SAS^® Anti-Money Laundering

Complete money laundering protection, full anti-money laundering compliance

Overview
Benefits
Features
Screenshots

SAS Anti-Money Laundering is an enterprise solution that facilitates the critical task of suspicious activity monitoring using a risk-based approach. The solution applies advanced analytics and scenarios against an institution's transactional data to identify suspicious behavior. Once identified, the investigative function provides a seamless workflow that increases effectiveness and efficiency.

Benefits

Improve accuracy of alerts and focus on high-risk events, rather than chasing all simple alerts.
Easily adapt to changing requirements.
Improve the efficiency and effectiveness of the investigative process.
Ensure security by monitoring all known institutional risks.

Data management.
Alert generation process.
Risk classification process.
Watch list matching.
Integrated case management.
Business analytics.
Easy administration.

Screenshot

SAS Anti-Money Laundering home screen

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Screenshots

How SAS^® Is Different

SAS Anti-Money Laundering bridges the usual gap between technology and compliance functions by providing a significant analytical tool that works through logical processes.
The solution's platform is adaptable to each institution's risk profile, and scenarios and risk factors are driven directly from the bank's anti-money laundering risk assessment and can be easily changed as the institution's or industry's risks change.
SAS Anti-Money Laundering does not merely assess transactions; it employs scenarios and risks across a wide array of bank knowledge to develop alerts.
The SAS platform can be integrated as part of an institution's overall financial crimes monitoring program instead of being limited to just money laundering.
A centralized data repository greatly enhances the ability of global institutions to centrally manage multiple subsidiaries from a central location, as well as monitor more risks with fewer redundant hardware resources, while ensuring that data governance and compliance policies are being followed.

Benefits

Improve accuracy of alerts and focus on high-risk events, rather than chasing all simple alerts.
- The system reduces the number of false positives by providing analytic tools that let the user refine monitoring policies and adjust scenarios and risk factors to achieve optimal results.
Easily adapt to changing requirements.
- The solution's data model includes a broad set of transaction types, products, channels and services. New data feeds can be imported into the system easily.
- Business users can configure scenarios and risk factors through a point-and-click interface.
- Ad hoc reports can be generated to answer virtually any question.
Improve the efficiency and effectiveness of the investigative process.
- Analysts can aggregate alerts into a case to dispose of work items more quickly and eliminate redundant tasks.
- The solution prioritizes high-risk events for investigation and provides compliance staff with clear explanations regarding why certain events should be investigated first.
- A risk scoring methodology provides a risk-ranked list of alerts using every customer transaction across every account in the institution.
- Investigators can drill down through risk scores to display all "red flag" characteristics of a customer.
- All transactions that caused the alert are displayed to support the decision process.
Ensure security by monitoring all known institutional risks.
- The solution's breadth and flexibility ensures that all institutional knowledge is assessed.
- Customer risk scores are based on prior behavior, expected behavior and known CIP information, which allows an unmatched depth of analysis.

Features

Data management.

A proven data model maps transaction records to support transaction, account, customer and household dimensions.
The data model includes the core schema for preparing transaction data for nightly batch analysis.
A knowledge center data schema supports data retention and investigation.

Alert generation process.

Scenarios and risk factors are applied to transactions to detect potentially suspicious activity.
Events that meet the rule parameters become alerts.
Alerts are subject to additional workflow processes, such as suppression, risk scoring and routing.

Risk classification process.

A customer's on-board risk score is automatically integrated with their actual transactional behavior.
Risk analysts can reassess a customer's risk classification manually, or upon periodic review.
Information gathered during enhanced due diligence can be documented on the customer to support a more accurate view of money laundering risk.

Watch list matching.

The system imports sanctions and other watch lists to identify persons, organizations or high-risk jurisdictions that represent regulatory risk.
Fuzzy matching logic is used to increase the accuracy of entity matches.
Transaction, party or counterparty matching lists can be worked as alerts or cases.

Integrated case management.

A Web-based user interface supports the management, investigation and reporting needs of anti-money laundering analysts and investigators.
All actions performed on alerts and cases are documented and retained for audit and regulatory review purposes.
The system automatically identifies alerts that may be related to existing cases to speed the investigative process.

Business analytics.

Ad hoc client software allows business analysts to report and analyze information contained in the anti-money laundering schemas.
The SAS Business Intelligence platform is bundled with the solution to provide extended reporting and analysis capabilities.
Business analysts can generate ad hoc queries and reports or use powerful data mining capabilities to analyze trends in customer behavior.

Easy administration.

A point-and-click environment enables easy modification of scenarios and risk factors, the creation of new scenarios and risk factors, and the creation of customized routing rules for distributing the work load to compliance analysts.