This ebook provides a comprehensive, implementation-focused guide to designing, deploying, and optimizing fraud prevention that is explicitly tuned for AI shopping agents. You will learn how to preserve conversion and customer experience while rigorously blocking bad actors, minimizing false declines, and aligning risk controls with autonomous buyer behavior. The playbook covers strategy, data architecture, modeling, decisioning, operations, measurement, and compliance with step-by-step frameworks and ready-to-use templates. Chapters include: Understanding AI Shopping Agents And Fraud Dynamics; Traffic Taxonomy And Risk Personas For Agents And Humans; Signal Architecture: Device Intelligence, Behavior, And Graph Data; Agent Identification: Attestation, SDKs, And API-Level Controls; Feature Engineering And Model Design For Agent-Aware Detection; Decisioning Orchestration And Dynamic Friction Strategies; Human-In-The-Loop Review, Operations, And Playbooks; Measurement: KPIs, Experimentation, And False Decline Reduction; Implementation Roadmap, Compliance, And Vendor Selection.