Agentic systems are taking on tasks from cash positioning to FX execution. Hear how MassMutual and RSM are applying supervised autonomy in treasury: where it worked, where humans must stay in the loop, and what measurable outcomes they’re tracking. Discover how to vet, validate, and continuously supervise these agents: what to automate, what to escalate, and how to prove outcomes are explainable and reversible. You’ll leave with a playbook for safe autonomy in finance.

You will learn how to:

• Identify which treasury activities are ready for agentic autonomy (cash positioning, FX workflows, exception handling) versus which should remain human-controlled and define clear escalation triggers.

• Apply a practical validation and supervision framework to continuously monitor agent performance, manage drift, and ensure every recommendation and action are explainable and reversible.

• Establish the governance controls required to operationalize agentic AI in finance—policy guardrails, approval workflows, and audit-ready evidence—so automation scales safely across the organization.