SAS^® Customer Due Diligence

Continuous event-based risk rating

Event-based scoring in order to refine the risk of a customer relationship.
Individually weighted attributes to scale and articulate the risk to the organization.
Flexible mapping of risk attributes to additional data sources.
Ability to introduce new data elements and test on production data.

Data management

Common data model with SAS Anti-Money Laundering.
Enrichment of customer profiles through consolidation of customer information from disparate systems.
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.

Preconfigured risk rating model and risk bands.
Preconfigured customer risk rating scenarios.
Ability to create, govern and update customer monitoring scenarios with a visual, built-in scenario builder.
Extendable end user Interface with pre-built screens.
Preconfigured dispositions including EDD Review.
Preconfigured EDD review pages and workflow.
Preconfigured dispositions.
Periodic review tracking.
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.