In episode 13 of the Responsible AI Report, Patrick speaks with Christophe Rougeaux about the importance of responsible AI and model risk management in the financial sector. They discuss how banks can expand their model risk management capabilities to include AI oversight, the challenges of building specialized expertise in risk management teams, and strategies for accelerating AI deployment while maintaining robust risk management practices. Christophe emphasizes the need for a holistic understanding of the AI lifecycle, continuous improvement, and a supportive culture for safe AI implementation.
Takeaways
- Financial institutions must prioritize dedicated governance teams for AI.
- Model risk management should include new risk dimensions like bias and cybersecurity.
- Talent acquisition in AI is a challenge for banks competing with tech companies.
- A holistic view of the AI lifecycle is essential for speed to market.
- Continuous improvement is necessary for effective AI processes.
- Change management is crucial for implementing new practices in banks.
- Building specialized expertise in risk management is vital for AI validation.
- Communication from leadership is key to fostering a culture of safe AI.
- Banks need to adapt their operating models to optimize AI deployment.
Learn more at:
https://www.linkedin.com/in/christopherougeaux/
Christophe Rougeaux is an expert in analytics who helps global organizations ensure effective and sustainable management of their analytics, through robust oversight governance. Christophe previously co-led McKinsey's Model Risk Management service line. Since 2024, he is a Model Risk Management Executive at TD Bank Group where he is heading the model validation of the non-retail portfolio and leading strategic AI/Model Governance initiatives.
Visit our website at responsible.ai
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