Agentic AI for Fraud Detection

This book explores how intelligent software agents can revolutionize fraud prevention in financial systems. These agents operate independently, learning, reasoning, and making real-time decisions to secure digital transactions. The book begins with foundational principles of agent-based AI and progresses to system architecture, agent coordination, and adaptive behaviour in complex environments. It emphasizes secure data handling, ethical compliance, and explainable decision-making. Key topics include intelligent sensing, privacy-preserving techniques, and dynamic risk analysis. Each chapter builds conceptually, integrating theory with practical case studies that demonstrate how agentic systems detect anomalies and mitigate threats. Readers gain insight into designing robust, ethical, and autonomous fraud detection frameworks. This book bridges academic depth with industry relevance and equips readers to build secure, intelligent systems that protect financial ecosystems from evolving fraud risks.