SAS® Model Manager
What does SAS Model Manager do? SAS Model Manager, with its patented, secure model repository and rich metadata structure and project templates, streamlines the tedious and often error-prone steps of creating, managing and deploying analytical models.
Why is SAS Model Manager important? Because analytics play an increasingly important role in business processes, it is critical that organizations reduce the likelihood of erroneous model output or incorrect interpretation of model results. The robust tracking features and detailed systems of checks and balances continually verify the accuracy and usefulness of analytical models.
For whom is SAS Model Manager designed? It is designed for analysts struggling to create new models and provide better answers faster; IT professionals responsible for validating score code as it is deployed in operational environments; business process owners concerned with applying analytical insights to gain competitive advantage; and all stakeholders concerned with the performance of analytical models.
Key Benefits
- Reduces time to manage and deploy models into production. SAS Model Manager provides an easy-to-use graphical user interface that guides users through a repeatable process for registering, testing and validating models. Models can be monitored from their creation to deployment into real-time or batch scoring systems until they are retired.
- Provides an integrated environment for tracking and monitoring model performance. An iterative framework for organizing and tracking ensures analytical models are functionally performing as intended throughout the model life cycle. As models are tested and compared, performance benchmarking reports are generated. As they are deployed, performance metrics are pushed across reporting channels.
- Enables compliance with regulatory requirements such as Sarbanes-Oxley and Basel II. SAS Model Manager provides flexible and unique compliance and validation reporting. Best practices can be captured via the patented centralized data repository, lifecycle templates and metadata management system. Users are guided through the difficult steps of deploying analytics from creation into the production operational environment.
Key Features
- Central, secure repository for managing analytical models. The SAS Model Manager Repository stores extensive documentation about the model, scoring code and associated metadata by allowing collaborative sharing of models coupled with user group authentication, version control and audibility. A model management project collects all necessary information for model deployment and performance monitoring based on a time-phased model management lifecycle that defines the sequence of milestones and tasks required from initial model registration up to final model retirement.
- Validation of scoring logic. Scoring officers using SAS Model Manager have a template to follow and a system to record each test that the scoring engine goes through to ensure the logic embedded within the champion model is sound. A mapping that details each accuracy checkpoint along with the expected scoring results is captured, recorded and logged in the system. Champion models can be exported for on-demand and batch scoring only after they are completely validated.
- Monitoring and reporting on model performance during test and production cycles. As the champion model reaches test, stage and production lifecycle milestones, status and performance information is pushed to those who manage the test criteria being evaluated. An audit trail is created as the champion model is phased into production and the predecessor champion model is retired. Performance benchmarks are calculated to display the champion model's scoring performance as well as to document conformance to required reporting standards. Several canned reports are provided as well as the flexible user-designed reports that monitor production model performance on an ongoing basis.
For a complete list of key benefits and features, refer to the SAS® Model Manager fact sheet. 
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