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March 23, 2018

NICE Actimize introduces AI-enabled financial crime investigation platform

Financial crime management solutions provider NICE Actimize is set to release an AI-enabled investigation management system ‘Actimize ACTone’ to serve as an alert and case management platform for financial services organisations (FSOs).

Using Autonomous Financial Crime Management (AFCM) approach and AI-driven automation, the new solution is expected to reduce investigation time for a single alert by nearly 70% and enhance analyst’s decision making.

Actimize ACTone uses analytics and automation at every step to transform detection and investigation of financial crimes. It also enables the FSOs to employ an intelligent virtual workforce along with human investigators to investigate financial crimes.

NICE Actimize’s ACTone offers a single platform to resolve all alerts and cases from a diverse system of financial crime solutions.

The approach allows transformation of any financial crime system by using AI-enabled robotics and automation.

In combination with NICE Actimize’s Autonomous Financial Crime Management approach, the solution is expected to enable better resource utilisation, increase accuracy and productivity.

NICE Actimize president Joe Friscia said: “This paradigm shift, as reflected in our release of the new ACTone investigation management system is another proof-point in our march towards bringing the vision of Autonomous Financial Crime Management to reality.

“ACTone seamlessly merges technology and data to both improve productivity and to turn raw data into actionable intelligence.

“In an autonomous world, instead of machines assisting humans to complete work, humans will assist the machines. With financial criminals getting smarter every day, it’s time for us to do the same.”

Actimize ACTone Investigation Manager is capable of identifying visual relationships across entities to detect risks and provides a dynamic risk score to every entity to help the analysts in making faster decisions.

It also eliminates manual data gathering thereby reducing operational costs and errors.

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