SAS unveils financial crimes suite

Source: SAS

Getting away with financial crime just got harder. The latest SAS Financial Crimes Suite arms institutions to detect potential suspicious activity more efficiently than ever.

A new customer due diligence solution within the suite more accurately detects changes in a customer's risk profile. Enhanced anti-money laundering and case management capabilities also make it easier to have a complete view of threats across an institution's financial crimes investigation unit.

"A comprehensive view of potential threats will help in efforts to thwart criminals from successful attempts of hiding illicit funds," said James Wester, Global Payments Research Director at IDC Financial Insights. "A technology infrastructure with customer risk rating and high-performance analytics will help speed detection and investigation in all channels. Companies like SAS are bringing to market a full suite of modules to support money laundering compliance, customer due diligence and fraud prevention all within a unified framework and user interface for more efficient investigations."

Today's rigorous regulatory environment requires banks to move quickly with confidence. SAS Financial Crimes Suite uses a visual scenario designer to recommend optimal detection models. The designer instantly assesses the impact of potential scenarios and risk-rating changes. In-memory architecture speeds analysis of real-time testing environments, reducing guesswork through improved model efficiency.

SAS® can focus precious resources on the highest-risk relationships

To identify potential money launderers and people funneling money to terrorists, institutions must constantly assess customer activity. The new SAS Customer Due Diligence does this by weighing all customer data to set baseline expectations.

Data management features easily integrate key customer attributes from external sources and detect incriminating relationships. The regulatory reporting interface controls both workflow and investigations. Context-aware analytics intercept and assess events for possible risk. The resulting baseline customer score can be automatically updated with a new risk rating based on behavior changes.

The solution streamlines the review process by:

  • Making financial institutions aware of changes in customer behavior faster than ever.
  • Providing a risk-rating feature to ensure adherence to standard policies, procedures and controls through flexible workflow.
  • Offering fully auditable case management that automatically tracks all aspects of investigations for consistent investigative and quality assurance processes.

SAS amps up detection for more effective investigations, case management

Time is critical in combating money laundering. SAS High-Performance Anti-Money Laundering speeds relevant information to investigators in minutes, rather than hours. By adding enhanced correspondent banking scenarios to the solution's data model, SAS further strengthened the detection layer to zero in on potential criminals. The new relationship grid helps investigators review subjects faster by quickly assessing party details associated with possible delinquent behavior.

To increase detection capabilities, a peer group anomaly component has also been added to SAS High-Performance Anti-Money Laundering, which compares an entity's behavior to its historical behavior and the behavior of its peer groups. Peer grouping has also been expanded, adding multiple peer groups and analytics to detect outliers on expected behavior.

SAS High-Performance Anti-Money Laundering increases monitoring effectiveness and efficiency through rapid information from new scenario tests via live production data.

SAS Enterprise Case Management has also been enhanced by replacing advanced querying with a single search field, encompassing all content included in the SAS solution. Information is captured and tracked through a central audit service, making investigations seamlessly auditable. More efficient investigations result from the new "to do" lists in the subject field of cases. 

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