NICE Actimize Transforms Anti-Money Laundering with New Suspicious Activity Monitoring Solution Utilizing Robotic Process Automation and Artificial Intelligence Technologies
By FF Newsroom · 23 May 2018

Financial services organizations and their compliance programs face the hard realities of meeting regulatory requirements around detecting and reporting anti-money laundering schemes, while managing the cost of compliance. Today NICE Actimize, a NICE (Nasdaq:NICE), business and leader in autonomous financial crime management solutions, takes aim at this challenge with its next generation Suspicious Activity Monitoring (SAM) solution, which combines machine learning analytics for laser-accurate crime detection with robotic process automation, virtually eliminating the manual search for third party data, increasing team productivity, and reducing investigation time for a single alert by up to 70 percent.
The new Suspicious Activity Monitoring solution introduces NICE Actimize’s innovative concept of Autonomous Financial Crime Management to the anti-money laundering category for the first time. NICE Actimize’s recently-announced Autonomous Financial Crime Management approach represents a massive shift in unifying and mitigating risk through targeted utilization of big data, advanced analytics everywhere, artificial intelligence and robotic process automation which in concert reduce reputational risk.
Leveraging NICE Actimize’s experience in advanced analytics and transaction monitoring solutions, the ultimate goal of SAM is to leverage intelligence and automation to reduce human effort and error, meeting regulators’ requirements to detect and report sophisticated crime schemes.
Key elements of the new SAM solution also include:
- Expert-infused machine learning: While financial crime analysts provide oversight to the process, the solution’s machine learning models work to enhance detection and reduce false positives.
- Analytics agility: Automated tuning and optimization keeps AML analytics faster and more flexible than fast-changing financial crime attack patterns and money laundering schemes.
- Managed analytics and information-sharing: Cloud-managed analytics takes the burden of model tuning and optimization off financial services organizations. Meanwhile performance dashboards using cloud-based data provides organizations with insight into the performance of their SAM analytics and lets them compare those to industry peer organizations.
- Virtual workforce: Robots will assume the rote tasks associated with AML operations, freeing up financial crime experts to focus on the more complicated elements of an investigation.
- Visual storytelling: A simple graphical view of money laundering cases means investigators no longer spend hours constructing the stories behind suspicious activity reports.