From Detection to Prevention:
Analytics Advances Fraud Management
Challenge & Opportunity
A government agency providing business support needed to enhance its anti-fraud capabilities. The organisation faced three key challenges
- Rising sophistication in fraudulent activities
- Resource constraints for case investigation
- Need for proactive fraud prevention
Our Approach
Discover & Diagnose
- Risk pattern analysis
- Data quality assessment
- Process flow mapping
- External data integration
Design & Model
- Predictive risk scoring development
- Interactive binning implementation
- Feature engineering framework
- Natural language processing integration
Deploy & Execute
- Risk detection engine deployment
- Alert prioritisation system
- Investigation workflow integration
- Performance monitoring framework
Optimise & Scale
- Continuous model refinement
- Pattern detection enhancement
- Threshold adjustment system
Results & Impact
Key Results
- £15M in prevented fraudulent claims
- 60% reduction in false positives
- 30% improvement in early detection
- Enhanced investigation efficiency
Business Outcomes
- Streamlined case prioritisation
- Improved resource allocation
- Enhanced risk intelligence
- Proactive prevention framework
Solution Toolkit
- SAS Enterprise Miner
- Oracle
- Python
- NLP
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