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Autonomous investigation from detection to closure. 50-70% cost savings. 90%+ case accuracy. Regulatory-ready documentation.
Fraud alerts auto-create cases with context from detection system
Autonomous collection of player data, transactions, behavioral patterns
Automated fraud indicator identification & comparison to typologies
Graph analysis discovering fraud rings and coordinated account networks
Severity scoring and categorization (low/medium/high-value fraud)
Case resolution suggestions: dismiss, warn, restrict, close account
Fraud alert triggers auto-case creation with context
Autonomous collection of account, transaction, behavioral data
Compare against known fraud signatures and typologies
Graph analysis identifies related accounts and fraud rings
Severity assessment and fraud category classification
Automated event sequencing and visualization
Decision support: dismiss, warn, restrict, or escalate
Evidence compilation and regulatory report generation
Complex cases routed to analysts; auto-cases actioned
Discover networks of accounts with shared attributes (IP, payment method, device)
Identify coordinated betting patterns suggesting organized fraud
Track fund movement across accounts detecting mule networks
Detect synchronized activity across accounts suggesting automation
Identify coordinated trading/betting exploiting odds inefficiencies
Detect affiliate partners running bonus abuse or account testing schemes
Audit investigation workflows, backlogs, fraud typologies; map decision criteria
Encode investigation processes into decision logic and automation workflows
Deploy autonomous investigation on high-volume fraud type (bonus abuse, ATO)
Full deployment; escalation routing; automated documentation generation
Monitor accuracy; retrain quarterly; expand to new fraud types; improve recommendations
50-70% cost savings. 90%+ accuracy. 5-10x faster closure. Regulatory-ready documentation.
Schedule a Demo →Typically 40-60% of cases are straightforward enough for autonomous closure (low-risk, clear-cut fraud). Medium-complexity cases (20-30%) are recommended for analyst review with AI assistance. Complex, high-value fraud (10-20%) require full analyst investigation.
Our models achieve 90%+ accuracy matching analyst conclusions on test cases. Accuracy varies by fraud type: bonus abuse/ATO achieve 95%+, while complex collusion requires more analyst input.
Yes. Graph analysis works on real-time behavioral patterns (shared IP, device, payment method, betting patterns). GNNs identify suspicious networks even with limited historical training data.
Investigations generate audit trails and evidence documentation for all major jurisdictions. Investigation logic is fully traceable and explainable for gaming commission audits.
Yes. We integrate via APIs with most case management and fraud detection platforms. Data flows from your system to our investigation engine, results flow back for analyst review and action.