Developing an AI-Powered Voice Assistant for an iOS Payment App

This thesis investigates the potential of an AI-powered voice assistant in simplifying and securing financial transactions in a Peer-to-Peer (P2P) payments application, integrating cutting-edge Machine Learning technologies on-device such as BERT for text classification and a custom Dialogue State Tracking mechanism. Through a meticulous design and development process, the study explores the integration of voice commands into a real iOS app to facilitate in-app operations, prioritizing user privacy through local data processing, and enhancing user interaction and accessibility via an intuitive UI/UX design leveraging the novel SwiftUI framework. The research conducts a thorough evaluation of the system’s performance, focusing on user experience, security, and the accuracy of voice and language recognition capabilities. The analysis reveals significant results in operational efficiency and user satisfaction, highlighting the voice assistant’s role in advancing digital payment solutions. The work concludes with a critical analysis of the findings, discussing the implications for future AI applications and proposing avenues for further research in voice-enabled technologies for financial services.