Streamline the tedious and often error-prone steps of creating, managing, validating, deploying, monitoring and operationalizing your analytic models. Quickly put your best models into production. And take action – fast – if model performance starts to degrade.
Accelerate model validation, management and deployment.
With an efficient, repeatable process for registering, validating, deploying, monitoring and retraining models, you can track models all the way from their creation, to their deployment into real-time or batch scoring systems, to their retirement. Accountability metrics and version control status reports record who changes what, when control is passed from one area to another, etc.
Provide models that are up-to-date and accurate.
An iterative framework ensures that analytical models are tested and compared, performance benchmarking reports are generated and – as models are deployed – performance metrics are pushed to established reporting channels. Modelers can easily collaborate and reuse models. And you can set automated alerts to detect when scoring results change over time, which indicates model decay.
Ensure auditability and compliance.
Compliance and model validation reporting capabilities are highly sought-after due to heightened regulatory requirements. A centralized model repository, lifecycle templates and version control provide visibility into analytical processes and ensure they can be audited to comply 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 regulatory inquiries on demand.
Streamline modeling processes.
With this fully web-based software, you can streamline the manual error-prone steps of creating, managing, deploying, monitoring and operationalizing analytical models. An automated and collaborative model management process lets you track each step of the modeling project and create customized workflows for different types of models. Different users touching or interpreting a model will get a unified view of its current stage with access to information that will help them take relevant actions.
- Centralized repository. Easily manage analytical models via a centralized, secure web-based repository.
- Analytical workflow management. Define and track custom workflows for model life-cycle management using a web-based interface.
- Model validation. Validate model scoring logic before models are exported to production.
- Performance monitoring and reporting. Monitor and report on model performance during test and production life cycles.
- Overall model lifecycle management. Manage projects collaboratively with prebuilt model lifecycle templates.