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.
Comprehensive solution
Supports transaction monitoring, customer due diligence, customer onboarding, real-time watchlist screening, case management and regulatory reporting capabilities on a single, integrated platform powered by AI, machine learning, robotic process automation and advanced network analytics.
Data orchestration
Centralizes the enrichment and transformation of multiple data types – including transaction data, nonmonetary event data, geographic data, risk lists, third-party data and a variety of other customer data – to get it analytics-ready.
Nimble platform
Unites all analytical tasks – from data access, preparation, interactive exploration, optimization, machine learning, AI and other advanced model development to deployment activities – in a cohesive, open, high-performance environment.
Entity-centric investigations
Provides a holistic view of risk with entity analytics that enables AML analysts and investigators to visualize complete networks through the network viewer and dive deep into relationships using link expansion.
Cloud-native, elastic & scalable
Leverages SAS Viya. Optimizes complex analytical, in-memory calculations for unconstrained environments. Adjusts automatically in constrained environments. Lets you quickly experiment with different scenarios and apply more sophisticated approaches to increasing amounts and speeds of incoming data.
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
本解決方案可在 SAS Viya 上運作，這是一個現代化、開放的平台，具有能夠克服任何分析難題的廣度與深度。
SAS® Viya®擴充了SAS平台協助每一個人-資料科學家、商業分析師、應用程式開發人員到高階主管等所有人，提供協作與快速實現創新。
Explore More on SAS® Anti-Money Laundering and Beyond
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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.
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White Paper
What is next-generation AML? The fight against financial crime fortified with robotics, semantic analysis and artificial intelligence
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Customer Story
洗錢防制SAS 幫助 Landsbankinn 降低誤報率並簡化調查過程
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Customer Story
Fast analytical defenseDeutsche Kreditbank AG combats fraud and money laundering with SAS.
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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.
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White Paper
How AI and Machine Learning Are Redefining Anti-Money LaunderingMachine 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.
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White Paper
Developing Scenario Segmentation and Anomaly Detection ModelsAn effective AML transaction monitoring strategy includes segmenting the customer base by analyzing customer activity and risk characteristics in order to monitor them more effectively. This paper discusses how to blend both quantitative and qualitative methods to tune scenarios to identify the activity that poses the most risk to the bank.
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White Paper
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.
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White Paper
Enhancing AML Efficiency and EffectivenessCelent 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.
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White Paper
Analytics and the AML Paradigm ShiftFinancial organizations are deploying artificial intelligence and machine learning in the fight against financial crimes. David Stewart, Director of Pre-Sales for the Global Security Intelligence Practice at SAS, offers tips to help separate fact from market hype when reviewing new data analytics tools.
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White Paper
Fighting Financial Crime Amidst Growing ComplexityGrowing 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.
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White Paper
Best Practices in Transaction Monitoring Scenario Threshold Tuning and Model VerificationLearn about a best practices approach to performing scenario verification and threshold tuning projects for BSA/AML transaction monitoring systems.
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White Paper
AML Customer Risk RatingThis paper is geared toward the technical audience to describe the benefits of, and how to adopt, statistical modeling for AML and CDD.
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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.
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Customer Story
Preventing crime and ensuring compliance at 120 Nordic banksSDC enables small and medium financial institutions in four Nordic countries to stay compliant.
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