Fraud Detection in Financial Transactions

This project leverages machine learning algorithms to detect fraudulent transactions in financial data. It aims to identify anomalies in transaction patterns that may indicate fraudulent behavior, helping businesses mitigate financial risks.

Features

• Detects fraudulent transactions using advanced machine learning techniques.
• Analyzes transaction patterns to identify unusual activities.
• Provides real-time fraud alerts and risk scores for transactions.
• Supports integration with financial systems for seamless fraud detection.

Installation

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

1. Clone the Repository

   git clone https://github.com/username/fraud-detection.git
   cd 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 app.py

Upload your transaction dataset via the web interface to start analyzing for fraud.

Results

The system flags suspicious transactions and provides insights into potential fraud cases, helping to prevent financial losses.