Model Risk Management in the Age of AI and a Changing Regulatory Environment

How has the definition of ‘model risk’ expanded since the early 2010s, and what new categories of risk do model risk teams now have to oversee that simply did not exist when frameworks like SR 11-7 first emerged?

Model Risk has had to adapt along with the changes in the banking industry. With the adoption of AI and large language models in business, Model Risk must stay adaptable and intentional to maintain effective governance frameworks for emerging model types.

With the rapid adoption of AI, machine learning, and large language models across banking operations, how should model risk teams rethink traditional validation approaches that were originally designed for deterministic financial models?

Model risk teams have had to move beyond the traditional toolbox of statistical testing to include AI specific risks.

Generative AI models require a deeper dive into data accuracy and controls, explainability of outputs, and evaluation of performance that traditional financial models do not require.

Fortunately, for most banks, the burden is not entirely on the MRM teams – we must work along-side other subject matter experts in the Bank, like Data Management/Governance and Information Security/Technology to help ensure the overall governance of AI Models are effectively managed.

Many banks built their model risk functions around quantitative finance expertise. As model usage expands into areas like fraud detection, cybersecurity, and AI-driven decision tools, what new skills and capabilities are most urgently needed inside model risk teams today?

The technical and mathematical skills are in place, and transferrable to evolving models and technologies – at least for Model Risk Management.

I believe that being adaptable, curious, and eager to work with others is essential in the bank today. Establishing proactive working relationships throughout the organization is essential to ensure that each new model is accurately tracked and effectively governed.