Online Transaction Fraud Detection

Overview

The Online Transaction Fraud Detection system is a machine learning project designed to identify fraudulent activities in online transactions. It uses a combination of rule-based systems and anomaly detection algorithms in Artificial Intelligence to flag suspicious transactions for further review.

Key Features

• Real-time monitoring: The system can monitor transactions in real-time to identify potential fraud.
• Anomaly detection: It uses advanced algorithms to detect anomalies that may indicate fraudulent behavior.
• User-friendly interface: A simple and intuitive user interface for non-technical users.

Getting Started

To get started with the project, follow these steps:

Prerequisites

• Python 3.8 or higher
• Libraries: numpy, pandas, scikit-learn, Pytorch, PyQt5, torchvision, etc.
• Or install from requirement:

  pip install -r requirement.txt
  

Installation

1. Clone the repository:

   git clone https://github.com/YapWH/Fraud-Detection.git
   

2. Open the folder and run the MCYIC.py file.

   python MCYIC.py
   

Contribution