SAS^® Anti-Money Laundering Features

Data management

A financial services 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.

Centralizes enrichment and transformation of multiple data types to get it analytic ready.

Cloud-native and open analytics engine
Cohesive environment for all analytical tasks from data access, preparation, interactive exploration, optimization, machine learning, AI, and other advanced model development to deployment activities.

Combination of proven rules with advanced analytic techniques including machine learning, deep learning and artificial intelligence
Peer-group anomaly detection
Create cases from alerts and file regulatory reports to government authorities
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.

Aggregation of alerts at the entity level that provide a holistic review of the risk presented by the entity to the institution.
Auto-prioritization of alerts.
Disposition options and management overview.
Workflow builder.