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watsonx.governance Model Risk Governance (MRG) workflows
Last updated: Dec 12, 2024
watsonx.governance Model Risk Governance (MRG) workflows
You can use watsonx.governance Model Risk Governance (MRG) workflows as delivered or modify them to meet your requirements. You can also use them as templates and learning tools for your own workflows.

Workflows for models

Model Lifecycle
This workflow takes an AI model from the completion of the candidate process through to approval for deployment. It includes multiple stages and sub-workflows that involve various stakeholders.
Model lifecycle workflow
Foundation Model Onboarding workflow
The Foundation Model Onboarding workflow takes a foundation model through an approval process. The approval process includes stages for legal approval, AI ethics approval, and finance approval.
Foundation model onboarding workflow
Model Candidate workflow
This workflow allows a user to add a Model object to the inventory as a candidate. The Model candidate is submitted for Approval as either a Model or a Non Model. The approver can override the candidate proposal. After a model candidate is confirmed as a Model, the Model Development and Documentation process can begin.
Model Validation workflow
This workflow runs during the Model Lifecycle workflow. The Review Planning team that is identified on a Preference object is responsible for completing this review. This workflow is also used for conducting reviews after the model is in production.
Model Deployment
The Model Deployment workflow is used to govern the process of model deployment when development is complete. If the model is being deployed in production, there is an additional step to make the model ready for production before deployment is complete.
Model Risk Assessment
This workflow performs a model risk assessment on the model, the results of which are used to assign a tier to the model. The Model Risk Scorecard calculation then uses the values in Preference records to compute risk scores and tier. At the end of the workflow, the scores and tier are copied to the parent Model.
Model Attestation workflow
This workflow is typically started by an MRG administrator and records a model owner's response to a request for attestation.
Model Decommission workflow
This workflow is used to remove a Model from production and retire it.
Model Change Request workflow
This workflow provides governance for changes to Models. A workflow can be based on changes in the business or to the data and other inputs to a Model. Users can accept, approve, or reject the change and decide whether it is material or not.

Workflows for use cases

Use Case Request
The Use Case Request workflow takes a proposed use case through an approval process. All stakeholders reviews must be completed before the use case is approved.
Use Case Stakeholder Review
The Use Case Stakeholder Review workflow takes a use case through a series of reviews by stakeholders. Information about each review is captured in a Use Case Review object.
Use Case Development and Validation
The Use Case Development workflow takes a use case through a development and validation process. After the validation process is complete, the Use Case Deployment Approval workflow starts.
The Use Case Development workflow is shown in the Workflow Designer. The main workflow stages are: Under Development, Validation Assignment, and Validation.
Use Case Deployment Approval
The Use Case Deployment Approval workflow takes a use case through an approval process for deployment of the model.
The Use Case Deployment Approval workflow is shown in the Workflow Designer. The main stages are: AI Committee Approval and Model Deployment.
Model Use Case Request
This workflow is disabled by default. The Use Case Request workflow replaces it.

Workflows for metrics

Metric Value workflow
This workflow automates the Breach Status calculation and facilitates performance monitoring of deployed models. This process is critical to the ability to proactively decide to change the model or its usages or to remove a model from production.

Typically, metrics and their values are pulled in from watsonx.governance. But metrics can also be created and managed in Governance console. In this case, an MRG administrator creates Metric and Metric Value objects, a Metric Capturer provides the latest data for the metric, and the Metric Owner reviews and approves it. The workflow calculates breach status for the Metric and copies the most recent Metric Value information to the Metric.

Metric Value Creation workflow
When the next collection date comes due for an active metric, this workflow automatically creates a new metric value, and populates it with owner, capturer, and threshold information from the parent metric. The collector can then populate the metric value information and submit it for review.
Note: This workflow is not applicable to Governance console metrics.

Workflows for questionnaires

AI Assessment Workflow
This workflow is disabled by default. The Questionnaire Assessment workflow replaces it.
Questionnaire Assessment Workflow
The Questionnaire Assessment workflow moves a questionnaire assessment through the information gathering, review, and approval stages.

Other workflows

Challenges workflow
This workflow is started against a Model, one of its Model Deployments, or a Review. The result can be no action or changes to a Model or Model Deployment.
Model Risk Assessment Workflow
This workflow manages risk assessments for a use case by using the Risk object type.

The owner of the risk is asked to assess the use case, including the inherent risk, inherent likelihood of the risk, and the mitigation strategy. When the risk assessment is complete, the workflow sets the status of the risk to Approved.

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