Lupus AI is a state-of-the-art financial protection system that combines the power of machine learning with a seamless app and website integration. Our mission is to revolutionize fraud detection and prevention, ensuring the safety and security of your hard-earned wealth.
Fraudulent transactions pose a significant threat to the financial sector, causing substantial financial losses. Current fraud detection methods often fall short in effectively identifying and preventing such activities. To tackle this pressing issue, we present Lupus, an ML-powered solution. Leveraging advanced algorithms and real-time analysis of extensive transactional data, Lupus swiftly detects and flags potential fraud transactions. By providing timely alerts, it helps safeguard banks from financial losses and combat fraudulent activities.
- Automatic flagging of potential fraudulent transactions
- User-friendly web and mobile app interface for easy access and management of flagged transactions
- Customizable alert settings for tailored notifications to relevant personnel
- Secure and encrypted data storage to protect sensitive information
- Regular updates and improvements based on ongoing analysis and feedback from users
- Lupus is a machine learning-based fraud detection system for banks
- The system will analyze large volumes of transactional data in real-time
- Lupus will utilize advanced algorithms and techniques to flag any potential fraud transactions
- The system will have a user-friendly web interface for easy access and monitoring of fraudulent activities
- The Lupus mobile app will provide real-time notifications of suspicious transactions to bank customers
- The system will have the capability to learn and adapt to new fraud patterns for improved accuracy and efficiencyy text
Lupus can be of use to the financial sector by detecting fraudulent activities in real-time and preventing potential losses. The machine learning-based system utilizes advanced algorithms and techniques to analyze large volumes of transactional data, providing a reliable and efficient means of fraud detection. Its user-friendly web application and mobile app make it accessible to banks and their customers, enhancing the customer experience and improving overall security. The project's scope includes implementing the system in real-world scenarios and expanding its capabilities to include additional features such as fraud prediction.
- Integration with additional data sources and APIs for better analysis and accuracy.
- Implementation of more advanced machine learning algorithms and models for improved fraud detection and prevention.
- Real-time alerts and notifications for suspicious activities, allowing for immediate action to be taken.
- Incorporation of natural language processing (NLP) techniques to analyze textual data, such as email and chat conversations, for fraud detection.
- Integration with blockchain technology to ensure the security and immutability of transactional data.
- Development of a user-friendly dashboard for banks and financial institutions to visualize and monitor their transactional data.
- Integration with mobile devices and biometric authentication for added security and convenience.
User Dashboard with details of transactions and graphical data rendered from the ML model in the backend for the transaction
The ML model in Lupus.ai employs KNN, Random Forest, and RGB Boost algorithms to detect and prevent financial fraud. Compressed using joblib, the model is seamlessly integrated into the Django server, enabling real-time predictions and efficient communication. It classifies transactions as fraudulent or legitimate, providing prompt actions for fraud prevention. The model's scalability and performance handle large volumes of transactional data, while continuous improvement ensures adaptation to evolving fraud patterns. Lupus.ai's ML model offers accurate and efficient fraud detection, safeguarding financial institutions and providing a secure banking experience.
Follow these steps to get started with the project:
- Clone the repository:
git clone https://github.com/your-username/your-repository.git - Install the required dependencies:
npm install - Configure the necessary settings and credentials.
- Run the application:
npm start
Shinjan Patra
Role: App Developer
Mathangy Krishna
Role: ML Developer
Tanmay Agarwal
Role: FrontEnd Developer
Jatin Kumar
Role: Backend Developer
This project is licensed under the MIT License.