Enable GL Outlier Detection

GL Outlier Detection is available for journals that are configured to use the approval process.

GL Outlier Detection is a machine learning (ML) service that creates an information model that’s trained specifically on your organization's data. The service then evaluates new journal entries to assess whether they exceed historical patterns. If they do, the entries are flagged as outliers.

Identifying unusual General Ledger journal entries helps you spot potential errors before the transactions are posted to the general ledger.

Approvers can use this information to determine whether the transaction will be approved, corrected, or declined.

Subscription

AI/Machine Learning

General Ledger

Regional availability

All regions

User type

Business user with admin privileges

Permissions

Administration

Application subscriptions: List, View, Subscribe, Configure

Prerequisites

To create your data model, Outlier Detection needs data that meets the following requirements:

  • At least 1 month of data that's less than 2 years old

  • At least 1,000 posted General Ledger journal entry lines

  1. Go to Company > Admin >Subscriptions.

  2. Select the toggle next to AI/Machine Learning to enable the subscription.

  3. Select Configure.

  4. In the AI Services section, select Enable data service.

    This allows Sage Intacct to index your company data. This is necessary for GL Outlier Detection to gather and index your historical data. GL Outlier Detection relies on this data to learn what's an outlier and what's been the norm for your company.

  5. In the Outlier Detection section, select Enable for General Ledger approval.

    It takes time for the data model to be created, from 24 to 48 hours, depending on how much data is evaluated.

  6. Select Save.

The status changes to Ready when your data model is completed. After the model is ready, you can customize your settings in Configure General Ledger.

Next step: Customize GL Outlier Detection