Credit Card Fraud Detection

Credit Card Fraud Detection

Abstract:

Today’s digital age sees credit card fraud. Credit card fraud detection systems must be developed to address this issue. This system detects suspicious user behavior and location patterns. The system verifies cardholder identity by analyzing spending patterns and geographic locations. The system requests additional verification when an unusual pattern is detected to ensure transaction security.

Introduction:

Credit card fraud has increased due to widespread credit card use online and offline. Fraudsters exploit system vulnerabilities to steal from individuals and financial institutions. Thus, real-time fraud detection and prevention mechanisms are essential.

Objectives:

This project aims to create an effective credit card fraud detection system. The system looks for unusual spending and location patterns by analyzing user behavior and location data. Credit card transactions will be safer and more reliable thanks to this project.

Project Details:

Advanced algorithms and machine learning techniques analyze user credit card data to detect fraud. The system considers user country and spending habits. The system detects suspicious behavior by comparing the current transaction to the user’s historical data.

If the system detects an unusual pattern, it verifies the transaction further. Logging in again, providing additional authentication credentials, or undergoing additional security checks may be required. To prevent unauthorized access and fraud, the system may temporarily block the user’s account after three invalid attempts.

To improve credit card fraud detection, the project uses cutting-edge data analysis and technologies. It uses machine learning models trained on large datasets of legitimate and fraudulent transactions to improve detection over time.

Conclusion:

Today’s digital world requires a strong credit card fraud detection system. This project uses user behavior and location scanning to find suspicious patterns. The system improves payment security by analyzing user data and characteristics. The system’s algorithms are updated and refined to detect and prevent credit card fraud, protecting individuals and organizations’ finances.

Note: Please discuss with our team before submitting this abstract to the college. This Abstract or Synopsis varies based on student project requirements.