Skip to main content


         This documentation site is for previous versions. Visit our new documentation site for current releases.      
 

This content has been archived and is no longer being updated.

Links may not function; however, this content may be relevant to outdated versions of the product.

Model transparency for predictive models

Updated on April 16, 2021

Transparent artificial intelligence is becoming an important requirement for many businesses. In risk management, decisions need to be explainable, and opaque predictive models are not allowed. In marketing, the policy for the transparency of models might be less strict and allow for the use of opaque models.

Each predictive model type that comes with Pega Platform™ is assigned a transparency score by default. For example, a decision tree has a high transparency score, whereas a neural network model has a low transparency score. By default, the transparency threshold is set to 1 and all model types are allowed in all business issues. Lead data scientists can modify transparency thresholds for different business issues. For example, they can increase the threshold for risk management to indicate that opaque models are non-compliant in that area.

Model Transparency Policy landing page

Model Transparency Policy landing page

Model transparency policy in Pega Platform helps you indicate compliant and non-compliant predictive models.

Compliant and non-compliant models

Compliant and non-compliant models

When you develop models in the Analytics Center portal, you can check the transparency policy on the portal at any time.

Transparency policy on the Analytics Center portal

Viewing a model transparency policy in the Analytics Center portal

For more information, see Configuring the model transparency policy for predictive models.

Have a question? Get answers now.

Visit the Support Center to ask questions, engage in discussions, share ideas, and help others.

Did you find this content helpful?

Want to help us improve this content?

We'd prefer it if you saw us at our best.

Pega.com is not optimized for Internet Explorer. For the optimal experience, please use:

Close Deprecation Notice
Contact us