AI is transforming financial services—but trust, transparency, and auditability remain critical barriers to adoption. This masterclass explores how Agentic AI can be deployed in high-stakes financial environments, from portfolio optimization to trade execution, while maintaining rigorous governance and operational safeguards. Drawing on real-world research and deployment experience, participants will learn how to architect AI systems that are not only powerful, but also explainable, compliant, and trusted by institutional stakeholders.

What You’ll Learn

• How to design Agentic AI systems for real-time decision-making in trading, onboarding, and advisory workflows.
• Techniques for integrating AI with financial APIs, data lakes, and legacy infrastructure to enable seamless orchestration.
• Strategies for implementing model governance frameworks that ensure explainability, auditability, and human-in-the-loop escalation.

Key Takeaways:

• A reference architecture for regulated Agentic AI systems tailored to financial services.
• Lessons learned from deploying AI in institutional finance—including what works, what fails, and why trust is the ultimate currency.
• A governance toolkit for building MRI-style model diagnostics to scan and validate AI behavior at scale.
• Why This Matters Despite the hype, most AI use cases in finance fail to deliver real impact due to lack of trust, transparency, and operational integration. This session equips financial leaders, AI strategists, and technologists with the frameworks needed to build AI systems that are not only innovative—but also usable, scalable, and regulator-ready.

Who Should Attend:

Financial professionals, AI strategists, and innovation teams working in:

• Asset Management & Trading
• Banking & FinTech
• Risk & Compliance
• Financial Infrastructure & Data Platforms