BFSI_OCR

ApnaBank - AI-Powered Banking Web App with OCR

Overview

ApnaBank is a full-stack web application designed as a modern banking platform with AI-driven features for loan eligibility prediction, CIBIL score analysis, and financial data visualization.

Features

• Homepage: Interactive landing page with smooth scrolling animations and banking service details.
• User Authentication: Secure login and registration system.
• Dashboard: Displays monthly transactions and financial data visualizations (pie charts, bar graphs, etc.).
• Loan Checker: Users can upload recent payslips, and the system extracts data using OCR and a trained model to determine loan eligibility and CIBIL score.
• CIBIL Score Predictor: Predicts the CIBIL score using a pre-trained ML model.
• Expense Tracker: Tracks personal expenses based on categories and transactions.
• AI Integration: Machine learning models to process financial data and determine loan eligibility.

Tech Stack

• Frontend: Streamlit
• Backend: Python
• Database: SQLAlchemy
• Machine Learning: scikit-learn, pandas, numpy
• OCR Processing: OpenCV, Tesseract

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/ApnaBank.git
   cd ApnaBank
   

2. Create a virtual environment and activate it:

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

3. Install dependencies:

   pip install -r requirements.txt
   

4. Run the application:

   streamlit run apnabank_app.py
   

Dataset Information

ApnaBank uses two datasets:

1. user_data.csv - Contains user details like expense category, income, etc.
2. transaction_data.csv - Includes transaction history with transaction amount, date, and category.

AI Model for CIBIL Score Prediction

• A machine learning model (cibil_model.pkl) is trained using the transaction dataset.
• If a user is from a Tier-1 college (IIT, NIT) or a top ranker, they can still qualify for loans even with a low CIBIL score.

Project Structure

ApnaBank/
├── 
│     ├── apnabank_app.py
│     ├── apnabank.db
│     ├── cibil_model.py
│     ├── user_data.csv
│     ├── transaction_data.csv
│     └── venv/
│   
└── README.md

Flowchart - Loan Eligibility Process

Contributing

Feel free to contribute by submitting pull requests or reporting issues.

License

MIT License

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