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Configure subledger analysis

  • Updated

Subledger analysis libraries allow organizations to configure risk analysis workflows specifically for subledger data.

Library-level configuration determines how subledger data is segmented, scored, analyzed, and reviewed within MindBridge. These settings help standardize subledger analysis workflows across engagements.


Create a subledger analysis library

App Admins can create a new library using a subledger analysis template.

When creating the library, select the appropriate subledger template and include the required analysis types for the engagement workflow.


Configure library settings

Configure the required library-level settings used during subledger analysis.

This may include:

  • filters
  • populations
  • risk scores
  • risk ranges
  • control point settings

These settings determine how subledger data is grouped, scored, and analyzed throughout the workflow.


Configure populations

Populations allow users to segment subledger data into meaningful groups for analysis.

Organizations can configure populations based on:

  • account groupings
  • transaction types
  • business processes
  • user-defined attributes
  • other relevant subledger dimensions

Configured populations can then be reviewed independently throughout the analysis workflow.


Configure risk scores and ranges

Risk scores and risk ranges determine how transaction activity is evaluated and categorized within the analysis.

Administrators can configure:

  • enabled risk scores
  • scoring thresholds
  • low-, medium-, and high-risk ranges
  • applicable control points

These configurations help align subledger analysis with organizational audit methodologies and risk assessment workflows.


Use the configured library in an engagement

Once the library has been configured, users can create engagements and ingest subledger data using the configured analysis template.

After the analysis has been run, users can review results through:

  • Risk overview
  • Risk segmentation
  • Trends
  • Data table

Users can also:

  • investigate transaction-level activity
  • create annotations
  • export results
  • add entries to audit workflows and sampling procedures

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