SAS^® for Enterprise Fraud and Financial Crime Features

A hybrid analytic approach

Business rules for automatically flagging suspicious activities.
Near-real-time transaction monitoring.
Anomaly detection for uncovering abnormal patterns of behavior.
Predictive modeling for identifying new or emerging threats based on previous threats.
Network analysis for linking multiple parties through associative behavior or common ownership.
Adaptive segmentation with advanced neural networks.

Identifies behavior patterns among customers, accounts or other entities that only appear suspicious when viewed in a larger context across a community of related accounts or entities.
Analyzes activities and relationships within a network of related entities, such as customers who share demographic data or transactions.

A banking-specific data model includes correspondent banking scenarios to further strengthen detection methods in the high-risk category of correspondent banking.
A relationship grid enables fast assessment of details associated with correspondent banking alerts and the entities connected with them.

Compares an entity’s behavior to its historical behavior, as well as the behavior of its peers.
Supports multiple peer groups.
Provides outlier detection both above and below expected behavior.

Rates new customers and updates existing customer scores in three primary categories – entity, geography and product type – based on key events that could affect the overall risk of the relationship.
Systematically reviews customer profiles and notifies relevant parties if there are any changes.

Extracts accurate insights from big data in shorter reporting windows.
Applies sophisticated analytic techniques to all relevant data – not just a sample.
Array processing enables monitoring multiple risks during a single pass of the data.

Takes an enterprise approach to data management and consolidation to ensure consistent, accurate, timely data.
Combines data integration, data quality and master data management in a unified environment.
Brings together cross-channel enterprise data – from all lines of business, organizational units and geographic regions – on a single platform.

Flexible interface offers configurable, secure access to multiple solutions – customer due diligence, currency transaction reporting, case management, AML solutions, etc.
Assembles alerts from multiple monitoring systems, associates them with common individuals or entities, and automatically prioritizes and routes suspicious cases.
Enables efficient review of work items sent electronically to the system prior to creating or linking incidents to a case.

Enables creation of multiple automated workflows for different types of cases – fraud, money laundering, etc.
Includes to-do lists and makes certain action items mandatory prior to routing the case to the next step in the workflow.
Enables attachment of comments or documentation relevant to a case.
Captures and tracks all information relevant to a case through a central audit service, which enables easy auditing of the investigation process.