VeriKYC is a web application designed to streamline the Know Your Customer (KYC) verification process for banking and financial institutions. It utilizes machine learning techniques to authenticate customers using their valid government-issued ID and real-time face recognition.
Working.Demo.mp4
- User Authentication: Register and log in securely to perform tasks within the system.
- Server-side Sessions: Maintain secure user sessions on the server for data privacy.
- Machine Learning-Based Verification: Utilize ML models for ID information extraction and face matching.
- Privac 795B y Protection: No storage of ID information on the server.
- Node.js: JavaScript runtime environment.
- Express.js: Web application framework for Node.js.
- MongoDB Atlas: Cloud-based database manager.
- Bootstrap: Front-end framework for styling and responsiveness.
- EJS: Embedded JavaScript for dynamic HTML views.
- Joi: Library for form validation.
- Sanitize-html: Tool for HTML input sanitization.
- Passport.js: Authentication middleware.
- Oracle E2 Instance: Hosting platform for the ML API server.
- OCR: Extract details from ID cards using easy-ocr library.
- Face-Recognition: Perform face recognition using Python library.
- FastAPI: Framework for handling requests to and from the ML API server.
- Clone this repository.
- Install Node.js and MongoDB.
- Install dependencies:
npm install. - Run the application:
node app.js.
Contributions are welcome! Feel free to fork the repository and submit pull requests.
This project is licensed under the MIT License - see the LICENSE file for details.