As banks  compliance teams face a growing deluge of alerts, they need to distinguish suspicious from legitimate behavior quickly and confidently. Chartis Research has again named SAS a Category Leader in its AML Transaction Monitoring Solutions, 2026: Quadrant Update.

In Chartis' latest evaluation of the industry's 49 foremost providers of anti-money laundering solutions, SAS^® Anti-Money Laundering on SAS^® Viya^® earned best-in-class ratings in four of the report's seven capability assessments, including:

1. Data and system integrations. SAS Viya integrates transaction, customer and risk data across existing systems to inform detection and investigations as well as support intelligence sharing between institutions' AML and fraud teams.
2. Risk typology modeling. SAS combines statistical techniques, machine learning and behavioral analytics to tailor detection strategies to customer profiles, transaction patterns and emerging risks, giving banks the agility to adapt to changing money laundering threats.
3. Analytical modeling. AI-assisted code generation streamlines model development, while statistical techniques help institutions focus models on the factors most relevant to risk detection.
4. Model quality and validation. SAS supports model validation and ongoing monitoring, helping institutions address drift, bias and declining performance while also maintaining governance and oversight throughout the model life cycle.

Chartis also recognized SAS' advanced capabilities in workflow automation; solution packaging and deployment; and speed, volume and performance.

"SAS has significantly expanded the use of agentic AI, resulting in enhancements to analytical modeling, model quality and validation, and workflow automation," said Sean O'Malley, Research Director for Financial Crime and Control at Chartis. "The company's solution combines traditional scenario-based monitoring with advanced analytics, machine learning, network analysis and AI-driven risk scoring, producing enhanced results."

From more alerts to more useful intelligence – with built-in oversight
In its accompanying SAS Vendor Spotlight, Chartis cites the industry's shifting transaction-monitoring expectations. Fewer, higher-value alerts help investigators focus their limited time on legitimate risks – but improving alert quality demands richer context on top of more precise analytics and models able to adapt in parallel with criminal behavior.

Chartis highlights how SAS embeds AI across Viya to reduce manual coding, accelerate model development and deployment, and focus detection on meaningful risk signals. Behind those alerts, built-in model governance and responsible AI capabilities help banks maintain oversight from the first line of code through deployment and everyday use.

"Effective anti-money laundering programs extend well beyond alert management and suspicious activity filings," said Stu Bradley, Senior Vice President of Risk, Fraud and Compliance Solutions at SAS. "Investigators require a clearer picture of what warrants their attention. AI can help teams connect more signals and uncover risks that traditional approaches might miss. But if a bank can't recognize when a model has gone off track or explain why it generated an alert, it has simply traded one blind spot for another."

FRAML: Shared intelligence, fewer blind spots
Financial institutions have come to recognize their blind spots often sit between siloed functions. Chartis identifies growing momentum behind the convergence of fraud prevention and anti-money laundering, more commonly called FRAML.

Fraud and AML teams often see different facets of the same criminal activity. Suspicious payments or unusual account activity spotted by a fraud team could help an AML investigator connect the dots. Meanwhile, an AML investigation might expose criminal networks or money flows that help the fraud team detect related activity. Sharing those signals gives the institution a more complete risk picture, while allowing each team to follow its distinct investigative processes and regulatory controls.

Chartis credits SAS' integration of its fraud and AML capabilities with helping institutions bring transaction data, customer information, risk indicators and analytical models into a more comprehensive view of financial crime risk. This supports broader detection, decisioning and investigative workflows across existing technology environments.

Leadership across risk, fraud and compliance
"The rapid changes this year with respect to speed, volume and performance have produced an increasingly stratified set of results for many transaction monitoring vendors, but SAS has adapted to these changes and outpaced several competitors in the process," said O'Malley.