Home / Business / NICE Actimize Transforms Anti-money Laundering Industry

NICE Actimize Transforms Anti-money Laundering Industry

NICE Actimize Transforms Anti-money Laundering Industry

February 2018: NICE Actimize, a major player in the management of financial crime introduced an autonomous financial crime management solution in the AML category. The novel suspicious activity monitoring (SAM) solution integrates robotic process automation with machine learning analytics for an accurate crime detection. It virtually eliminates the manual search of third-party data, while reducing the investigating time for a single alert up to 70%.

Financial organizations and their compliance programs undergo hard realism of meeting regulatory requirements about reporting and detecting anti-money laundering schemes while managing the cost of compliance. NICE Actimize newly introduced autonomous financial crime management solution represents a massive shift in mitigating and unifying risk through targeted utilization of advanced analytics, big data and robotic process automation which reduces reputational risks.

NICE Actimize has added advanced machine learning capabilities into its solutions enabling detection of unidentified attacks. NICE Actimize applies a blend of both human expert models coupled with machine learning for reducing the noise of false positives which boosts financial crime investigations. With advanced analytics, the company has overcome the onslaught of attacks that have previously cost many losses. The new suspicious activity monitoring solution will help in detecting complex financial crime while increasing the team’s productivity.

Analyst View:

The introduction of autonomous financial crime management solution will help the company in mitigating risks of various financial institutions. With the rising financial threats, companies in the anti-money laundering industry continuously strive to introduce and enhance their software capabilities in order to meet the regulatory requirements and most importantly tackle money-laundering incidences. Financial institutions need machine learning that provides an advantage and advanced analytics that can evolve rapidly. The autonomous financial crime management solution expected to transform the approach of anti-money laundering industry to suspicious activity monitoring in the years to come.

About Shilohi Chandekar

mm
Ms. Shilohi R. Chandekar has been working as a Research Associate at Credence Research, Inc. for over a period of a few months now. She is a part of the ICT domain wherein, she is responsible for monitoring and analyzing the emerging market trends, technologies, and market behavior across various industries. She is also involved in scrutinizing data in order to come up with the key findings pertaining to the area of market study.

Check Also

Bosch Launched New Brakes That Could Reduce Air Pollution and Road Accidents

Bosch Launched New Brakes That Could Reduce Air Pollution and Road Accidents

On November, 2017, Bosch introduced a new brake called the iDisc that can cut air ...