Easily register, modify, track, score, publish and report on your analytical models using a visual, web-based interface. Store models within folders or projects. Develop and validate candidate models. Assess candidate models for champion model selection. Then publish and monitor champion models to ensure optimal model performance.
Streamline your analytical modeling processes.
SAS Model Manager simplifies the creation and management of model collections. The web-based interface makes it easy to automate the model management process, and enables more effective collaboration by letting users track progress through each step of the modeling process. A repeatable framework makes it easy to register, validate, track, monitor and retrain analytical models to ensure they’re performing well. You can define customized workflows for different model types, and everyone involved in interacting with or interpreting models gets a unified view of each model’s currency, definition and function.
Keep your models performing at their highest levels.
Easily test and compare analytical models with a web-based interface that ensures more efficient model processing and governance. Performance benchmarking reports and alerts can be generated for easy tracking to indicate model decay. Extensive tracking, validation and auditing reports are produced as analytical models are used across different departments and marked as champions for use in other applications. Ongoing monitoring identifies when it’s necessary to refine or retire a model. And model retraining integrates with the model pipeline processing environment for increased efficiency.
Ensure auditability and regulatory compliance.
The centralized model repository, lifecycle templates and version control capabilities provide visibility into your analytical processes, ensuring complete traceability and auditability for compliance with internal governance and external regulations. Basel II risk model validation reports provide transparency by assessing the soundness of internal credit risk measurement systems, tracking down anomalies and answering regulator inquiries on demand.
Gain complete knowledge of your model collections.
Track models from creation, through usage, to retirement with a centralized, efficient, repeatable process for registering, validating, monitoring and retraining models. Whenever a version is created, a snapshot of model properties and files is captured, ensuring comprehensive version control. Models are secured, and model version history is locked down and retained.
- Centralized model repository. Easily manage analytical models via a centralized, secure web-based repository.
- Analytical workflow management. Define and track custom workflows for model lifecycle management, including all phases – from problem-statement creation to model development and utilization.
- Model validation. Validate model scoring logic before models are pushed into production using a precise methodology and a system that automatically records each test the scoring engine performs.
- Performance monitoring and reporting. Automatically monitor and report on model performance during test and production cycles. Procedural templates document the validation performance and sign-off process, and an audit trail is created when the champion model is marked for production and the predecessor is retired.
- Overall model lifecycle management. Manage projects collaboratively using prebuilt model lifecycle templates.
This solution runs on SAS® Viya®, which has the breadth and depth to conquer any analytics challenge, from experimental to mission critical. SAS Viya extends the SAS Platform to enable everyone – data scientists, business analysts, developers and executives alike – to collaborate and realize innovative results faster.