Rapidly increasing risk – combined with evolving government regulations – requires an advanced strategy for monitoring data for illicit activity. SAS helps you take a risk-based approach, making it easier to manage alerts, test scenarios and comply with industry regulations.
Empower analysts to make better decisions faster amid rising regulatory expectations.
Get quick, accurate alerts.
Know almost instantly if suspicious activity is happening. SAS segmentation strategies can identify patterns based on an entity's history or its peers – an approach proven to increase SAR conversion rates. And because you can manage alerts from a centralized system, it's easier to preserve data security, minimize IT support costs and promote collaboration across the enterprise.
Easily track flow of funds.
With our funds tracking capability, it's easy to visualize the flow of funds between the focal entity and other entities of interest. The Sankey diagram used to track the flow of funds helps you see debits and credits, as well as variation in volume of funds between entities.
Be transparent. And compliant.
With anti-money laundering and counterterrorist financing regulations affecting the industry, not only must you file timely and accurate SARs, but you also must be able to show regulators and auditors how you analyze and prioritize risks. With our technology, you can automatically monitor suspicious behavior, document the decision process and, if applicable, file pre-populated reports with the appropriate authorities.
Find the best scenario and take the best action.
SAS high-performance visualization tools significantly reduce the time required to analyze data, visualize patterns, hypothesize monitoring strategies and validate scenario deployments. With SAS Visual Scenario Designer, you can simulate and validate scenarios until you find – and implement – the right one. The end result? Better decisions, faster.
Instantly access the information you need.
In an industry that moves fast, you don't need complicated user interfaces slowing you down. SAS Anti-Money Laundering technology has an interface that's designed to facilitate quick, accurate decisions – which means all the information you need is one or two clicks away.
Get to Know SAS® Anti-Money Laundering
Explore More on SAS® Anti-Money Laundering and Beyond
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- 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.
- White Paper Enterprise Risk Mitigation for Community Banks To help meet fraud and AML challenges, SAS and Jack Henry Associates have partnered to offer JHA Enterprise Risk Mitigation Solutions™ (ERMS), a cloud-based customization of SAS Visual Investigator that converges fraud detection and AML compliance in a single, intuitive, visual workspace.
- 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.
- 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.
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.
- Article Anti-money laundering and counter-terrorist financingTo monitor for financial crimes, an essential element for both anti-money laundering and counter-terrorist financing is using data analysis to detect unusual activity during processing by monitoring transactions, customers and the network of behaviors.
What is next-generation AML?
The fight against financial crime fortified with robotics, semantic analysis and artificial intelligence
Developing Scenario Segmentation and Anomaly Detection Models
An 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.
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.
- Webinar What Is a Next-Gen AML System?Learn how AI, machine learning and robotic process automation can help the global banking industry and financial firms transform the fight against money laundering.
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.
Analytics and the AML Paradigm Shift
Financial 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.
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.
Best Practices in Transaction Monitoring Scenario Threshold Tuning and Model Verification
Learn about a best practices approach to performing scenario verification and threshold tuning projects for BSA/AML transaction monitoring systems.
- 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.
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