A sophisticated, end-to-end anti-money laundering solution, delivering unprecedented prediction and detection capabilities, lowest false positives and reduced investigation times – while decreasing overall compliance costs.
Stay ahead of emerging risks and changing regulations. SAS® has helped financial institutions achieve more than 90% model accuracy, reduced false positives by up to 80% and improved the SAR conversion rate fourfold.
Expose complex, hidden networks.
Quickly uncover emerging, complex money laundering and terrorist financing threats with network and entity generation processes that automatically build network diagrams and reveal hidden relationships. Advanced analytics enables entity resolution by looking at multiple data sources and references to a customer, then accounting for inconsistencies, errors, abbreviations and incomplete records to help determine whether they relate to the same entity.
Improve operational efficiency.
Empower AML investigators with an integrated, configurable, user-friendly alert and case management solution that offers self-service capabilities and intelligently prioritized alerts for expedient triage, investigation and disposition. An interactive, drag-and-drop page builder lets administrative users conﬁgure settings, views and workﬂows to tailor the application for unique business or user requirements.
Rely on comprehensive suspicious activity monitoring and reporting.
Gain more comprehensive risk coverage with a hybrid approach to monitoring transactions. This approach combines proven rules to detect known risks with advanced analytic techniques – including machine learning, deep learning and AI – to identify unknown risks and hidden relationships. Administrative users can create, govern and update program-defined monitoring rules with a custom, built-in scenario builder. Integrated workflow management helps AML teams seamlessly create cases and file regulatory reports with government authorities.
Comply with customer due diligence and beneficial ownership rules.
Quickly verify customer information at account opening using customer onboarding capabilities. Our risk-based, scalable approach supports the complete customer life cycle – from initial onboarding to ongoing customer due diligence efforts. Analysts and investigators can review events on a continuous basis – as they happen – instead of reviewing over longer time intervals. Sophisticated visualization capabilities allow AML investigators to quickly spot and monitor beneficial owners.
Stay in compliance with SAS® Real-Time Screening.
Comprehensively screen transactions in real time, and customers in batch, against a wide variety of watchlists – including PEPs, enforcement lists like the Section 314(a) program, and other internal or third-party lists (e.g., Do Not Do Business) – with SAS Real-Time Screening. Our superior scoring algorithm − with organization-specific filtering rules, unique name matching analytics, multilingual screening capability and alert consolidation − generates high-quality hits with low false positives. The solution also supports real-time alerting and interdiction capabilities during customer onboarding.
Gain complete transparency.
Ensure success with internal model governance boards and external regulators through an open box (transparent) environment. SAS Anti-Money Laundering offers complete visibility into scenarios that trigger red flags and provides clear explanations regarding alert generation for outcome auditing.
Get to Know SAS® Anti-Money Laundering
This solution runs on SAS® Viya®, which has the breadth and depth to conquer any analytics challenge, from experimental to mission critical. SAS Viya extends the SAS Platform to enable everyone – data scientists, business analysts, developers and executives alike – to collaborate and realize innovative results faster, with flexible licensing and pricing options to accommodate your current and future needs.
Explore More on SAS® Anti-Money Laundering and Beyond
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- Article Mobile payments, smurfs and emerging threatsM-payment remittances are replacing traditional banks and money services that have historically charged high fees for small transfers. Former US Treasury Special Agent John Cassara maps what he sees in the road ahead and gives advice for protecting your firm.
- Analyst Report SAS named Best in Class in Aite Matrix: Case Management to Combat Global Fraud and Money LaunderingAite names SAS Best in Class in Aite Matrix: Case Management to Combat Global Fraud and Money Laundering.
- E-Book Fight money laundering with these 5 game changers from SASEffectively battling dynamic financial crime threats requires new capabilities for AML defense – such as artificial intelligence, machine learning, intelligent automation and advanced visualization.
- White Paper What is next-generation AML? The fight against financial crime fortified with robotics, semantic analysis and artificial intelligence
- Customer Story Analytics powers anti-money laundering effortsSAS helps Landsbankinn reduce false positives and streamline investigation.
- Customer Story Fast analytical defenseDeutsche Kreditbank AG combats fraud and money laundering with SAS.
- Customer Story A risk-based approach to combat money laundering in IsraelSAS Anti-Money Laundering helps Ayalon Insurance monitor suspicious activity and meet challenging regulatory requirements.
- Article Next generation anti-money laundering: robotics, semantic analysis and AIAnti-money laundering taken to its next level is sometimes referred to as AML 2.0 or AML 3.0. What does this next wave of AML technology look like? What can it do that you can’t do with traditional AML? See the results innovative financial institutions around the globe are already getting.
How AI and Machine Learning Are Redefining Anti-Money Laundering
Machine learning can play a big role in the defense against money laundering, either to automate tasks that formerly required human intervention, such as managing the data to train models, or detect more financial crimes risk that rules and more basic analytic techniques might miss.
AI Is at the Forefront of Reducing Money Laundering and Combating the Financing of Terrorism
See how artificial intelligence (AI), machine learning (ML) and robotic process automation (RPA) are helping firms overcome the challenges, improve results and make AML/CFT programs more efficient and effective.
Enhancing AML Efficiency and Effectiveness
Celent discusses how banks are adopting artificial intelligence, machine learning and robotic process automation, including the benefits and key lessons learned. The paper explores considerations for AI adoption and future benefits for the AML industry.
Fighting Financial Crime Amidst Growing Complexity
Growing speed, volume and technological complexities raise the challenges in AML. However, recent developments in artificial intelligence, machine learning and robotic process automation are producing solutions that improve AML programs.
- White Paper Customer Due DiligenceTake a more comprehensive, continuous approach to customer due diligence where risk ratings are always up to date and reflective of the latest demographic and transactional changes.
- Customer Story Preventing crime and ensuring compliance at 120 Nordic banksSDC enables small and medium financial institutions in four Nordic countries to stay compliant.
Check out these products related to SAS® Anti-Money Laundering, built on the powerful SAS® Platform.
- SAS/ACCESS® SoftwareRead, write and update data regardless of its native database or platform.
- SAS® Data PreparationQuickly prepare data for analytics in a self-service, point-and-click environment with data preparation from SAS.
- SAS® Real-Time ScreeningScreen transactions in real time, and customers in batch, against a variety of watchlists.
- SAS® Visual AnalyticsVisually explore all data, discover new patterns and publish reports to the web and mobile devices.
- SAS® Visual Data Mining and Machine LearningSolve your most complex problems faster with a single, integrated in-memory environment.
- SAS® Visual Text AnalyticsUncover insights hidden in text data with the combined power of natural language processing, machine learning and linguistic rules.