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Fraud Detection books focus on the strategies, technologies, and practices used to identify, investigate, and prevent deceptive activity across industries such as banking, e-commerce, insurance, healthcare, and telecommunications. This category blends theory and hands-on guidance, covering fraud typologies, risk assessment, controls, and compliance, alongside analytical techniques like statistics, machine learning, anomaly detection, and network analysis. Readers will find case studies, forensic accounting methods, transaction monitoring, anti–money laundering and KYC concepts, identity theft and social engineering defenses, and guidance on governance, ethics, and model explainability. Titles range from practitioner manuals to data-science playbooks and investigative histories, serving analysts, auditors, investigators, risk managers, data scientists, and students seeking practical frameworks and tools to reduce losses and protect consumers and organizations.

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