Explore how agentic AI can support financial compliance and risk management while keeping regulatory judgment and human oversight central. This course introduces large language models (LLMs), prompt engineering, fine-tuning, multimodal AI, vector databases, and agentic retrieval-augmented generation (RAG) for evidence-grounded compliance workflows.

Designed for compliance, risk, audit, and fintech professionals, the course connects AI capabilities to practical implementation decisions. You'll compare prompting, model adaptation, and agentic automation for financial compliance tasks, then map a multimodal RAG workflow with vector retrieval and an auditable evidence trail. You'll also examine AI-assisted legal and corporate workflows, assess data readiness and integration needs, and choose between state-machine orchestration and autonomous planners. Evaluate model drift, regulatory exposure, monitoring, and human review checkpoints in predictive compliance scenarios. By the end, you'll be able to identify suitable AI approaches and their limitations, assess automation readiness, justify orchestration choices, and recommend governance controls. What sets this course apart is its focus on traceability, cost awareness, and responsible automation—not replacing human compliance judgment.