Effective AI Model Risk Management
Managing Next Generation Models & Algorithms
AI and Gen AI are pushing the limits of traditional model risk management. If you’re responsible for MRM or model governance, you’ve probably felt it too: New risks, more complexity, and frameworks that weren’t built for this.
That’s why we hosted a webinar with TCS (TATA Consultancy Services), focused on how banks and insurers are adapting their MRM practices to keep pace with AI. In this industry practitioner roundtable, experts from TCS and Yields explore how leading financial institutions are adapting to these challenges, and what you can do to stay ahead.
What you'll learn
- How AI & Gen AI MRM Differs from Traditional MRM
- How AI & Gen AI MRM fits into the wider AI governance landscape
- Why engineering is now a core pillar of effective model risk oversight
- Practical examples from the field: what works, what doesn’t
- How Yields and TCS are partnering to address AI MRM in Practice
About the
Speaker(s) /
Jos Gheerardyn is the co-founder and Chief Executive Officer (CEO) of Yields. Prior to his current role, he worked as both a manager and an analyst in the field of quantitative finance. With nearly 20 years of experience, he has worked with leading international investment banks and start-up companies. Jos is the author of multiple patents that apply quantitative risk management techniques to the energy balancing market. Jos holds a PhD in superstring theory from the University of Leuven.
Marc Taymans has over 25 years of invaluable experience in the field. He co-founded Risk Dynamics and led its growth until its acquisition by McKinsey in 2016. He’s a master in model risk management, extending his expertise across continents.
