False Positives occur when fraud detection systems incorrectly flag legitimate transactions or activities as fraudulent, leading to unnecessary reviews and potential customer friction.
Impact Areas
- Customer experience
- Operational costs
- Processing time
- Resource allocation
- Business reputation
Common Causes
- Strict rules
- Outdated models
- Data quality issues
- System errors
- Risk thresholds
Detection Methods
- Rate monitoring
- Pattern analysis
- Rule review
- Performance metrics
- Customer feedback
Reduction Strategies
- Model tuning
- Rule optimization
- Data enhancement
- System updates
- Regular review
Best Practices
- Regular monitoring
- Model updates
- Rule refinement
- Performance tracking
- Customer communication
Minimizing false positives while maintaining effective fraud detection requires careful balance.