to take an increased role in model risk management.
Internal credibility: Errors in models are causing users to doubt their effectiveness and are creating a drive for improved model risk management within financial institutions.
Senior management involvement: Model risk management has not previously been seen as a strategic priority and has been implemented disparately with little or no aggregation. Senior management members need to lead enterprise-wide model risk management.
Mix of quantitative and qualitative risk management needed: Model risk management is difficult because it requires a mixture of quantitative (e.g. validation and testing) and qualitative measures (e.g. model use policies), which must be used in combination with one another.
End-to-end model risk management: To be effective, model risk management must encompass the full model development lifecycle and the full risk management lifecycle, from risk identification to risk control.
This report provides extracts from Chartis’s detailed report on model risk management published in June 2014 and highlights the capabilities of Oracle in this field. This report uses Chartis’s RiskTech Quadrant® to explain the vendor landscape. The RiskTech Quadrant® uses a comprehensive methodology of in-depth independent research and a clear scoring system to explain which technology solutions meet an organization’s needs. Chartis considers Oracle one of the leading vendors offering model risk management solutions.