Customer Authentication in Mobile Banking-MLOps Practices and AI-Driven Biometric Authentication Systems

Abstract

The intersection of customer demands, security, and innovative services in the diverse mobile banking space calls for continuous adaptation by financial institutions. Small challenges such as on-demand customization and scalability are addressed through merging technologies, which is important for smaller institutions undergoing IT modernization. Despite the slow pace of ML adoption in banking, those leveraging ML experience increased their success in this competitive landscape. This article looks at the role of MLOps in overcoming challenges posed by evolving data volumes and complexities in deploying and developing ML models within financial institutions. As online banking authentication holds an important role in securing financial transactions, a historical overview of authentication methods, from biometrics to tokens, creates a chance to delve into the transformative potential of AI-driven biometric authentication. With the increase in mobile banking fraud, the need to safeguard sensitive customer data is met with radical technology. The article examines the varied authentication methods employed in online banking applications and depicts the potential of biometrics, majorly behavioral biometrics, to improve security and user experience. The rise of online mobile banking systems introduces both convenience and security concerns, thus prompting a closer look at the adoption of biometrics to mitigate fraud risks and improve the seamless authentication process throughout the user session. Customers increasingly demand quick and easy mobile payments, so biometrics has become a key fraud prevention and detection solution. By running in the background and eliminating setup authentication and risk-based authentication, behavioral biometrics significantly reduces fraud, thus addressing the limitations of traditional authentication methods like email verification and passwords. The article navigates the evolving mobile banking security space, highlighting the important role of MLOps and the potential of AI-driven biometric authentication in meeting the dual objectives of improving customer experience and strengthening severity protocols.