International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Personal Finance Tracker with Budget Recommendation AI |
|---|---|
| ABSTRACT | Personal finance management is an essential life skill, yet many individuals lack structured tools that provide personalized budgeting and saving guidance. Most existing trackers operate as passive logging systems without analytical intelligence. This paper presents a comprehensive Personal Finance Tracker with an AI-driven Budget Recommendation System, designed to automate expense management, visualize spending behavior, and provide customized saving suggestions. The system enables users to add income, log expenses, generate expense usage charts, download expense reports, set saving goals, and receive intelligent saving recommendations based on financial patterns. The AI module uses heuristic scoring, trend analysis, and lightweight predictive techniques to identify overspending patterns and recommend optimal monthly savings and category limits. The system was evaluated with diverse financial data sets to ensure accuracy and usability. Results indicate that the integrated AI model improves user decision-making, reduces unnecessary spending, and increases saving consistency. This paper provides methodological depth, architectural details, and experimental evaluations to demonstrate the system’s impact and scalability. |
| AUTHOR | V ZOTHANSIAMA, LALRINDIKA, AARYA DHURI |
| VOLUME | 176 |
| DOI | DOI: 10.15680/IJIRCCE.2025.1311102 |
| pdf/102_Personal Finance Tracker with Budget Recommendation AI.pdf | |
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