A Novel Framework For Proactive Financial Wellness: The Cognitive-AI Expense Tracker With Predictive Analytics And Behavioral Nudging

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Authors: Prince Kumar, Amit Kumar, Prashant Pal
Cited by: 0

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.

Fields of Study & Subjects

Financial Literacy Pension Retirement Analysis Decision Support System Applications Decision-Making and Behavioral Economics

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
1 January 2026
Language
EN