Enhanced SAS®Anti-Money Laundering now quicker to detect suspect activity

Advanced analytics and better transparency into transactions a boon to financial institutions

CARY, N.C. (March 15, 2006) – SAS, the leader in business intelligence, today underscored itscommitment to the financial services industry with the release of a new version of SAS Anti-Money Laundering. Complementing its recently announced SAS® Money Laundering Detection, the new offering includes several enhancements to help institutions worldwide fight against money laundering.

SAS Anti-Money Laundering now provides advanced analytics for detecting unknown types of behavior, enabling banks to better display the flow of funds between accounts so they can be more effective in identifying suspect relationships and high-risk accounts. Also, the advanced analytics offer scenarios that detect variances against normal behavior and expected activity, allowing banks to easily identify accounts having similar transaction behavior which may signal possible illegal money laundering activity.

The new version also delivers better transparency into customer transactions, making it easier for banks to see cases that have been closed or suppressed in support of audit and regulatory review processes. In addition, SAS Anti-Money Laundering provides visual clues, including background attachments for an investigator to see if a case has been worked and/or requires urgent attention.

“SAS is known for listening to our customers and working with them on developing solutions to address specific business issues,” said David Stewart, director of SAS’ anti-money laundering program. “This new version of SAS Anti-Money Laundering is a reflection of suggestions and recommendations from global financial institutions customers on how we can make this solution more powerful.”

Installed directly or through an application service provider, SAS Anti-Money Laundering is a sophisticated anti-money laundering solution that can take mountains of information from all areas of a financial business, manage and refine that information, and turn it into usable knowledge that will help a business automatically identify and classify suspicious behavior. It can help banks meet stringent government regulations, protect shareholder confidence and maintain a strong reputation. The solution offers an integrated and open-ended architecture that lets banks gather information across data sources, transform the appropriate data into real intelligence, detect suspicious activity and accurately alert investigators and authorities.

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