Every financial firm is deploying AI agents. Very few can answer the question regulators are starting to ask: "How do you know what your agent did — and why?"
This session presents the Ethics-to-Control Trace Graph (ECTG), a governance architecture designed specifically for agentic AI operating in regulated financial environments — wealth management, capital markets, and enterprise securities operations. ECTG creates a live, executable mapping between AI ethics principles and operational control points, transforming agent governance from policy documents into auditable runtime behavior.
Drawing on research aligned with the emerging IEEE 3410-2025 Model Risk Management standard for GenAI in finance, this talk demonstrates how enterprise architects and AI engineers can instrument their agent pipelines for explainability, control, and regulatory defensibility — without sacrificing the autonomy that makes agents valuable.
Attendees will leave with: a working ECTG design pattern, a checklist for audit-ready agent deployments, and a framework for mapping agent actions to SEC/FINRA compliance obligations. Built for practitioners who are shipping agents into production, not just theorizing about them.