Governance and Risk Management of AI and ML models
Model risk management isn’t new to Risk and Compliance teams, but AI and machine learning models are. AI and ML models require stringent controls and governance over the processes used to operate them and their outcomes. Creating an automated ModelOps process allows firms to grow and scale their AI initiatives while enforcing the governance, business and risk controls that are not only expected, but required.Join us as we assess how model risk management teams can enhance model operations processes to ensure regulatory, compliance and risk requirements and controls are enforced and auditable. Webinar session includes:
- Best practices for including MRM controls in the model life cycle
- Automating model risk management processes for increased efficiency
- Bringing together all three lines of defense to centralize processes and enable increased coherence with a centralized production model inventory
- Managing differences in quality and controls of different model types
- Overcome the complexity of monitoring AI and ML models across business units
Speakers:
Dave Trier, VP of Product, ModelOp
Jacob Kosoff, Head of Model Risk Management and Validation, Regions Bank
Menglin Cao, SVP, Head of AI NLP Model Development, Wells Fargo
Andreza Barbosa, Head of Model Risk Governance, Goldman Sachs
