Personal Expense Tracker Using AI

Abstract This research paper delves into the realm of artificial intelligence-driven expense tracker applications, exploring their historical progression, underlying technological frameworks, and practical utilization. Drawing from current literature, the study scrutinizes the limitations of existing systems and suggests improvements through the integration of advanced technologies such as OAuth for secure login, the employment of Firebase for data management, and the utilization of TensorFlow for predictive analytics. Furthermore, it introduces an innovative concept of a notification parsing system that can automatically retrieve transactional data from payment notifications to dynamically adjust daily budgets while upholding user privacy. This paper amalgamates various research methodologies to illustrate the transformative potential of AI within the realm of personal finance management. Keywords: Expense Tracker, Artificial Intelligence, Machine Learning, Budgeting, Privacy