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Automated Expense Categorization and Anomaly Detection using Customized Deep Learning Models

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Volume-10 | Issue-5

Last date : 27-Oct-2026

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Automated Expense Categorization and Anomaly Detection using Customized Deep Learning Models


Pratham Choudhari



Pratham Choudhari "Automated Expense Categorization and Anomaly Detection using Customized Deep Learning Models" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications, March 2026, pp.431-440, URL: https://www.ijtsrd.com/papers/ijtsrd101634.pdf

This paper presents the development and evaluation of "Finance Tracker," a web-based personal finance management system designed to automate and streamline financial tracking, budgeting, and goal setting. Leveraging modern web technologies, the system offers seamless recording, monitoring, and analysis of financial transactions, ensuring scalability, reliability, and accessibility across various devices. Finance Tracker addresses the prevalent inefficiencies and fragmentation found in existing personal finance tools by unifying essential services such as income and expense logging, transaction categorization, and financial goal management. The system provides an intuitive graphical user interface, real-time updates, and insightful reports, empowering users to make informed financial decisions. Our implementation successfully demonstrates core functionalities including robust user authentication, budget planning, transaction tracking, secure document storage, and efficient notification services. Through a comprehensive evaluation, Finance Tracker exhibits strong performance in data retrieval and synchronization, proving its feasibility as a scalable and efficient solution for digital finance management with significant potential for future expansion.

Finance Tracker, Personal Finance Management, Web-Based Application, Budgeting, Expense Tracking, Financial Planning, API Integration, Cloud-Native, UI/UX


IJTSRD101634
Special Issue | Smart Innovations in Computer Science and Applications, March 2026
431-440
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

International Journal of Trend in Scientific Research and Development - IJTSRD having online ISSN 2456-6470. IJTSRD is a leading Open Access, Peer-Reviewed International Journal which provides rapid publication of your research articles and aims to promote the theory and practice along with knowledge sharing between researchers, developers, engineers, students, and practitioners working in and around the world in many areas like Sciences, Technology, Innovation, Engineering, Agriculture, Management and many more and it is recommended by all Universities, review articles and short communications in all subjects. IJTSRD running an International Journal who are proving quality publication of peer reviewed and refereed international journals from diverse fields that emphasizes new research, development and their applications. IJTSRD provides an online access to exchange your research work, technical notes & surveying results among professionals throughout the world in e-journals. IJTSRD is a fastest growing and dynamic professional organization. The aim of this organization is to provide access not only to world class research resources, but through its professionals aim to bring in a significant transformation in the real of open access journals and online publishing.

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