International Journal of Science, Engineering and TechnologyAuthors: Prince Kumar, Amit Kumar, Prashant Pal
Abstract: Traditional expense trackers function as passive digital ledgers, requiring significant manual input and offering limited, retrospective insights. This paper proposes a novel framework for an AI- powered expense tracker that transcends this reactive model. The proposed system, termed the Cognitive Financial Assistant (CFA), leverages a multi-modal architecture integrating Natural Language Processing (NLP) for seamless transaction logging, Computer Vision (CV) for receipt digitization, and a Predictive Behavioral Engine to forecast future spending and financial stress. Its core innovation lies in its Proactive Nudge Engine, which uses behavioral economic principles to deliver context-aware, personalized interventions aimed at improving financial decision-making in the moment. We detail the system's architecture, present a proof-of-concept implementation, and analyze preliminary user study data (N=150) suggesting a 23% reduction in impulsive spending and a 31% increase in user-reported financial confidence compared to control groups using standard trackers. This research establishes a new paradigm for personal financial tools: from passive record-keepers to active, cognitive partners in financial wellness.
