Go beyond traditional surveillance

Our solution brings a holistic and cognitive approach to monitoring all employee-related activities, helping you improve the efficiency and accuracy of surveillance programs, and effectively comply with regulations. It goes beyond traditional rules-based alert systems to proactively monitor employees in real-time, leveraging both unstructured and structured data - emails, chat transcripts, voice recordings, customer complaints, and trade data. You can leverage prebuilt models and also identity new predictive patterns for applications across conduct risk, market abuse, client suitability, and complaints. Contact our sales rep to get started.

Holistic view of risks

Deliver a complete view of risks across the organization by detecting sophisticated misconduct, often missed by traditional surveillance solutions.

Fast and effective threat detection

Instantly drill-down into the evidence and reasoning behind an alert to make a quick and accurate decision.

Reduced cost of employee non-compliance

“Know your employee” by proactively monitoring employees and linking various information with their profiles for a more complete view of who they are.

Decreased false positives and negatives

Prioritize alerts based on risk and tackle the most concerning first by capitalizing on sophisticated, prebuilt models for more efficient and effective surveillance.

Security and privacy in the cloud

  • IBM enables companies to scale and adapt quickly to changing business needs without compromising security, privacy or risk levels when using IBM cloud offerings.

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Which option is right for you?

  • Holistic Surveillance


    Minimize the impact of unseen risks by detecting, profiling and prioritizing non-compliant behavior across trade, voice and electronic communication data.

  • Voice Surveillance


    Unlock voice data to accelerate identification of suspicious intent and ensure regulatory compliance.

  • Complaints Analytics


    Uncover systemic risks in your sales practices by collecting and analyzing complaints data.