Centralized model repository
Easily manage analytical models via a centralized, secure web-based repository.
Store SAS and open source models within projects or as standalone models. Develop and validate candidate models. Assess and compare candidate models for champion model selection. Then publish and monitor champion and challenger models to ensure optimal model performance.
Analytical workflow management
Define and track custom workflows for model life cycle 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 life cycle management
Manage projects collaboratively using prebuilt model life cycle templates.
Easily register, modify, track, score, publish, govern and report on your analytical models using a visual, web-based interface.
Quickly operationalize your analytical models.
SAS Model Manager simplifies the creation and management of model collections. The web-based interface makes it easy to automate the model management process. It also facilitates more effective collaboration by letting users track progress through each step of the modeling process. Rapid, automated techniques let you operationalize models with just a few clicks, both in batch and in real time. A repeatable framework enables easy registration, validation, tracking, monitoring and retraining of 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, life cycle 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.
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.
Explore More on SAS® Model Manager & Beyond
Discover how the analytics life cycle takes you from raw data to predictive modeling to automated decisions.
WHITE PAPER
Learn how you can operationalize analytics to derive business value in this TDWI Best Practices Report.
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