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D. Ramadevi is an Assistant Professor in the Department of CSE (AI & ML) at Narsimha Reddy Engineering College, India. Her research interests include Artificial Intelligence, Deep Learning, and intelligent security systems.
The swift advancement of digital banking, mobile transactions, e-commerce, cloud technology, and Financial Technology (FinTech) has greatly enhanced the availability and effectiveness of financial services. Nonetheless, the growing dependence on digital platforms has exacerbated cybersecurity risks, such as identity theft, account hijacking, payment fraud, insider breaches, and illicit access to financial systems. Conventional authentication techniques, including passwords, Personal Identification Numbers (PINs), and One-Time Passwords (OTPs), are becoming progressively susceptible to phishing, credential compromise, brute-force assaults, and social engineering. Biometric authentication has surfaced as a resilient and accessible method by employing distinctive physiological and behavioural traits for identity confirmation. Technologies including fingerprint identification, facial identification, iris scanning, voice identification, palm vein verification, and behavioural biometrics offer robust safeguards against fraud while enhancing user convenience. Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Computer Vision, and Explainable Artificial Intelligence (XAI) significantly improve biometric systems via intelligent recognition, liveness detection, adaptive authentication, and ongoing surveillance. This chapter elucidates the principles, framework, artificial intelligence methodologies, applications, obstacles, and prospective research avenues of biometric fraud deterrence systems within the contemporary financial landscape.