Loading article...
Loading article...
Stream/Area:
-
Subject:
-
Paper ID:
IJSREM53660
Volume:
9 |
11 |
Nov 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
In today’s fast-paced digital world, effective personal finance management has become a major challenge for individuals due to multiple income sources, diverse expenses, and limited financial awareness. Most existing tools only provide basic expense tracking and lack personalization, automation, and intelligent guidance. To address these limitations, this project proposes an AI-Driven Personal Finance Management System that combines rule-based logic and machine learning (ML) techniques to simplify financial planning and decision-making. The system allows users to record income and expenses, categorize them automatically, predict future budgets, and receive personalized investment recommendations such as SIPs, Fixed Deposits (FDs), Recurring Deposits (RDs), and Mutual Funds. Using machine learning models like Linear Regression, the system forecasts future spending trends, while rule-based eligibility checks help determine suitable investment options. Developed using Python, Flask, and scikit-learn, the proposed system provides a user-friendly dashboard with secure login, real-time alerts, and savings goal tracking. It enhances financial literacy by delivering data-driven insights and promoting better money management habits. The project demonstrates how artificial intelligence can transform personal finance management from manual, time-consuming processes into automated, intelligent, and personalized financial assistance for every user.
KEYWORDS
Publication Date
10/10/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
Documents
Article Views
0
Total views since publication
PDF Downloads
12
Total downloads since publication
Geographic Reach
5
Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.
Plagiarism Screening
This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.
Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
Related research in the same subject area
Loading similar articles...