Model Risk Management: Using an infinitely scalable stress testing platform for effective model verification and validation
Model risk and the importance of model risk management has gotten significant attention in the last few years. As financial companies increase their reliance on quants and quantitative models for decision making, they are increasingly exposed to model risk and are looking for ways to mitigate it. The financial crisis of 2008 and various high profile financial accidents due to model failures has brought model risk management to the forefront as an important topic to be addressed. Many regulatory efforts (Solvency II, Basel III, Dodd-Frank etc.) have been initiated obligating banks and financial institutions to incorporate formal model risk management programs to address model risk.
In this talk, we will discuss the key aspects of model verification and validation and introduce a novel approach to do stress and scenario tests leveraging parallel and distributed computing technologies and the cloud. The platform leverages cloud based technologies to run stress tests on a massive scale without having to invest in fixed in-house architectures. Through a case study, we will illustrate best practices for stress and scenario testing for model verification and validation. These best practices meant to provide practical tips for companies embarking on a formal model risk management program or enhancing their model risk methodologies to address the new realities.