--- sourceDocument: Brazil Governance, Risk, and Compliance sourceDocumentLink: https://www.servicenow.com/docs/r/governance-risk-compliance Release : - brazil ft:locale : - en-US ft:publication_title : - Brazil Governance, Risk, and Compliance ft:clusterId : - grc bundleId : - grc workflow : - Technology --- # Categorizing risks with the Governance, Risk, and Compliance: Predictive Intelligence plugin # Categorizing risks with the Governance, Risk, and Compliance: Predictive Intelligence plugin {#ariaid-title1} Release version: Brazil Updated September 10, 2026 ![](https://www.servicenow.com/docs/portal-asset/ico-clock) 2 minutes to read Summarize ![AI sparkle icon](https://servicenow.com/docs/portal-asset/ai-sparkle-icon) Summarized using AI This content was generated using new OpenAI-powered functionality. Results are provided on an as is basis and are not guaranteed to be accurate or complete. ## Summary of Categorizing risks with the Governance, Risk, and Compliance: Predictive Intelligence plugin The Governance, Risk, and Compliance: Predictive Intelligence plugin enhances risk management by automatically predicting and associating risk statements with orphan risks---risks that lack predefined risk statements---within your organization's risk records. This AI-powered feature streamlines the traditionally manual and time-consuming process of categorizing risks, improving accuracy and efficiency in risk aggregation and reporting. Show full answer Show less ## Key Features * **Automated Risk Statement Prediction:** Uses artificial intelligence and machine learning to analyze risk names and descriptions, comparing them to existing risk statements to recommend the best matches. * **Improved Risk Categorization:** Enables risk users to view recommended risk statements when none are assigned, facilitating correct association and categorization of risks. * **Configurable Solution:** Risk administrators with the `mladmin` role can set up and customize the similarity solution within the Risk Workspace application to align with organizational requirements. ## Benefits * **For Risk Owners:** Simplifies identifying appropriate risk statements, helping group orphan risks into manageable categories. * **For Risk Managers:** Reduces the number of orphan risks by improving initial categorization accuracy and provides better visibility into the organization's comprehensive risk profile for impact analysis. * **For Risk Administrators:** Offers the ability to configure and train machine learning models to optimize risk statement predictions based on organizational data. ## Setup Requirements To enable this feature, a risk administrator must have the `mladmin` role and perform the following: * Install and activate these applications/plugins: Risk Management, Risk Workspace, Predictive Intelligence, and Recommended Actions - Advanced. * Train a similarity machine-learning solution on at least 1,000 existing risk records to enable accurate prediction of risk statements. * Review and modify the default similarity solution to meet specific organizational needs. ## Practical Impact for ServiceNow Customers By leveraging this plugin, your organization can expect to save considerable time and effort in risk statement assignment, reduce errors in risk categorization, and gain enhanced insight into the overall risk landscape. This enables more effective risk aggregation, reporting, and decision-making across all levels of risk management. By using the Governance, Risk, and Compliance: Predictive Intelligence plugin, you can predict the risk statements for your orphan risks (the risks that don't have risk statements) on the risk records for your organization. You can then identify the correct risk statement for the risks and then aggregate them into manageable categories. Usually, the first line of employees or the risk champions within an organization identify the risks for the business. Note: A risk champion is an executive who is in charge of identifying and reporting risks within an organization.As the risk champions identify these risks, they manually associate the risks with the correct risk statement. The organization's senior management gets visibility into the organization's risk profile because these operational risks are aggregated into the enterprise risks. However, your risk champions must manually search the complete risk library to identify the correct risk statement for the identified risks. This activity is time-consuming and is an inefficient use of resources. When the risk champions search for risk statements manually, they tend to select whatever is the earliest match rather than search for the entire library, which results in the incorrect categorization of risks with risk statements. ## Predicting risk statements on risk records {#categorization-of-risks__section_z1d_dff_2wb} The Governance, Risk, and Compliance: Predictive Intelligence plugin uses artificial intelligence (AI) and machine learning (ML) to predict the related risk statements on the risk records. The Predictive Intelligence plugin uses the similarity capability in the Predictive Intelligence engine to compare the risk name and description with the risk statements. With this plugin, your organization can reduce the effort that is required to search and identify the risk statements to associate with the identified risks. Your organization also gets higher accuracy in risk aggregation and reporting and visibility into the organization's risk profile. The following example shows the recommended risk statements on the risk record. Note: A risk user (sn_risk.user) can only see the risk statement recommendations when the risk statement isn't defined on the risk record. Based on the recommendations, a risk user can associate the risk with a related risk statement. ## Benefits of risk categorization with risk statements {#categorization-of-risks__section_pnq_hff_2wb} By categorizing your organization's risks with the risk statement, the following benefits are provided to different users: * Risk owners: Identify the correct risk statement for the orphan risks to group risks into manageable categories. * Risk managers: Reduce the number of orphan risks that were created by the first line of employees or risk champions. The risk managers get visibility into the organization's risk profile and can analyze the impact due to the similar type of risks. * Risk administrator: Configure the solution definition to predict the risk statements that are based on the organizational needs. {#categorization-of-risks__ul_omp_1v5_1wb} ## Setting up the feature {#categorization-of-risks__section_hms_ymt_1wb} A risk administrator with the ml_admin role can set up the risk categorization in the Risk Workspace application. Before your organization can use this feature, the risk administrator must install and activate the following applications and plugins: * Risk Management * Risk Workspace * Predictive Intelligence * Recommended Actions - Advanced {#categorization-of-risks__ul_g51_mdv_1wb} A risk administrator can train a default similarity solution for the risks in your organization by using the Predictive Intelligence plugin. Note: A similarity solution is a machine-learning solution to collect and compare your existing records to new similar records. For more information, see [Create and train a similarity solution](https://www.servicenow.com/docs/access?context=create-similarity-solution&version=brazil&pubname=brazil-intelligent-experiences&ft:locale=en-US). Note: You must have at least 1000 risk records for the similarity algorithm to work. A risk administrator with the ml_admin role can review the default similarity solution definition for risk and modify it based on your organizational needs.