Credit Card Fraud Detection System

An end-to-end system for detecting fraudulent credit card transactions using Python, SQL, Excel, and Power BI.

Project Overview

This project implements a comprehensive credit card fraud detection system that:

• Analyzes transaction patterns to identify potentially fraudulent activities
• Stores and queries data using SQL
• Provides financial analysis through Excel
• Visualizes insights with interactive Power BI dashboards

Repository Structure

credit-card-fraud-detection/
│
├── data/                      # Data directory
│   ├── raw/                   # Raw data files
│   └── processed/             # Processed data files
│
├── scripts/                   # Python scripts
│
├── notebooks/                 # Jupyter notebooks
│
├── sql/                       # SQL scripts
│
├── excel/                     # Excel templates and files
│
├── powerbi/                   # Power BI report templates
│
└── docs/                      # Documentation files

Development Phases

1. Data Acquisition & Setup: Initialize GitHub repository, download dataset, and set up project structure
2. Data Preparation & Analysis: Clean and analyze transaction data with Python
3. SQL Database Implementation: Set up database, create tables, and implement queries
4. Excel Analysis & Reporting: Build Excel templates for financial analysis
5. Power BI Dashboard Development: Create interactive dashboards for fraud monitoring

Dataset

This project uses the Credit Card Fraud Detection dataset from Kaggle, which contains transactions made by credit cards in September 2013 by European cardholders.

Requirements

• Python 3.8+
• Git and GitHub account
• SQL Server or MySQL
• Microsoft Excel
• Power BI Desktop

Setup Instructions

Detailed setup instructions can be found in the documentation:

• Python Environment Setup
• Database Setup
• Excel Configuration
• Power BI Configuration

License

This project is licensed under the MIT License - see the LICENSE file for details.