SAS named Forrester leader in financial crime tools

SAS has been named a Leader in Forrester's latest assessment of financial crime management solutions, receiving the highest score for current offering among 15 suppliers.

In its Financial Crime Management Solutions evaluation, Forrester gave SAS 4.70 out of 5 for current offering. The analyst firm awarded SAS the top possible score in nine of 11 criteria: data integration, administrator management, watchlist management and screening, AI and machine learning-based risk scoring, transaction type support, queue definitions and alert routing, case management, third-party integrations, and regulatory and operational reporting.

The assessment comes as banks and other financial institutions try to bring fraud controls and anti-money laundering work closer together. Forrester defines financial crime management solutions as integrated platforms that combine enterprise fraud management with know-your-customer and anti-money laundering functions.

SAS was the only supplier in the review not to receive any below-par scores across the current offering criteria. Customer feedback was also above average relative to other suppliers, with users highlighting machine learning model building and testing.

Converging systems

The ranking comes as financial institutions face pressure to connect information that often sits in separate systems, including identities, accounts, transactions, behavioural indicators, and other signals used to detect suspicious activity and investigate potential crime.

Analysts and suppliers increasingly use the term FRAML to describe the convergence of fraud and anti-money laundering functions. The idea is that institutions can improve detection and investigation by treating fraud and money laundering as connected risks rather than separate compliance and security problems.

In its evaluation, Forrester wrote: "SAS' vision shines with its converged support for AML and fraud management plus agentic AI capabilities for investigations and decisioning."

It also said: "Overall, SAS offers one of the strongest solutions in terms of technical capabilities."

Governance focus

The report also pointed to the growing role of AI agents in investigations and decision-making. As more financial institutions test automation in areas such as alert triage, case review, and data preparation, governance has become a central issue for software buyers and regulators.

Forrester noted that "AI governance is also integral" to SAS' approach. The report also referred to the company's AI agent for extracting schemas from data sources, its range of data source integrations, and its algorithms for machine learning-based risk scoring.

Stu Bradley, Senior Vice President of Risk, Fraud and Compliance Solutions at SAS, said the market is moving towards integrated data and stronger oversight as firms deploy more AI in financial crime controls.

"Financial institutions cannot converge fraud and AML detection on fragmented data, and they cannot safely scale agentic AI without trusted data and governance," Bradley said.

He also linked the findings to demand from institutions that want systems able to work across multiple data environments and technical stacks.

"Forrester's evaluation reflects firms' urgency - and SAS' ability - to connect disparate data sources, work across technologies and programming languages, and apply advanced analytics responsibly and consistently across fraud and financial crime detection," Bradley said.

Broader market

The Forrester ranking adds to a broader debate over how banks should modernise financial crime operations as transaction volumes rise and criminal methods evolve. Traditional systems have often produced large volumes of alerts, creating operational strain for investigators and compliance teams.

Suppliers in the sector are responding by promoting platforms that combine data integration, analytics, alert routing, and case management in one environment. The commercial argument is that a more unified approach can help institutions decide which alerts need attention rather than simply generating more of them.

Bradley said this becomes more important as AI agents take on more investigative work with less direct human intervention.

"As AI agents play a greater role in investigations and decisioning, strong governance and human oversight are paramount," he said. "Not to automate for automation's sake, but to give investigators better context, more intelligent prioritisation, and trusted decision support so they can confidently tackle evolving threats. That's the kind of responsible, data-driven AI SAS delivers."