💸 Budget Tracking System

AI-Powered Expense Tracking & Budget Forecasting Platform

📌 Overview

Budget Tracking System is a web-based application designed to help users track their income and expenses while providing AI-driven budget forecasts based on historical spending behavior.

Unlike traditional expense trackers, this system integrates time-series forecasting models to predict future budget needs, enabling users to make more informed financial decisions.

🎯 Project Goals

Record and manage user income and expenses

Categorize financial transactions

Analyze historical spending data

Generate monthly budget forecasts using machine learning

Improve users’ financial awareness through data visualization

🧠 System Architecture

Backend

Python (Flask)

Flask-SQLAlchemy

Flask-Login (Authentication)

MSSQL

Frontend

HTML5

CSS3 (Custom Styling)

Jinja2 Templates

AI & Forecasting

Time Series Analysis

Facebook Prophet for monthly budget prediction

🖼️ Application Screenshots

Below are real screenshots from the Budget Tracking System application, showcasing key features and user interfaces.

🔐 Authentication

Login Page

Register Page

📊 Dashboard

The dashboard provides an overview of the user’s financial status with visual summaries.

Dashboard – Overview

Dashboard – Detailed View

💾 Expense Management

Users can add and manage their expenses and view historical records.

Add Expense Page

Expense History

🤖 Budget Forecasting

The forecasting module predicts future expenses based on historical data using a time-series model.

Forecast – Result 1

Forecast – Result 2

Forecast – Result 3

📈 Analysis Module

The analysis section helps users understand their spending patterns through multiple visual insights.

Analysis – View 1

Analysis – View 2

Analysis – View 3

⚙️ Key Features

🔐 User Authentication

Secure login and registration

Password hashing

Session management with Flask-Login

💾 Expense Management

Add income and expenses

Category-based tracking

Date-based historical records

🤖 AI-Based Budget Forecasting

Monthly time-series modeling

Historical data aggregation

Future budget predictions using Prophet

🧪 Forecasting Model

The forecasting process includes:

Aggregating expenses on a monthly basis

Cleaning and filling missing time periods

Training a Prophet time-series model

Predicting future monthly budget requirements

Why Prophet?

Performs well on small datasets

Handles seasonality and trends effectively

Suitable for financial time-series data

📊 Data Visualization

Monthly expense summaries

Category distribution analysis

Personalized financial dashboard

🗄️ Database Design

Main database tables:

Users

Expenses

Categories

ForecastResults

Sample Fields:

user_id

amount

category

transaction_date

created_at

🚀 Installation & Setup

Clone the repository

git clone https://github.com/sinemadalan/budget_tracking.git

Create virtual environment

python -m venv venv source venv/bin/activate # Windows: venv\Scripts\activate

Install dependencies

pip install -r requirements.txt

Run the application

flask run

📁 Project Structure

budget_tracking/

├── app.py

├── data_values.sql

├── requirements.txt

├── static/

│ └── images/

│ ├── budget.png

│ └── budget_sidebar.png

├── templates/

│ ├── index.html

│ ├── login.html

│ ├── register.html

│ ├── expenses.html

│ ├── analysis.html

│ └── forecast.html

└── README.md

👩‍💻 Author

Sinem Adalan

Software Engineering Student

Interests: AI, Data Science, Web Development

⭐ Conclusion

The Budget Tracking System demonstrates the integration of software engineering principles, database management, and machine learning in a real-world financial application.

It serves as a scalable foundation for intelligent personal finance systems and showcases practical AI usage in budget forecasting.