AI is changing what's detectable, and what's exploitable. This session covers a practical framework for matching AI tools to signal type, the emerging attack surfaces (deep fakes, synthetic documents, identity spoofing) that are outpacing old detection methods, and a 90-day playbook and vendor-evaluation rubric to pilot your first AI-augmented fraud, risk, or security workflow.

Learning Objectives:

• Apply a framework for matching AI tools to signal type: recognizing how LLMs and traditional ML add value, and when to apply each.
• Identify emerging AI-driven attack surfaces (synthetic/deepfake documents, visual identity spoofing etc.) and understand why legacy detection approaches decay against them.
• Build a 90-day pilot plan, using a practical vendor-evaluation rubric, to launch one AI-augmented fraud, risk, or security workflow at your community bank.