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Insider Risk Whitepaper

We take a fundamentally different approach to detecting insider risks before they become security incidents. Legacy techniques are limited to reactively analyzing machine-generated data and user actions to identify breaches that have already occurred. In stark contrast, our algorithms model an insider’s intent by understanding the content of their communications so that malicious users can be stopped before they commit an offense.

Used by 15 out of the top 20 global banks, our patented approach to deriving insights from human communications will process 10 billion conversations in 2020. Our machine learning models have been proven in the most arduous of regulatory environments and are trusted to proactively locate risks from insider trading to conspiracy and harassment. By combining multiple weak signals into profiles of risky behavior, we inform organizations of human risks before they become international fiascos.