Leading Provider of AI-Powered Fraud and Anti-Money Laundering Solutions
SAS has been recognised as a Market Leader in the latest Datos Insights assessment of fraud and anti-money laundering (AML) case management solutions. The company was featured in the newly published Datos Matrix: Fraud and AML Case Management report, which evaluated nine notable solution providers in the sector. SAS achieved the highest score for Vendor Stability, reflecting its longstanding operation in the global market and client retention rates that exceed 90 per cent, according to Datos Insights. The company also earned a top ranking for Product Features, specifically for the case management capabilities within its AI-powered financial crime management platform, built on the cloud-native SAS Viya platform. This platform incorporates SAS Fraud Decisioning for real-time detection, SAS Anti-Money Laundering for regulatory compliance, and SAS Visual Investigator for case management.
Becki LaPorte, Strategic Advisor in the Fraud and AML Practice at Datos Insights and co-author of the report, commented on the increasing prevalence and complexity of fraud and money laundering schemes, noting the role of technology in combating these trends. As AI-fuelled fraud and money laundering threats continue to grow in scale and sophistication, financial institutions require technology that unifies detection and investigation, underpinned by strong governance. SAS brings those capabilities together in a single platform that provides organisations with the depth to address complex threats, the agility to adapt to evolving schemes, and the intelligence to drive faster, more accurate decisions. The report highlights SAS’s strengths in AI-driven automation and its ability to merge fraud and AML functions, showcasing features such as continuous risk monitoring and advanced entity resolution.
Categories: Vendor Stability, Product Features, Case Management Capabilities
Tags: SAS, Market Leader, Fraud, Anti-Money Laundering, Case Management, AI, Cloud-native, Risk Management, Investigational Efficiency, Automation