Keywords
agent-based artificial intelligence fraud detection, multi-agent systems financial fraud detection, AI fraud prevention techniques, blockchain in fraud detection systems, real-time fraud detection digital payments, deep learning fraud detection framework, reinforcement learning fraud detection agents, cloud security AI threat detection, financial fraud typology analysis, e-commerce fraud detection AI, digital identity fraud prevention, intelligent fraud detection systems, adaptive AI cybersecurity systems, currency recognition fraud detection AI, public sector fraud detection AI, scalable fraud detection architecture, ethical AI in fraud prevention, regulatory compliance AI systems, transactional fraud detection models, autonomous agents cybersecurity systemsAgent-Based Artificial Intelligence in Fraud Detection: Strategies for Building Secure Self-Governing Systems
authored by: C. Kishor Kumar Reddy, Anindya Nag, Shikha Khullar & Sarika SLength: 229 mm | Breadth: 34.7 mm | Height: 152 mm | Imprint: NIPA | Weight: GMS
This book will be available from 09-Aug-2026
Agent-Based Artificial Intelligence in Fraud Detection explores advanced AI-driven approaches for identifying and preventing fraud in modern digital ecosystems. The book presents agent-based artificial intelligence, multi-agent systems, blockchain integration, and deep reinforcement learning as powerful tools for adaptive and real-time fraud detection. It covers financial fraud, public sector applications, cloud security, currency recognition, and distributed decision-making systems.
Through case studies and practical frameworks, it highlights scalability, interoperability, ethics, and regulatory challenges in deployment. The work provides a multidisciplinary roadmap for researchers, policymakers, and cybersecurity professionals to build secure, transparent, and resilient digital financial systems in an evolving technological landscape.
Chapter 1 Foundations and Principles of Agent-Based Artificial Intelligence for Enhancing Fraud Detection Mechanisms in Complex Financial Ecosystem
Chapter 2 Comprehensive Analysis of Fraud Typologies & Behavioural Patterns in Financial, E-Commerce, and Digital Identity Domains
Chapter 3 Design and Implementation of Multi-Agent Architectures for Scalable and Adaptive Data Fraud Detection Systems
Chapter 4 Integrating Blockchain Technology with Agent-Based AI to Ensure Data Integrity, Transparency, and Trust in Fraud Prevention Systems
Chapter 5 Applications of Agent-Based AI in Public Sector Fraud Detection: Enhancing Transparency and Accountability in Government Services
Chapter 6 Real-Time Detection of Transactional Fraud in Digital Payment Platforms through Intelligent Multi-Agent Systems
Chapter 7 Deep Learning Framework with Agent-Based Currency Recognition in Fraud Detection to Empower the Visually Impaired
Chapter 8 Applying Deep Reinforcement Learning to Develop Autonomous Agents Capable of Continuous Adaptation in Dynamic Fraud Environments
Chapter 9 Advanced Coordination, Negotiation, and Conflict Resolution Techniques Among Autonomous Agents in Distributed Fraud Detection Networks
Chapter 10 AI in Cloud Security: Threat Detection, Compliance Monitoring, and Intelligent Response Automation
Chapter 11 Addressing Scalability, Latency, and Interoperability Challenges in Real-World Deployments of Agent-Based Fraud Detection Systems
Chapter 12 Navigating Ethical, Legal, and Regulatory Challenges in the Deployment of Agent-Based AI Systems for Fraud Prevention in Financial Services
Chapter 13 Challenges, Opportunities, and a Research Roadmap for the Next Generation of Agent-Based AI Solutions in Fraud Prevention