PAYMENT FRAUD DETECTION ANALYSIS
Generated: 2025-11-15 04:01


SYSTEM PERFORMANCE OVERVIEW

Period Analyzed: 2024-01-01 to 2024-06-30
Total Transactions: 5,031,298
Total Volume: $521,499,607.13

ANOMALY DETECTION RESULTS:
✓ Anomalies Detected: 193 incidents
✓ Detection Rate: 69.4%
✓ False Positive Rate: 2.0%
✓ Financial Impact Prevented: $3,933,787.98

TOP THREATS IDENTIFIED:
1. DDoS Attacks: 12 incidents
2. Card Testing: 6 incidents  
3. Merchant Breaches: 48 incidents

RECOMMENDED ACTIONS:
1. IMMEDIATE:
   • Set automated blocks for transactions with risk score > 80
   • Implement rate limiting during 2-4 AM (peak fraud hours)
   • Add CAPTCHA for crypto transactions > 10% of volume

2. SHORT-TERM (30 days):
   • Deploy ML model to production with 61% precision
   • Establish 24/7 monitoring for response time > 1000ms
   • Create merchant risk scoring system

3. LONG-TERM (90 days):
   • Implement real-time streaming analytics
   • Build customer behavior profiles
   • Develop predictive fraud models

EXPECTED OUTCOMES:
• Reduce fraud losses by 70% ($3,933,788 annually)
• Improve customer experience (reduce false positives by 50%)
• Meet regulatory compliance for real-time monitoring

Next Review: Weekly fraud metrics starting 2025-11-22


Detection Methods Comparison:
Statistical: Precision=83.72%, Recall=18.65%
Machine Learning: Precision=61.47%, Recall=69.43%
