Go beyond threshold-based monitoring
iManage Threat Manager utilizes machine learning to analyze millions of transactions in iManage Work audit tables to detect patterns of normal and abnormal user behavior over time. Detected threats are based on statistically generated thresholds, not an arbitrary number- significantly reducing false positives.
iManage Threat Manager monitors advance activities that exposes user intent such as unique clients and matters accessed. A proprietary algorithm scores alerts based on deviations from individual user and peer group behavioral patterns.
iManage Threat Manager provides recommendations for at risk threat patterns and organizations can test these recommendations against their own data to verify the quality and quantity of alerts generated.