Abstract
<jats:p>Fraud has become increasingly sophisticated in the digital era, exploiting advancements in technology, interconnected systems, and human vulnerabilities. Traditional fraud detection methods often struggle to identify emerging threats in real time, creating a need for more intelligent and adaptive solutions. Intelligent Fraud Detection Systems Using AI, Machine Learning, and IoT: A Behavioral and Psychological Analytics Approach explores the integration of Artificial Intelligence (AI), Machine Learning (ML), and Internet of Things (IoT) technologies to develop proactive and robust fraud prevention frameworks. This work emphasizes the importance of behavioral and psychological analytics in understanding user patterns, detecting anomalies, and predicting fraudulent activities before significant damage occurs. By combining technological innovation with insights into human behavior, the book presents a multidisciplinary perspective on modern fraud detection. It serves as a valuable resource for researchers, academicians, industry professionals, and policymakers seeking to enhance security, trust, and resilience in digital ecosystems while addressing the evolving challenges of fraud in an increasingly connected world.</jats:p>