Advanced Detection Models
Leverage rules engines, supervised/unsupervised ML models, anomaly detection, and network analysis to identify fraud patterns and high-risk cases.
Fraud Detection & SIU Platform
Fraud Detection & SIU
Detect and stop fraud across underwriting and claims: rules & ML models, link analysis & networks, image/video forensics, provider/partner scoring, alerts & queues, investigations & evidence, recoveries & reporting, integrated with PAS/Claims and provider networks.
Fraud Detection Impact
Fraud & SIU Suite
Detection and Investigation Unified
- Reduce fraud leakage with ML-powered detection
- Real-time alerts and prioritized work queues
- Complete SIU case management and evidence tracking
- Provider and partner risk scoring
- Comprehensive audit trail and compliance reporting
Optimized for Fraud Prevention
Comprehensive Fraud Detection and Investigation
Our Fraud Detection & SIU system combines advanced analytics, machine learning, and comprehensive case management to detect, investigate, and prevent insurance fraud across all touchpoints.
Complete SIU Workflow
Manage investigations from alert to resolution with case assignment, evidence management, interviews, site visits, and legal handover capabilities.
Core Modules
Key Features for Fraud Detection & SIU
Modular approach covering detection, investigation, and recovery. Enable modules progressively based on your organization's fraud prevention strategy.
Signals & Rules
Red flags for policy/claim, identity/device, provider behaviour, and document anomalies.
Machine Learning Models
Supervised/unsupervised models, anomaly detection, and outlier scoring.
Network & Link Analysis
Entities graph (customers, devices, addresses, providers) with risk propagation.
Image/Video Forensics
EXIF/tamper checks, similarity search, and staged-photo detection hooks.
Provider & Partner Scoring
Hospital/garage risk, over-billing, coding anomalies, and kickback red flags.
Alerting & Queues
Scored alerts with SLAs, prioritised work queues, and escalation paths.
Case Management (SIU)
Assignments, interviews, site visits, evidence vault, and legal handover.
Recoveries & Outcomes
Recovery tracking, write-back to claims, penalties, and learning loop.
Dashboards & KPIs
Hit-rate, precision/recall, TAT, savings, and provider heatmaps.
Governance & Privacy
Consent, access controls, and privacy-by-design for sensitive data.
Reporting & Regulator Packs
Case logs, outcomes, and periodic compliance packs.
Integrations
PAS/Claims, provider networks, payment gateway, OCR, and BI tools.
Integration and Deployment
Seamless Integration with Insurance Systems
The system integrates with PAS, Claims, provider networks, and forensics tools to provide comprehensive fraud detection and investigation capabilities.
Integration Options
- PAS/Claims integration for real-time fraud detection
- OCR & Forensics tools for document verification
- Graph/Link Analysis for network fraud patterns
- Provider Networks integration for scoring
- Data Warehouse/BI for analytics and reporting
- API-First & SSO for seamless access
Deployment and Security
- Cloud or on-premise deployment options
- Multi-layered encryption for sensitive fraud data
- Role-based access controls and audit trails
- Backup and disaster recovery features
Implementation Approach
Structured Rollout, Measurable Outcomes
A practical rollout approach to implement fraud detection and SIU capabilities with measurable results. Validate the system with realistic fraud scenarios before full-scale deployment.
Before Go Live
- Process mapping and gap analysis for fraud detection workflows.
- Configuration of rules, signals, and ML models.
- Data migration and integration planning with phased execution.
- System testing (SIT) and user acceptance testing (UAT).
- Training and readiness checklist across fraud and SIU teams.
After Go Live
- Active support and stabilization of fraud detection system.
- Continuous improvements and model tuning.
- Enhancements to detection rules and analytics capabilities.
- Ongoing security reviews and system performance tuning.
Rayterton can start without upfront payment. The focus is to validate fit through working workflows and real outputs before scaling rollout.