NICE Actimize enhances e-communications offering with machine learning tools
Autonomous financial crime detection company NICE Actimize has enhanced its e-communication surveillance solution with improved machine learning, analytics and investigative tools.
The additions have been released to bolster the surveillance detection and case management capabilities for clients, lower false alerts and reduce compliance costs. The machine learning and natural language processing-powered analytics can automatically review the entity of employee communications.
Other benefits of the newly updated system include the ability to reconstruct trades up to 50-times faster so analysts can improve risk management. The system supports full compliance with global communication monitoring regulations such as MiFID II, Dodd-Frank, and FX Global Code.
Clients can leverage the solution to automate the majority of their compliance workflows and reduce the total cost of ownership via analytics and cloud deployment.
The NICE Actimize solution already utilises natural language processing-based speech and text analytics which can detect risky communications or extract quotes or trade details. With the new capabilities, flagged communications can now be classified based on relevancy, business topic and asset class.
NICE executive vice president Chris Wooten said, “Many leading financial institutions, both on the buy-side and sell-side, currently leverage our solutions to improve their compliance programs’ detection accuracy, total cost of ownership and efficiency.
“This newest release of our eCommunications surveillance solution, with its next generation machine learning and our award-winning ActOne investigation and case management solution, brings communications surveillance detection and investigative efficiency to a whole new level.”
Earlier in the year, IDB Bank deployed the NICE Actimize solution to support its AML processes. In working together, the bank uses the AML compliance tools to identify suspicious activity and improve its customer due diligence processes.
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