SAS® Anti-Money Laundering Features
- A banking-specific data model:
- Maps transaction records to support transaction, account, customer and household dimensions.
- Includes the core schema for preparing data for nightly batch analysis.
- A knowledge center data schema supports data retention and investigation.
- Support for multiple data types (nonmonetary event data, geographic data, risk lists, third-party data, associate data and a variety of customer information data) in addition to transaction data.
High-performance analytics & visualization
- Visualize emerging risks.
- Scenario builder enables testing, tuning and simulating scenarios in seconds to improve scenario efficacy and adhere to model governance best practices.
- Provides rapid access to customer, account and transaction data.
- Uses array processing for alert generation.
- Uses peer-group anomaly detection.
Suspicious activity monitoring & reporting
- Applies scenarios and risk factors to transactions to detect suspicious activity.
- Generates alerts for events that meet rule parameters.
- Subjects alerts to additional workflow processes (suppression, risk scoring, routing).
- Includes an easy-to-use, point-and-click interface that enables:
- Creation and modification of scenarios and risk factors.
- Creation of customized routing rules for workload distribution.
- Flexible suppression capabilities.
- Ability to import sanctions and other watch lists to identify persons, organizations or high-risk jurisdictions that represent regulatory risk.
- Fuzzy-matching logic increases the accuracy of entity matches.
- Ability to work transaction, party or counterparty matching lists as alerts or cases.
- Combines functionality with the Dow Jones Watchlist service.
Investigation & alert management
- Aggregation of alerts at the entity level that provide a holistic review of the risk presented by the entity to the institution.
- The number of alerts and aggregation of triggering transactions are displayed for each alerted entity.
- Layout for alerted entity and case queues allows for bulk actions.
- Flat navigation was designed to create user efficiencies and speed the decision-making process.
Peer-group anomaly detection
- Compare an entity's current behavior with its historical behavior, as well as the behavior of its peers.
- Include multiple peer groups and detect outliers both above and below expected behavior.
- Ability to index and analyze data quickly.
- Gives the user the ability to search comments and attachments.
- Was used by a team of investigative journalists to compile information provided by the Panama Papers to build stories against political figures.
- Partitioning data by allowing for separate schemas within a database.
- Allowing each schema to have its own AGP process.
- One web application for all schemas means easier management.
- Simplified implementation.