Multiply your model validation workforce by 30% or more with automation
How can you shorten the time for model validation?
What were the results of the validated models? Are models performing within risk controls?
With ModelOp, you always know.
Automate, enforce and audit model risk management processes and reporting
Regulations like the recently updated SR 11-7 and the newly proposed EU AI Act provide new regulatory guidance designed to standardize practices and processes that lead to responsible AI.
How we do it:
A centralized evergreen repository that ensures all required validation, approvals, and rules are adhered to minimize model risk.
Traceability, including version controls of models and related artifacts, ensure auditability at any time.
Regardless of type of model (including 3rd party vendor models), or where they are run (edge, cloud, on premises), the evergreen model inventory is the persistent system of record for every model in production.
Go faster and scale – automate model validation
Performing model validation manually is no longer an option unless you are willing to delay AI projects. Maintaining a staff of model validators to grow with your business is a huge challenge today. The right answer is to automate.
How we do it:
Enterprise-scale process automation that standardize model validation and other model risk management processes across all teams and model types.
Automated documentation services ensure design documentation, breach notifications and other standard reports are automatically generated using standardized templates and system-collected model data and metadata.
Automated testing and packaging of models using out-of-the box and custom tests expedites and standardizes the process for model validation and analysis.
Monitor, analyze and enhance your model risk management processes with new insights
Model testing and validation needs to evolve and provide insights for performance and diagnostic testing as your AI and model use changes and grows.
How we do it:
Out of the box and custom model monitors for pre-production testing and post-production operations allow you to quickly accelerate and improve model risk processes.
System collected data and metadata allow you to gain insights on model performance and operations and discover areas for improvement.
Native integrations with IT systems, Risk systems, and business applications accelerate time to validation and integrity in data across systems.
