Analysis types available in MindBridge – MindBridge: English (US)

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Summary

MindBridge supports several analysis types, depending on your organization's needs and methodologies. Review the analytical capabilities of each analysis below, as well as the datasets required to access them.


Transaction Risk Analytics

MindBridges's Transaction Risk Analytics ("TRA") offer tailored configurations of machine learning algorithms that you can run against large, structured financial and operational datasets. These configurations help you uncover financial risk and operational inefficiency, deliver meaningful results for specific use cases, and can help drive outcomes in your organization.

TRA configuration files are created in collaboration with a MindBridge Customer Success Manager ("CSM"), and can be geared towards your organization’s unique needs and methodology.

During creation, a TRA analysis may be configured for any of the following time frames:

Reach out to your CSM or Account Manager today to see if TRA is right for your organization.


General ledger analysis

The General ledger ("GL") analysis uses various combinations of machine learning, statistical, and rule-based control points to find anomalies in financial data. It runs analytics on 100% of the transactions and entries, and is most effective when analyzing balanced transactions containing 2 or more line entries.

A GL analysis can be created in engagements that use any of the following MindBridge libraries (or, a custom library that uses one of the following as a base library):

During creation, a GL analysis may be configured for any of the following time frames:

Relevant files

*When you import a general ledger, chart of accounts, or account mapping file, MindBridge detects and maps accounts automatically, but you will need to verify your account mappings before running an analysis. Account mappings are shared between all general ledger analyses within an engagement.

Note: Review the import requirements for general ledger analyses below.

Analysis capabilities

Note: If enabled by your App Admin, you may also have access to the Risk monitoring dashboard, allowing you to compare summary analytics between two date ranges.


Accounts payable analysis

The AP analysis can analyze single-sided sub-ledgers to calculate detailed vendor balances and activity throughout a reporting period.

This analysis leverages machine learning, statistical, and rule-based control points, the following 5 of which are unique to this analysis:

Relevant files

Note: Review the Accounts payable data checklist to learn more about these datasets, including required files.

Analysis capabilities


Accounts receivable analysis

The AR analysis can analyze single-sided sub-ledgers to calculate customer balances and activity throughout a reporting period, including aging reports.

Relevant files

Note: Review the Accounts receivable data checklist to learn more about these datasets, including required files.

Analysis capabilities


Review engagement

The review engagement analysis can analyze transactions posted to a general ledger in order to help you develop an opinion related to reasonable assurance. MindBridge uses our suite of machine learning, statistical, and rule-based control points to provides streamlined and repeatable analytics to improve efficiency.

Visit Review engagements: Resource guide to learn about file import requirements.