FinTech Global
FinTech Global was experiencing significant fraud losses with legacy rule-based systems that blocked legitimate transactions. Their static rules generated a high false-positive rate, driving away good customers and costing millions in lost revenue.
The Challenge
FinTech Global was experiencing significant fraud losses with legacy rule-based systems that blocked legitimate transactions. Their static rules generated a high false-positive rate, driving away good customers and costing millions in lost revenue.
- Legacy rule-based system had not been updated in over two years
- False positives were blocking legitimate high-value wire transfers
- Manual review queues had grown beyond team capacity
- Regulatory pressure to improve AML detection without adding friction
- Mobile banking channel had limited fraud visibility compared to web
- No real-time device intelligence across platforms
The Solution
FinTech Global deployed VerifyStack with behavioral biometrics and device fingerprinting across web and mobile platforms, integrating the Mirage Protocol for advanced bot detection on all login and transaction endpoints.
- Phased rollout starting with login protection, then expanding to payment flows
- Behavioral biometrics (keystroke dynamics, mouse movement) layered on top of device fingerprinting
- Mirage Protocol deployed for real-time bot detection on API endpoints
- Custom risk policies built with VerifyStack policy engine for PCI-DSS compliance
- Real-time webhook integration with existing SIEM for unified threat visibility
- Consortium intelligence enabled for cross-customer threat sharing
Implementation Timeline
Discovery & Integration
SDK integration, baseline telemetry collection, and historical data ingestion.
Shadow Mode
VerifyStack ran in shadow mode alongside existing system, comparing decisions in real time.
Gradual Cutover
Progressive traffic shift from legacy rules to VerifyStack decisions, starting with low-risk segments.
Full Production
Complete migration with real-time dashboards, alerting, and automated policy management.
Results
- Eliminated manual review for 87% of previously flagged transactions
- Reduced customer friction complaints by 62% within first quarter
- Achieved regulatory compliance targets ahead of schedule
- Expanded to mobile banking channel with zero additional integration effort
- Saved an estimated $3.2M annually in fraud losses and operational costs
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