This project focuses on detecting fraudulent credit card transactions using SQL. The goal is to analyze transaction data, separate genuine vs. suspicious records, and uncover unusual patterns.
Data Cleaning & Preparation: Organized raw transaction datasets for analysis
SQL Queries for Fraud Detection: Used CASE, subqueries, joins, CTEs, window functions to identify patterns
Anomaly Detection: Flagged unusual behavior like high-value transactions or rapid multiple swipes
Step-by-Step Analysis: Structured queries to classify and filter transactions efficiently
SQL (PostgreSQL / MySQL)
CSV/Excel Dataset
(Optional) Visualization tools like Power BI
Strengthened SQL problem-solving skills
Gained hands-on experience in fraud detection and financial data analysis
Learned how data analysis can help reduce financial risks and protect customers
How to Use
Clone the repository
Load the dataset into your SQL environment
Run the provided SQL scripts to analyze and detect fraudulent transactions