Credit Card Fraud Detection

This project aims to detect fraudulent credit card transactions using machine learning algorithms. It helps financial institutions identify suspicious activities and prevent fraud before it impacts customers.

Features

• Real-time detection of fraudulent transactions.
• High accuracy models using techniques such as Logistic Regression, Random Forest, and Neural Networks.
• Handles large-scale data with imbalanced classes.
• Deployable as a real-time API for integration with payment processing systems.

Installation

To set up the Credit Card Fraud Detection system on your local machine, follow these steps:

1. Clone the Repository

   git clone https://github.com/username/credit-card-fraud-detection.git
   cd credit-card-fraud-detection

2. Set Up Virtual Environment (Optional but Recommended)

   python3 -m venv venv
   source venv/bin/activate   # On Windows: venv\Scripts\activate

3. Install Required Packages

   pip install -r requirements.txt

Usage

To start detecting fraudulent transactions, run the main script:

python fraud_detection.py

Analyze transaction data in real-time and flag suspicious activities.

Results

The fraud detection system successfully identifies fraudulent transactions with high accuracy, providing insights into suspicious patterns and helping reduce financial losses.