SAS® Intelligent Decisioning

SAS Intelligent Decisioning automates analytics-based decision making so organizations can function more efficiently while improving interactions with customers, suppliers, partners and employees. Likewise, organizations that are highly regulated − such as financial services, health care and insurance − can more easily achieve compliance as a result of documented, traceable decisions.

Enterprise data throughput

• Ability to deliver more than 5,000 real-time transactions per second:

• Ability to achieve response times of 10 milliseconds per transaction.

• Simple integration with a variety of third-party applications at the data level.

Decision flow builder

• A centralized, graphical drag-and-drop interface lets you assemble business rules, custom code and models into complete decision flows, minimizing the need to write deployment code that joins these pieces together.

• To define decisions, you can browse existing repositories of data, models and business rules and select from existing assets.

• Create custom code within a decision flow to integrate with business application REST APIs, databases, web service calls and open source Python.

• To control decision orchestration, add condition logic (i.e., IF-THEN-ELSE) and use outputs from any preceding rule or model.

• From a decision flow, you can easily navigate to the business rule editor to simplify editing and rule-logic updates using deep linking.

• Ability to drill through from decision flow to model repository simplifies model selection and model inspection.

• The enhanced rule list view provides compressed, easy-to-read rules for readily identifiable logic definitions.

• Version control for entire decision flow simplifies testing and validation.

• Reduce risk and improve outcomes by automating operational decisions.

• Capitalize on customer and operational needs – with the right action, at the right time, to the right channel.

• Streamline business rule management.

• Manage high-volume customer interactions and other enterprise decisions effectively and consistently.

• Standardize analytical model use and deployment in one governed environment.