At first glance, financial risk management might appear to have little in common with engineering Model-Based Design. Financial risk management is data-centric, highly dimensional, and deployed into software systems. Engineering models typically draw on fewer, highly coupled inputs, often embedded in physical and electronic hardware.

In both cases, validated, verified fit-for-purpose models are key, extending product lifecycles amidst extreme scenarios, albeit across different time horizons. Good processes mitigate against risks such as costly trading errors or compliance charges in finance, while high integrity requirements have long dominated engineering. Fit-for-purpose models also increase functionality and drive progress, enabling more differentiating features on a car, device, or plane, and facilitating new investment, lending, and liquidity-creating products.

In this talk, Ray discusses how financial risk technology stacks are evolving in response to regulatory and geopolitical change, bigger datasets, new modelling techniques, and rapidly changing development cultures. He also assesses the critical importance of good model development and implementation, and what insights he has taken from Model-Based Design in other industries.