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Dr. Mythily C. V. is an Assistant Professor in the Department of Mathematics at Erode Sengunthar Engineering College, India. Her academic interests include applied mathematics, computational intelligence, and data analytics.
The swift expansion of digital banking, e-commerce, mobile transactions, and cloud-oriented financial services has heightened the necessity for secure and intuitive authentication systems. Conventional authentication techniques, including passwords, Personal Identification Numbers (PINs), and One-Time Passwords (OTPs), are becoming progressively susceptible to phishing, credential compromise, replay assaults, and social manipulation. Biometric authentication has surfaced as a dependable substitute by using distinct physiological and behavioural traits of individuals. Facial Expression Analysis (FEA) is a biometric technology that improves traditional facial recognition by integrating dynamic facial movements and emotional expressions to authenticate users and identify spoofing attempts. Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Computer Vision, and Behavioural Analytics provide precise real-time recognition of face expressions for reliable user verification. This chapter delineates the principles, framework, methodology, applications, problems, and prospective research avenues of facial expression analysis for intelligent and secure user identification inside digital financial environments.