--- sourceDocument: Yokohama Governance, Risk, and Compliance sourceDocumentLink: https://servicenow-prod.fluidtopics.net/r/yokohama/governance-risk-compliance Release : - yokohama ft:locale : - en-US ft:publication_title : - Yokohama 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: Yokohama * * Updated January 30, 2025 * * ![](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 helps organizations automatically predict and assign appropriate risk statements to orphan risks---risks that currently lack associated risk statements. This AI and machine learning-driven capability improves risk categorization by analyzing risk names and descriptions to suggest relevant risk statements, enabling more accurate aggregation and reporting of organizational risks. Show full answer Show less ## Key Features * **Risk Statement Prediction:** Uses similarity algorithms within the Predictive Intelligence engine to match risk records with relevant risk statements, reducing manual effort and time spent searching the risk library. * **Improved Accuracy:** Minimizes incorrect risk categorization caused by manual and often incomplete searches by risk champions, enhancing visibility into the organization's risk profile. * **Role-Based Visibility:** Risk users (with the snrisk.user role) see risk statement recommendations only when a risk record has no defined risk statement, allowing informed association decisions. * **Configurable Solution:** Risk administrators with the mladmin role can set up, train, review, and customize the similarity solution to fit organizational needs. ## Benefits for ServiceNow Customers * **Risk Owners:** Easily identify correct risk statements for orphan risks, grouping similar risks into manageable categories. * **Risk Managers:** Reduce the number of orphan risks, gaining clearer, aggregated visibility into the overall risk landscape and enabling better impact analysis of similar risks. * **Risk Administrators:** Gain control over the predictive solution setup and customization to align risk statement predictions with organizational priorities. ## Implementation Requirements * Installation and activation of the following are required before use: * Risk Management * Risk Workspace * Predictive Intelligence * Recommended Actions - Advanced * A risk administrator with the mladmin role must train a similarity solution using at least 1000 existing risk records to enable effective predictions. * The similarity solution can be reviewed and adapted by the risk administrator to meet the specific needs of the organization. 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=yokohama&pubname=yokohama-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.