Deepfake Fraud in Digital Banking

Deepfake technology is transforming the digital landscape while creating new and complex threats to banking security, customer identity verification, and financial fraud prevention. Deepfake Fraud in Digital Banking explores how artificial intelligence can be used to detect and prevent fraudulent activities involving AI-generated faces, cloned voices, manipulated identities, and suspicious financial transactions. This book examines the growing challenges faced by digital banks and financial institutions as synthetic media becomes increasingly sophisticated. It explores the potential of multimodal artificial intelligence, combining facial analysis, voice recognition, behavioural patterns, and transaction-related signals to strengthen fraud detection systems. The book also discusses explainable AI, responsible model development, privacy considerations, and the importance of reliable identity verification. With a focus on emerging financial technologies and the evolving digital banking environment, this work connects theoretical concepts with practical applications in cybersecurity and financial risk management. It also highlights the importance of developing transparent, adaptable, and trustworthy AI systems that can support banking professionals in identifying suspicious activity and protecting customers. Designed for students, researchers, fintech professionals, banking practitioners, and cybersecurity enthusiasts, this book provides an introduction to the challenges and opportunities associated with AI-driven fraud prevention. It aims to contribute to the broader discussion on building safer, more resilient, and more trustworthy digital financial services. Important: Ensure that the final manuscript actually covers the topics described above. The description should accurately reflect your finished book.