Hoboken, New Jersey-based financial services-focused technology company NICE Actimize has launched a new automation-based solution intended to help companies detect white collar crime.
Branded as Suspicious Activity Monitoring solution, the tech incorporates robotic process automation (RPA), machine learning, and analytics principles to help users better detect when a potential threat emerges and gauge whether human intervention is necessary.
NICE Actimize, a subsidiary of NICE (Nasdaq:NICE), says the biggest benefit of the offering is “virtually eliminating the manual search for third-party data,” something that can reduce “investigation time for a single alert by up to 70%” and improve overall productivity for those tasked with monitoring potential financial crime incidents.
Anti-money laundering is one key feature, with the autonomous aspects of the technology helping to reduce human error and “false positives” while maintaining compliance and reporting needs. The analytics recording ability also keeps a history of money-laundering and attack patterns used by financial criminals, something that the machine learning aspects can adapt to over time as these strategies adapt.
Joe Friscia, president of NICE Actimize, also highlights the automated technology’s ability to free up financial crime experts within the company to spend more time investigating higher-level threats. The firm’s Suspicious Activity Monitoring solution, he says, “automates everything but the analysts’ final decision in every transaction, putting the emphasis on human decision-making instead of manual execution.”
“With resources devoted to 80% rote administrative work with only 20% intelligence,” added Friscia, “it was critical that we dramatically turn that unproductive scenario around.”
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