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RupeeX - Personal Finance Tracker


EOI: 10.11242/viva-tech.01.09.14

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Citation

Devansh Choukekar, Chinmay Sakhare, Shravni Gharat, Anjana Kamble, Prof Poonam Jadhav, " RupeeX – Personal Finance Tracker ", VIVA-IJRI Volume 1, Issue 9, Article 14, pp. 1-7, 2026. Published by Computer Engineering Department, VIVA Institute of Technology, Virar, India.

Abstract

RUPEEX is a smart personal finance tracking system designed to help individuals manage their monthly income, expenses, and savings efficiently. With the increasing complexity of personal financial planning and rising living costs, manual expense tracking has become inefficient and error-prone. RUPEEX automates expense recording, categorization, budget analysis, and future expense prediction using data-driven techniques. The system allows users to track spending across multiple categories such as food, shopping, travel, bills, and entertainment. It provides monthly summaries, visual insights, and predictive analytics to estimate upcoming month expenses based on historical spending patterns. An integrated AI-based recommendation module offers personalized financial suggestions to help users optimize savings and reduce unnecessary expenditures. By utilizing a centralized database, intelligent analytics, and user-friendly interfaces, RUPEEX improves financial awareness, promotes disciplined spending habits, and supports informed financial decision-making. The system is suitable for individuals, students, and professionals seeking effective personal finance management.

Keywords

- Personal Finance Tracker, Expense Categorization, Budget Management, Financial Analytics, Expense Prediction, AI-Based Financial Recommendation.

References

  1. R. Shirke, A. Sabde, P. Swami, and R. Chavan, “Budget Buddy: An AI-Powered Personal Finance Management System”, International Journal of Scientific Innovation in Engineering, vol. 2, no. 11, pp. 93–98, Nov. 2025.
  2. J. Kumar, A. Vishwakarma, N. Sainy et al., “Personal Finance Manager with Predictive Analytics Using LSTM for Enhanced Financial Decision Making”, International Journal of Research – GRANTHAALAYAH, vol. 12, no. 5, pp. 156–169, May 2024.
  3. R. Kharat, S. Solapurkar, A. Tikkas et al., “A Smart AI-Based Personal Finance Assistant: A Multi-Model Approach for Expense Categorization, Budgeting, Forecasting and Anomaly Detection”, International Journal for Research in Applied Science and Engineering Technology (IJRASET), 2025.
  4. P. Sahu, A. Pradhan, A. P. Nathan et al., “AI Expense Tracker”, International Journal for Research in Applied Science and Engineering Technology (IJRASET), 2025.
  5. Deepthi C. G., J. J. Shetty, I. B. Shreeya et al., “AI-Powered Finance Management Platform”, International Journal for Research in Applied Science and Engineering Technology (IJRASET), 2025.
  6. K. Aajad, N. Kumar, A. Rajput et al., “FINBOT – An AI-Integrated Expense Monitoring and Financial Analytics Platform”, International Journal of Computer Sciences and Engineering, vol. 13, no. 11, pp. 37–44, Nov. 2025.
  7. T. Warin and A. Stojkov, “Machine Learning in Finance: A Metadata-Based Systematic Review of the Literature”, Journal of Risk and Financial Management, vol. 14, no. 7, 2021.
  8. L. Vancsura, T. Tatay, and T. Bareith, “Navigating AI-Driven Financial Forecasting: A Systematic Review of Current Status and Critical Research Gaps”, Forecasting, vol. 7, no. 3, 2025.
  9. “The Role of Artificial Intelligence in Financial Forecasting: A Systematic Literature Review”, Accounting Studies and Tax Journal (COUNT), 2024.
  10. S. Aishwarya and S. Hemalatha, “Smart Expense Tracking System Using Machine Learning”, Proceedings of the 1st International Conference on Artificial Intelligence for Internet of Things (AI4IoT), pp. 634–639, 2023.