Comparison
MaiGuard vs Rules-Only Fraud Systems
Static rules catch known patterns but miss evolving fraud. MaiGuard combines configurable rules with ML models, behavioral biometrics, and entity graph analysis for adaptive protection.
Capabilities vary by plan and configuration. See the scoring guide and architecture overview for details.
Rules + ML hybrid
Configurable velocity and threshold rules run alongside ML models that adapt to your transaction data — catching novel patterns rules miss.
Behavioral biometrics
Browser SDK collects keystroke, mouse, and scroll signals to distinguish bots from humans — unavailable in rules-only systems.
Shadow mode testing
Validate new rules in production without affecting live decisions. Rules-only systems require staging environments or risky direct deploys.
Entity graph analysis
Multi-hop graph traversal detects mule networks and synthetic identity rings — beyond what flat rule conditions can express.
Feedback intelligence loop
Submit outcome feedback to improve rule precision and monitor model drift over time.