Benford’s Law in Accounting: An Anomaly Metric in the Roghnu Data Portal

When it comes to financial data, small irregularities can sometimes signal big problems. That’s why Roghnu’s new Data Portal Health / Data Anomaly Metrics service includes Benford’s Law,  a proven statistical tool, to help organizations proactively identify unusual patterns in their accounting data.

Unlike traditional anomaly detection that relies on third-party AI services, all analysis happens securely within the Roghnu Data Portal, keeping sensitive financial information protected while delivering deeper insights into data integrity and compliance.

Sage Intacct Data and Benford’s Law in Accounting

Roghnu has developed an automated process that applies Benford’s Law analysis to Sage Intacct and other data sets, delivering a powerful new anomaly detection feature in the Data Portal.

This analysis helps identify irregularities or unusual patterns in transaction data, such as potential errors, fraud, or reporting issues. By comparing actual digit frequency distributions to expected norms, Roghnu gives organizations a proactive tool for financial data integrity and compliance monitoring.

More About Benford’s Law

Benford’s Law is a statistical principle that predicts the frequency distribution of the first digits in naturally occurring numerical datasets. According to the law, lower digits (like 1 or 2) occur as the leading digit more frequently than higher digits (like 8 or 9).

For example, the number 1 appears as the first digit about 30% of the time, while 9 appears less than 5% of the time.

In accounting and forensic auditing, Benford’s Law is widely used as a tool for detecting anomalies, irregularities, or potential fraud. By comparing the expected distribution of first digits with the actual distribution in datasets such as expense reports, sales transactions, or ledger entries, auditors can identify unusual patterns that may warrant further investigation.

Value & Benefits of Benford’s Law

• Fraud Detection: Highlights transactions that may have been fabricated or manipulated, as artificially created numbers often deviate from Benford’s expected pattern.

• Efficiency: Narrows the scope of detailed audits by flagging only suspicious subsets of data.

• Broad Application: Works on many types of datasets, especially large, diverse, naturally generated numbers, making it useful across multiple industries.

• Proactive Risk Management: Helps organizations detect potential issues before they escalate into major problems.

Limitations of Benford’s Law

Benford’s Law is not definitive proof of fraud. It is an analytical red flag that signals where deeper investigation may be needed. It works best on large datasets that span multiple orders of magnitude and are not artificially constrained (for example, prices fixed at $9.99 will not follow Benford’s distribution).

Benford’s Law in the Roghnu Data Portal

By embedding Benford’s Law analysis directly into the Roghnu Data Portal, organizations can continuously monitor financial data for red flags without extra tools, exports, or external risk exposure. It’s one of several anomaly metrics available now, alongside others such as Prior Period GL Journal Entry by User.

This is just the beginning. Roghnu’s Data Portal Health & Data Anomaly Metrics will continue to expand, giving finance and compliance teams a growing set of tools to proactively strengthen data integrity.

Learn more about the full service in our recent blog: Roghnu Data Portal Health & Data Anomaly Metrics – or schedule a demo today to see if the Roghnu Data Portal could be the right fit for you.