False Negatives occur when fraud detection systems fail to identify actually fraudulent transactions or activities as suspicious, allowing fraudulent activities to proceed undetected.
Impact Areas
- Financial losses
- Security breaches
- Risk exposure
- System reliability
- Business reputation
Common Causes
- Weak rules
- Model limitations
- Data gaps
- System blindspots
- Outdated patterns
Detection Methods
- Post-analysis
- Pattern review
- Loss monitoring
- System audits
- Performance metrics
Prevention Strategies
- Model enhancement
- Rule strengthening
- Data improvement
- System updates
- Regular testing
Best Practices
- Continuous monitoring
- Pattern updates
- System optimization
- Risk assessment
- Regular audits
Reducing false negatives is crucial for maintaining effective fraud prevention systems.