Chartis names SAS a Leader in anti-money laundering
Chartis has named SAS a category leader in trade-based anti-money laundering (TBAML) for its broad end-to-end automation and deep risk analytics capabilities.
The research group evaluated SAS and nine other vendors and published 'Trade-Based Anti-Money Laundering Solutions, 2022: Market and Vendor Landscape,' marking the first time Chartis has assessed this rapidly-growing area of financial crime compliance.
"The SAS solution is notable for combining data extraction, data fusion, document and transactional analytics, KYC/AML analytics and workflow management," the report's Vendor Analysis states.
"In particular, the integration of analytics for trade documents – to extract text from images and to perform various checks for trade fraud and AML risk indicators – stood out."
Additionally, the Vendor Analysis also acknowledges "SAS has rolled out the fully featured TBAML platform to a handful of clients, and currently leads the market in this nascent area."
Chartis's findings concluded that SAS is the highest-scoring in completeness of offering, recognising the company as a Leader in its RiskTech Quadrant Category.
Furthermore, Chartis has scored SAS' high' across all four criteria (data support, depth of typology coverage, breadth of analytical techniques, and workflow).
"Trade-based money laundering remains notoriously difficult to investigate due to immense international trade volumes and the complexity of trade transactions," Chartis financial crime risk management research principal Philip Mackenzie says.
"In this context, SAS can help financial organisations address the core categories of trade finance risk in a holistic way.
"Account and transaction activity in particular are key areas for SAS. In addition, the company has a library of prebuilt, ready-to-deploy TBAML typologies that employ AI and machine-learning capabilities to help detect anomalous activity."
As part of its TBAML offerings, SAS collaborated with EY to co-develop Trade Risk Analytics Compliance Kit (TRACK).
SAS explains that this advanced trade finance solution is designed to automate manual tasks and improve the detection accuracy of TBAML, sanctions risks and boycott violations.
The company says that implementing TRACK has seen approximately 100 checks replaced with a single, hybrid fraud/AML machine learning model.
This infrastructure assesses the probability of a trade transaction needing further investigation, and the model also learns from past outcomes.
Moreover, vigorous text mining and text analytics tools allow for critical contextual analysis buried in the documentation for about 9 million trade transactions annually, accounting for approximately 25 million related documents.
The initiative's award-winning results include a more than 30% jump in operational efficiency, accuracy rates above 85% for the fraud/AML model, and a 60% reduction in false positives by the sanctions screening module.
Citing the growing intensity of regulatory pressures, SAS says that financial services organisations will require effective data aggregation and a broad range of increasingly sophisticated analytics capabilities.
The company conducted a recent AML survey of 850 financial crimes professionals in collaboration with the Association of Certified Anti-Money Laundering Specialists and KPMG.
The results revealed unexpected innovation in AML technology, with 57% of respondents indicating that their businesses had either established AI or machine learning into their AML compliance processes, were piloting such solutions, or expected to implement them in the next 12-18 months.
"Global trade hit a record-breaking $28.5 trillion in 2021, underscoring the depth and complexity of monitoring for trade-based money laundering," said SAS fraud and security intelligence senior vice president Stu Bradley says.
"The sheer enormity of traded goods makes it easier for criminals to move vast sums of value in plain sight."
"Given pent-up demand on the global supply chain, it's critical that trade finance organisations reduce the friction of manual processes while managing their regulatory risk.
"Firms can rely on SAS' AI-driven, industry-proven solutions to cut through the noise and help focus scarce resources where they'll be most effective," Bradley adds.
The Chartis recognition comes at the same time as SAS is working with the European Banking Federation to host a virtual AML Masterclass series, examining how AI and machine learning can improve the effectiveness of banks in fighting financial crime.
