Last time, we spoke about a fraud detection technique known as Benford’s Law.  In summary, it can easily detect outliers in certain sets of data by looking at the first digit of a number.  Those outliers can then be examined to see if they are fraudulent.  For many financial transactions, approximately 30% of the numbers should start with “1” and approximately 5% should start with “9”.  In essence, Benford’s law compares what your data exhibits against what is expected.  For more details, read the link above.

For the following, I’ll show how to do the first digit test and then I’ll show how to do the first two digit test. The two digit test is useful to drill down on the data to show patterns that might not exist in the first digit test. For example, the two digit test is very effective at picking up multiples of ten (10, 20, 30, etc.).


  • Load data in ACL
  • Analyze Tab ⇒ Benfords
  • Select field to analyze
  • Select number of digits
  • Graph

The following contains real data that was used to help identify and prosecute fraudsters in Oregon.


Screenshot of step 2


Screenshot of steps 3 & 4


Screenshot of Step 5

Note the big difference between observed and expected values of the first digit “1”.


Conducting the first two digit test

After looking at the first digit, consider also looking at the first two digits, even if nothing showed up the first time. Just run Benford again and change to “2” leading digits.


Look at all those spikes in the data presented below at multiples of $10. In this instance, many of those were fraudulent.


And if you look further you find a very suspicious pattern of dozens of $100 transactions in the first 3 digit test.


Read more about the outcome of the fraud investigation here, and check back next month for more on the how to’s of data analysis in the world of auditing!