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Model Governance

What Is Model Governance? The Simple Definition

A set of practices and procedures to guide how organizations use AI and machine learning models. A good model governance program should cover inventorying all models, understanding their risks, setting guidelines for model development and validation, keeping documentation, and more.

The Technical Definition

Model governance refers to the systematic management and oversight of machine learning and statistical models used in various business processes.

It involves creating and enforcing policies, procedures, and controls to ensure the quality, fairness, accuracy, and compliance of these models throughout their lifecycle, from development to deployment and ongoing monitoring.

Explain It Like I’m Five

Model governance is like taking care of and watching over the computers that help us make decisions. We make rules for them, check if they’re doing their jobs correctly, and make sure they don’t make mistakes.

Use It At The Water Cooler

How to use “model governance” in a sentence at work:

“Our company’s model governance framework ensures that the machine learning models we use in our financial predictions are accurate, reliable, and follow all the rules and regulations.”

Related Terms

Artificial Intelligence, Data Governance

Additional Resources

New York DFS AI Regulation, What Insurers Need To Know

New York DFS AI Regulation, What Insurers Need To Know

A must-read for insurance professionals. Instead of combing through pages and pages of legislation, this overview highlights everything you need to know. Understand fairness principles, and what is required for regulatory compliance for insurers licensed in New York. Stay informed about the best practices in AI governance to prevent discrimination and ensure transparency in insurance processes.

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