Think about the term “slippery slope” for a moment. What do you imagine when you read it? How about a water slide? An article in the Journal of Accountancy compared Bedford’s Law with a theme park water slide, an apt image, and one that’s easy to keep in mind. Keep the concept of a curve in mind when looking at your data and you’ll be able to detect nonprofit fraud more easily.
A Picture of Nonprofit Fraud
In 1938, Frank Benford discovered a naturally occurring numerical law that predicts the frequency of digits in any number set. According to Bedford’s Law, an authentic data set includes the following frequency of digits:
- the numeral 1 will be the leading digit in a genuine data set of numbers 30.1% of the time;
- the numeral 2 will be the leading digit 17.6% of the time;
- and each subsequent numeral, 3 through 9, will be the leading digit with decreasing frequency.
Using Excel data and some simple calculations, you can chart your nonprofit’s numbers on a Benford curve. If the numbers don’t resemble the curve, it’s time to investigate, as something may be amiss.
Using Benford’s Law in Nonprofit Accounting
Benford’s Law works best with large data sets, typically groups of numbers with more than 100 entries. Fewer numbers provide too small a data set to chart accurately. Some recommend 500 or more numbers for improved accuracy.
Other tips include:
- The numbers must have an equal chance of starting with 1 through 9. If the dataset limits the numbers, Benford’s Law won’t work. Thus, calculating the average height of the Rockettes, the Radio City Dance troupe, doesn’t work because all Rockettes must be between 5’ 6” and 5” 10 1/2” tall; all digits begin with 5, therefore the curve won’t work. Think about this if your products are all priced with the same starting digit. Entering them into the spreadsheet and generating a curve won’t work to detect fraud, i.e., if all conferences run by your nonprofit have a fee of $199 for example.
- Don’t use it as definitive proof of fraud. Benford’s curve cannot prove or disprove fraud. It’s like a clue that leads you to investigate more deeply into potential fraud. It’s not a good idea to use it to accuse someone of fraudulent activity. It can, however, point to a problem requiring further investigation or the addition of an outside consultant to your team.
To use Excel to plot a Benford Curve:
- Use the Column Chart, LEFT, and COUNTIF functions.
- Enter the data by name in column A, and numerically in subsequent columns.
- Use the LEFT function to extract the first digit of each number in a column.
- Copy and use the same formula to extract all the first digits.
- Use the =COUNTIF function to count the occurrence of the first digit from each number that you extracted in the step above.
- Copy the results to a new cell.
- Chart the results.
The previously linked Journal of Accountancy article provides an Excel spreadsheet already set up with relevant formulas that you can download.
By charting the numbers, you’ll either see the Benford curve or a random graph. Some graphs look like straight lines with slight bumps in the middle. This tends to indicate that the data was artificially produced, in which case, fraud may be occurring.
It also may not be an example of fraudulent activity. That’s why it’s important to perform additional checks and investigate potential fraud before making accusations. Sometimes, a bell curve is just a bell curve.
About Welter Consulting
Welter Consulting bridges people and technology together for effective solutions for nonprofit organizations. We offer software and services that can help you with your accounting needs. Please contact Welter Consulting at 206-605-3113 for more information.
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