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Summary

Risk segmentation allows you to see various categories of data laid out in a structure that is meaningful to you.

When you create a segment, you have control over which data fields to include (i.e., mapped columns in the imported dataset) and how you want to view them.

Learn about risk segmentation and how it is performed in MindBridge below.

Note: Segments can be created in the library or created directly in the Risk segmentation dashboard for use in the analysis.

Understand custom risk segmentation

Each data field added to the structure adds a new filter, effectively reducing the scope of the dataset that will appear in the segment table.

The Risk score field must be selected to build a risk table. In the table, only the risk score and the data fields arranged below it will be scored for risk.

Scenario

In this scenario, we can see that the risk score is placed at the top of the data structure, allowing MindBridge to assign a risk score to the entire table.

• Risk score

  • Account hierarchy: Account code

    • Region
      • Department
        • User ID

This means that the segment table will be populated as follows:

• All entries with a risk score
  • All entries with a risk score AND a particular account code
    • All entries with a risk score AND a particular account code AND a particular region
      • All entries with a risk score AND a particular account code AND a particular region AND a particular department
        • All entries with a risk score AND a particular account code AND a particular region AND a particular department AND a particular user ID

Tip: To get a better idea of how segmentation works in action, drill-down on a given row and review the query structure in the filter builder on the Data table dashboard. You can also drill-down to see risk summary visualizations for a given segment.