💰 BudgetAI — AI-Powered Personal Budget Monitor

Transform raw bank and UPI statements into actionable financial insights with AI-powered budgeting, analytics, and risk detection.

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📌 Overview

BudgetAI is a multi-page Streamlit application that helps users understand their financial habits by analyzing bank and UPI statements.

The application provides:

• 📊 Interactive dashboards
• 🧮 Expense analytics
• 🗓 Budget planning
• ⚠️ Risk detection
• 🤖 AI-powered financial advice

This project was developed as a rapid MVP within 24 hours and is designed to be expanded into a production-ready intelligent finance platform.

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✨ Features

• Secure local authentication
• CSV/XLSX transaction upload
• Automatic transaction categorization
• Interactive dashboard
• Monthly expense analytics
• Budget planner
• Suspicious transaction detection
• AI financial advisor
• Local audit logging

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🖼 Product Preview

Dashboard Overview

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Expense Analytics

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AI Recommendations

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Budget Planner

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Upload Transactions

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🏗 System Architecture

The application consists of a Streamlit frontend, modular business logic, data-processing utilities, analytics engine, AI recommendation module, and visualization layer.

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🔄 Data Pipeline

flowchart LR
A[CSV/XLSX Statement]
-->B[Parser]
-->C[Cleaning]
-->D[Categorization]

D-->E[Dashboard]
D-->F[Risk Detection]
D-->G[AI Advisor]

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🚀 Future Roadmap

• AI Chat Assistant
• OCR Receipt Scanning
• Bank API Integration
• Investment Tracking
• Financial Forecasting
• Cloud Deployment
• Multi-user Support

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🛠 Tech Stack

Layer	Technologies
Frontend	Streamlit
Language	Python
Data	Pandas, NumPy
Charts	Matplotlib
Excel	openpyxl
AI	OpenAI API
Notifications	Twilio

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📂 Repository Structure

ABM-AI-Powered-Budget-Monitor/
│
├── README.md
├── app.py
├── requirements.txt
├── assets/
│   ├── screenshots/
│   └── diagrams/
├── pages/
├── utils/
└── data/

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⚙ Installation

git clone https://github.com/Rakhal06/ABM-AI-Powered-Budget-Monitor.git

cd ABM-AI-Powered-Budget-Monitor

python -m venv venv

# Windows
venv\Scripts\activate

pip install -r requirements.txt

streamlit run app.py

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💡 Usage

1. Login or create an account.
2. Upload a CSV/XLSX statement.
3. Explore dashboards.
4. Review spending analytics.
5. Create budgets.
6. Run risk detection.
7. Ask the AI Financial Advisor for recommendations.

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🎯 Learning Outcomes

• Multi-page Streamlit development
• Financial data processing
• Rule-based analytics
• AI integration
• Data visualization
• Modular Python architecture

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⚠ Known Limitations

• Local JSON authentication
• Prototype architecture
• CSV/XLSX support only
• No persistent cloud database

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🌱 Future Scope

• Cloud deployment
• OCR support
• Real banking APIs
• Smarter AI insights
• Investment portfolio analytics

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📄 License

MIT License

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👨‍💻 Author

B. Rakhal Krishna

• GitHub: https://github.com/Rakhal06
• Email: b.rakhalkrishna06@gmail.com

If you found this project useful, consider giving it a ⭐ on GitHub.