Aberdeen Group, a UK-based global investment management firm, has selected NiCE Actimize’s X-Sight Suspicious Activity Monitoring (SAM) and Watch List Screening solutions to enhance its financial crime operations. These solutions are part of NiCE Actimize’s portfolio of anti-money laundering (AML) offerings.
The X-Sight SAM solution utilizes advanced analytics, machine learning, and graph-based analytics to identify patterns of illicit behaviors and suspicious transactions. Complementing this, NiCE Actimize’s WL-X, an AI-powered screening solution, provides advanced matching techniques, predictive analytics, and access to global lists and data sources for party and real-time transaction screening. This capability enables the rapid and precise identification of high-risk customers and counterparties. According to Aberdeen Group, this approach has allowed the firm to better support client and customer outcomes through the deployment of next-generation analytics and enhanced case management.
“Our industry-leading anti-money laundering portfolio provides a comprehensive view of potential risks. Not only does its multi-tiered approach enhance the ability to catch suspicious activity early, but it also ensures comprehensive protection against evolving financial crime threats,” stated Craig Costigan, CEO of NiCE Actimize. “We look forward to continuing to work with Aberdeen to enhance the effectiveness of its financial crime prevention.”
Aberdeen Group, headquartered in Edinburgh, is focused on expanding its direct and advised wealth platforms and repositioning its specialist asset management business. As of March 31, 2025, the firm managed and administered £500.1 billion of its clients’ assets.
NiCE Actimize, a business unit of NiCE (NASDAQ: NICE), specializes in fraud prevention, financial crime detection, and regulatory compliance. The company states that over 1,000 organizations in more than 70 countries utilize its solutions. NiCE, a global provider of AI-powered platforms, serves organizations across over 150 countries.
