Sage Intacct GL Outlier Assistant: finding exceptions to the rules in your financial data

Sage Intacct’s GL Outlier Assistant leverages AI and machine learning to proactively detect and flag anomalies in your general ledger, helping finance teams catch errors, reduce risk, and streamline the approval process for more accurate and efficient financial management.

Artificial intelligence has quickly become a game-changer across industries, including accounting and finance. One standout example is the GL Outlier Detection and Outlier Assistant feature in Sage Intacct, a tool designed to streamline processes and save valuable time for finance professionals. In this post, we’ll explore why outlier detection matters, how the GL Outlier Assistant works, and the benefits it brings to your organization.

Introduction to outlier detection

Outlier detection is the process of identifying unusual patterns or anomalies in data. In accounting, especially within the General Ledger (GL), detecting these anomalies is crucial for maintaining data accuracy and integrity. Pinpointing outliers helps organizations catch errors, inconsistencies, and even potential fraud before they escalate into bigger issues. This proactive approach not only protects your organization’s financial health but also builds trust with stakeholders and regulators.

Mistakes can be costly—very costly

The impact of accounting mistakes can be enormous. For example, Bank of America once overstated its working capital by $4 billion due to an accounting error. Citibank employees accidentally processed a $900 million interest payment instead of $8 million. Mistakes like these are rare, but routine accounting errors are common and can be costly in terms of staff time and risk exposure. Sage customer interviews reveal that 10–20% of journal entries may need adjustment after posting to the general ledger, demanding extra time and resources to correct and document. The Sage Intacct GL Outlier Assistant is designed to address exactly these challenges.

Watch on-demand webinar: Sage Intacct GL Outlier Assistant

The importance of GL outlier detection

GL outlier detection is vital for several reasons:

1. Error detection: It helps catch errors in journal entries that can lead to incorrect reporting and decision-making, ensuring your financial statements are reliable.
2. Risk management: By identifying anomalies, organizations can mitigate the risk of financial misstatements, fraud, and non-compliance—protecting both finances and reputation.
3. Compliance: Outlier detection supports accurate, regulation-compliant financial data, reducing the risk of penalties and fines.
4. Operational efficiency: Automating the detection process frees up staff to focus on higher-value activities, boosting overall productivity.

GL Outlier Assistant: How it finds the exceptions

Introduced in 2020 and enhanced in 2022, the GL Outlier Assistant in Sage Intacct uses AI and machine learning to review journal entries and flag anomalies before transactions move to approval. Instead of sending flagged transactions to an approver, the Outlier Assistant returns them to the submitter for review or correction, streamlining the approval process and reducing workload for approvers.

Visual icons quickly show why an entry was flagged—whether it’s a coding anomaly, an unusual amount, or multiple issues. Configuration settings let you customize thresholds for what gets flagged, helping focus attention only on the most relevant outliers.

How the GL Outlier Assistant works

The Outlier Assistant operates in three stages:

Define stage

The assistant selects and previews data for analysis, pulling from sources like the general ledger and journals. Users can configure criteria such as date ranges, account types, and transaction amounts to target the most relevant data.

Learn stage

Here, the assistant builds a machine learning model using historical data to identify patterns and anomalies. Users can refine the model for accuracy by selecting which fields to analyze.

Review and operationalize

The assistant reviews detected outliers and suggests corrections. Users can verify and correct these entries. Additionally, the process can be operationalized with alerts, regular review schedules, and integration with other financial systems, maximizing the integrity and accuracy of your data.

We don’t know what we don’t know

Even with a highly skilled finance team, minor errors can go undetected and accumulate into significant issues. The GL Outlier Assistant provides a safety net, catching what might otherwise be missed. For instance, in a recent Sage Intacct webinar, a CFO reported that the tool helped flag 12 anomalous entries in less than a month—proof that even the best teams benefit from automated outlier detection. The feature is available to all Sage Intacct customers and can be activated easily.

Next steps

If your organization is looking to enhance accuracy, reduce risk, and improve efficiency with smart automation, Rand Group is here to help. As experts in financial systems and automation, we guide you through selecting, implementing, and optimizing tools like Sage Intacct GL Outlier Assistant to suit your organization’s needs.

Contact Rand Group today to learn more about how you can leverage AI-driven outlier detection, or explore our insights to discover other ways we help organizations succeed through technology and best practices.