SAS received the highest score in the current offering category among 15 vendors evaluated
AI and analytics titan SAS has been named a Leader in anti-money laundering solutions by Forrester. The Forrester Wave™: Anti-Money-Laundering Solutions, Q3 2022 evaluates the industry’s 15 most significant anti-money laundering (AML) technology providers, assessing and ranking them based on 26 evaluation criteria.
As criminals grow more sophisticated in their money laundering methods, financial services organizations like banks and insurers rely on ever-more advanced AML solutions to detect financial crime. Notably, SAS® Anti-Money Laundering attained the highest score of any evaluated vendor in the “current offering” category. The AI-powered anti-money laundering software solution scored 4.85 out of 5 overall and received the highest possible score in 12 of the category’s 13 criteria, including:
- Users and roles.
- Watchlist management and screening.
- Rules-based scoring and alerting.
- AI/machine learning-based scoring and alerting.
- Internationalization, currencies, and reporting.
The influential research and advisory firm’s assessment of SAS’ current AML offering notes that it “provides an overall robust solution.”
“Key management for encrypting data is explicitly configurable,” the report continues. “Rules-based and AI/ML based risk scoring is nice and functional. The solution can also provide rule recommendations. Workflow for model building is also functional and intuitive. Case management screen customization and usability is superior.”
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According to a global AML study by SAS, KPMG and the Association of Certified Anti-Money Laundering Specialists (ACAMS), one-third of financial institutions have accelerated their adoption of AI and machine learning for AML compliance since the COVID-19 pandemic began. Moreover, those that have deployed these advanced AML capabilities are seeing tremendous benefits.
“While anti-money laundering compliance expectations have increased due to more complex regulatory priorities, AI and machine learning are delivering on their promise of making AML programs more automated, efficient and effective,” said David Stewart, Director of Financial Crimes and Compliance at SAS. “It’s not hype or hyperbole. SAS has helped financial institutions achieve more than 90% model accuracy, reduce false positives by up to 80% and realize a twofold improvement on their SAR conversion rate.”
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