Four-Modality AI Detection.
95% Accuracy. Real-Time Protection.
Fraud, leakage, and inefficiency divert funds intended for citizen services — funds that disappear before reaching their intended purpose. GOVERN G5's Fraud Detection Engine addresses this with four distinct detection modalities working in concert, achieving a 95% true positive rate and identifying $47M in anomalous transactions in a single 6-month deployment period.
Four distinct detection vectors, working in concert
Fraudsters create multiple identities to claim benefits across multiple schemes — sybil attacks, benefit farming, and identity fusion attempts that drain public funds.
Graph database with ML models identifying:
- Sybil attacks and benefit farming across multiple schemes
- Identity fusion attempts combining partial records
- Fuzzy matching for name, address, and biometric variations
- Cross-scheme duplicate enrollment detection
- Graph database for relationship mapping
- ML-based duplicate detection
- Real-time identity verification against multiple data sources
- Continuous de-duplication as new beneficiaries enroll
Fraudulent claims at GPS coordinates inconsistent with registered addresses — beneficiaries claiming services in locations they couldn't possibly be.
Flags claims at GPS coordinates inconsistent with registered addresses:
- Beneficiary location verification against registered address
- Fraud hotspot identification through clustering analysis
- Geographic impossibility detection (impossible travel times)
- Regional fraud pattern recognition
- GPS coordinate cross-referencing with geofencing
- Spatial clustering algorithms for hotspot detection
- Historical pattern analysis for anomaly identification
- Map-based visualization for investigation
Anomalous patterns in claim and usage behavior that indicate fraud — perfect attendance records, immediate full-amount withdrawals, unusual claim frequencies.
Sequence analysis identifying anomalies:
- Perfect attendance records inconsistent with human behavior
- Immediate full-amount withdrawal patterns suggesting non-genuine enrollment
- Unusual claim frequency or amount patterns
- Seasonal and temporal anomaly detection
- Machine learning sequence analysis
- Behavioral baseline establishment per beneficiary
- Statistical outlier detection
- Pattern recognition across claim histories
Organized fraud rings exploiting multiple schemes through shared resources — shared bank accounts, common disbursement accounts, family-network fraud.
Identifies organized fraud rings and shared resources:
- Shared bank account withdrawal patterns across beneficiaries
- Common payment disbursement accounts
- Family-network fraud rings exploiting multiple schemes
- Provider-facilitated fraud networks
- Network graph analysis for relationship mapping
- Community detection algorithms
- Shared resource identification
- Organized crime pattern recognition
Validated by deployment data
Public Financial Management Reform across national and 47 county governments
Public Financial Management Reform across national and 47 county governments.
$47M in anomalous transactions identified in first six months through four-modality fraud detection.
The Fraud Detection Engine integrates with
Connected across the GOVERN G5 platform to share detection signals and verification across the full beneficiary lifecycle.
Protect your public funds
Request a detailed briefing on how the Fraud Detection Engine can protect your government programs from fraud and leakage.
Engagement begins with a verified, secure channel. Responses are handled only by cleared personnel.
All engagements require security clearance and authorization verification.
- Live demonstration of four-modality detection
- Deployment options for your data sensitivity
- Integration with existing scheme and finance systems
- Operational rollout and analyst training