Fraud Detection System for Online Payment Transactions Using Rule-Based Analysis

The objective of this project is to develop a fraud detection system that analyzes online payment transactions using predefined rules. The system identifies suspicious transactions based on abnormal patterns, helping prevent financial fraud and unauthorized payments.

Study common online payment fraud techniques and case studies.

Analyze transaction attributes such as amount, frequency, location, and device type.

Design a rule-based engine to detect suspicious transaction patterns.

Implement thresholds for transaction amount and frequency anomalies.

Generate alerts for potentially fraudulent transactions.

Maintain logs for flagged and approved transactions.

Provide administrative interfaces to update fraud detection rules.

Test system accuracy using simulated fraudulent and normal transactions.

Evaluate false positives and false negatives.

Improve rules based on observed results.

Document system effectiveness and real-world applicability.