AI-Enhanced Secure Mobile Banking System Utilizing Multi-Factor Authentication (original) (raw)
The increasing reliance on mobile banking has significantly heightened the need for robust security mechanisms to protect users from unauthorized access and fraudulent activities. As mobile banking continues to grow in popularity, safeguarding financial transactions and personal data becomes a top priority. This paper introduces an AI-enhanced secure mobile banking system that leverages Multi-Phase Authentication (MPA) to strengthen the authentication process. In this system, artificial intelligence is integrated with traditional authentication methods, creating a dynamic framework that assesses the risk level associated with each user interaction. Based on this real-time risk assessment, the system adjusts the authentication requirements, making them more stringent when higher risks are detected and more lenient when the risk is lower. This adaptive mechanism not only enhances the security of mobile banking by providing multiple layers of protection but also improves the user experience by reducing unnecessary authentication steps that can cause frustration and delay. The proposed system's effectiveness is validated through a series of simulations and case studies, which demonstrate significant improvements in key security metrics. These include a marked reduction in instances of fraud and lower false positive rates, which indicate that the system can accurately distinguish between legitimate and suspicious activities without imposing undue burden on users. Overall, the results of this study highlight the potential of AI-enhanced multi-phase authentication to provide a scalable and user-friendly solution for secure mobile banking. This approach represents a promising direction for the future of digital financial services, offering a balance between rigorous security and seamless user experience.
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