Addresses many data challenges, from processing big data to accessing and integrating legacy sources – all in a single platform.
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.
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.
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.
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.
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.
The fight against financial crime fortified with robotics, semantic analysis and artificial intelligence
Keeping pace with anti-fraud and anti-money laundering (AML) regulations represents a significant burden for financial institutions, particularly smaller ones. To help meet these 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, AML compliance and investigation in a single, intuitive, visual workspace.
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.
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.
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.
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.
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.
Learn about a best practices approach to performing scenario verification and threshold tuning projects for BSA/AML transaction monitoring systems.
Check out these products related to SAS® Anti-Money Laundering, built on the powerful SAS® Platform.
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