A Smart, AI-driven platform for modern personal finance management — combining voice input, receipt scanning, machine learning, and predictive analytics to help users take control of their financial future.
In today's fast-paced digital world, many individuals struggle with managing their finances due to the limitations of traditional budgeting tools and manual tracking. Our project — AI-Powered Personal Finance Tracker — presents an intelligent, accessible, and bank-independent solution for effortless financial management.
This platform uses cutting-edge technologies like Tesseract OCR for extracting transaction data from receipts, FinBERT NLP for intelligent expense categorization, and supports voice-based transaction logging via the Web Speech API and Stanza. For smarter budgeting and forecasting, it integrates Gradient Boosted Decision Trees, Prophet, and LSTM models.
Key modules include Group Expense Management for shared finances, and Celery-based Reminders to notify users about bills. The system is built with a Django backend and a responsive HTML + Tailwind CSS frontend.
- 🧾 Receipt Scanning: Extract transaction data using Tesseract OCR.
- 🗣️ Voice Logging: Add expenses using voice input with Web Speech API and Stanza.
- 📊 Smart Categorization: FinBERT classifies expenses into intelligent categories.
- 📈 Forecasting Engine: Uses Prophet + LSTM for financial trend prediction.
- 💰 AI Budgeting: Gradient Boosted Decision Trees generate budget suggestions.
- 👥 Group Expenses: Track and manage shared spending with others.
- ⏰ Bill Reminders: Scheduled reminders using Celery and Redis.
- 🖥️ Dashboard: Visualizes spending, forecasts, and trends for informed decisions.
- 🔐 Authentication: Session-based login system ensures secure access.
| Layer | Technologies Used |
|---|---|
| Frontend | HTML5, Tailwind CSS, JavaScript, Web Speech API |
| Backend | Python, Django, Celery, Redis, SQLite |
| AI & ML | Tesseract OCR, FinBERT (NLP), Stanza (NLP), Gradient Boosted Trees, Prophet, LSTM |
| Auth | Django Sessions |
Final-Year-Project/ ├── finance_tracker/ # Django project folder ├── templates/ # HTML templates ├── static/ # Tailwind CSS, JS, images ├── receipts/ # Uploaded receipt images ├── models/ # Trained ML models (Pickle format) ├── celery.py # Task scheduling setup ├── requirements.txt # Dependencies └── README.md # Project documentation
- Clone the Repository
git clone https://github.com/sugapriya-k/Final-Year-Project.git cd Final-Year-Project - Create Virtual Environment
python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate
- Install Requirements
pip install -r requirements.txt
- Run Redis Server
redis-server
- Start Celery Worker
celery -A finance_tracker worker --loglevel=info
- Run Django Server
python manage.py migrate python manage.py runserver