ISB&M College of Engineering, Pune
Let’s be real—figuring out your finances is a big deal, whether you’re just trying to keep your personal budget in check or running a business. You need a solid grip on cash flow, and the old-school ways of tracking expenses (think pen, paper, or clunky spreadsheets) are kind of a mess—they take forever and it’s way too easy to screw up. So, this paper’s all about a cool new tool: a web-based, AI-powered Expense & Budget Tracker that does the heavy lifting for you. It automatically tracks your spending, sorts everything into neat little categories, and spits out reports that actually make sense. They built it with stuff like PHP 5.6.2, MySQL, HTML, CSS, and JavaScript, and it grabs transaction info straight from your digital payment apps. The whole point is to make budgeting less of a chore—you get your expenses broken down, handy financial summaries, and even some predictions about where your money’s headed. The study digs into whether this thing really helps people get their financial act together. Down the road, they’re thinking about adding smarter AI to guess your future spending and hooking it up with more financial tools, like they talk about in [1] and [2].
BACKGROUND
keeping track of your cash these days is a total headache everything’s digital now, and it’s like your money’s playing hide-and-seek with you. Tons of folks are struggling to figure out where their bucks are going, and next thing you know, they’re blowing through their budget or just drowning in financial chaos. There are some money apps out there, yeah, but most of them are a pain. you’ve got to manually punch in every coffee you buy, or they don’t even connect properly to all the payment stuff you use. Singh [5] says the trick is getting those payment apps to team up perfectly with budgeting tools.
1.2 Problem Statement
The absence of an automated financial tracking solution that directly captures transactions from digital payment platforms creates a gap in efficient cash flow management. Users often rely on bank statements or third-party apps that require manual input, leading to inaccuracies and time-consuming processes. Research by Lee et al. [10] highlights the need for user-centered design in financial applications to improve user experience and minimize input errors.
OBJECTIVES
This study aims to develop a web-based AI Powered Expense & Budget Tracker that:
- Automates the retrieval and categorization of digital-transactions.
- Provides real-time expense insights through dynamic-dashboards.
- Enhances financial planning with budget-setting features.
- Stores transaction data securely in a MySQL database for analysis.
1.4 Scope
The system targets individual users and small businesses needing automated financial tracking. It primarily focuses on digital payment transactions, with potential expansion to other payment platforms and bank accounts. As discussed in Kumar and Singh [8], future improvements can include AI-driven forecasting models to predict financial trends and enhance budgeting capabilities.
LITERATURE REVIEW
There are some solid personal finance apps out there—like Mint, YNAB, and GoodBudget—that do a decent job helping people manage their budgets. But here’s the catch: they usually depend on you typing in your expenses by hand or linking up with your bank, and they don’t directly track transactions from digital payment platforms. Studies on automating expense categorization show it’s a big deal for cutting down on financial slip-ups, yet not many tools fully connect with all the payment systems people use these days. Gupta [2] points out that digital payment platforms are quickly turning into a goldmine of financial info for users, but most budgeting apps still haven’t figured out how to tap into that smoothly.
METHODOLOGY
3.1 System Architecture
The proposed system is built using:
- Backend: PHP 5.6.2, MySQL database
- Frontend: HTML, CSS, JavaScript
- Data Processing: Automated extraction of transaction data from various digital payment platforms
- Security: Encrypted database storage for transaction details
3.2 Workflow
1. User Registration & Authentication: Secure login with credentials.
2. Transaction Import: Automatic retrieval of digital payment transactions using API or data scraping.
3.Categorization: Assigning transactions to predefined expense categories (e.g., groceries, bills).
4. Budgeting Module: Allowing users to set financial goals and track spending.
5. Report Generation: Visualization of spending trends via charts and reports.
3.3 System Diagrams
- DFD (Data Flow Diagram): Illustrates data movement from user inputs to database storage.
DFD (Level 0)
DFD (Level 1)
A visual map showing how data moves through the system, from input to processing to output.
ERD (Entity-Relationship Diagram)
A diagram that outlines the structure of the database, highlighting how entities like users and transactions connect and relate.
Use Case Diagram
Shows interactions between users and the system
4. Implementation
4.1 Modules
1. User Management: Registration, login, and profile management.
2. Transaction Processing: Fetching and storing digital payment transactions.
3. Expense Categorization: Assigning transaction types using predefined rules.
4. Budget Planning: Setting monthly budgets and monitoring spending.
5. Analytics & Reporting: Visualizing financial trends using graphs and tables.
4.2 Technology Stack
-Frontend: HTML, CSS, JavaScript
-Backend: PHP 5.6.2, MySQL
-Security Measures: Data encryption and user authentication
RESULTS AND DISCUSSION
5.1 System Performance
The system was tested using a dataset of 50+ digital transactions. It successfully categorized 90% of transactions accurately. The dashboard provided clear spending insights, improving financial awareness among users.
5.2 User Experience Feedback
Preliminary feedback from test users indicated:
- 85% found the automated transaction tracking useful.
- 70% preferred it over manual budgeting apps.
- 60% suggested adding AI-based spending predictions.
5.3 Comparison with Existing Systems
Table as given below:
CONCLUSION AND FUTURE SCOPE
6.1 Conclusion
The AI Powered Expense & Budget Tracker successfully automates digital payment expense tracking, reducing financial mismanagement. It eliminates the need for manual inputs and provides insightful analytics for better financial planning.
6.2 Future Scope
- AI-based expense predictions for smarter budgeting, as proposed by Davis and Gupta [7].
- Integration with more payment platforms (e.g., GooglePay,Paytm).
- Mobile app development for wider accessibility.
- Multi-user support for small business financial management
REFERENCE
Kunal Nale*, Shubham Pawar, Akash Kanthale, Yashraj Kenjale, Trupti Sonkusare, AI Powered Expense & Budget Tracker: A Web Based Financial Planning System, Int. J. Sci. R. Tech., 2025, 2 (4), 01-05. https://doi.org/10.5281/zenodo.15121884
10.5281/zenodo.15121884
