Do this One Thing before you Submit your Business Tax Returns — and every quarter thereafter
Benford’s Law, which is different from the 80/20 rule (or the Pareto Principle), is a lesser-known method in the non-financial business community. It is a practical rule that can be used and sometimes adopted by forensic accountants and auditors to detect fraud in organizations finances. What is nice about it is that it’s a bais rule that can be implemented by anyone with a simple Excel sheet and could be useful in preventing and detecting internal fraudulent activities or tax audits.
If you include this tool in your business arsenal, you can benefit by having a cheap method to trigger suspicious activities, fraud alerts and possible tax audits.
What is Benford’s Law?
Named after physicist Frank Benford in 1938 after its use in a paper titled “The Law of Anomalous Numbers,” this principle has been around since 1881 and American astronomer Simon Newcomb. It goes by several other names, including the Newcomb-Benford Law, the law of anomalous numbers, and the first digit law. Benford’s law is explained from the first principles; the most prevalent is the universality of mathematics. It applies to data sets that are not dimensionless, meaning the numerical values depend on the unit.
It is observed that in real-life sets of numerical data, the leading digit is likely to be small, and dependent on the digit is likely to be a genuine data set. Simply put, the lower the numeral, the more likely its accuracy. Below are the percentages of numerals in genuine data sets:
- Numeral 1–30.1%
- Numeral 2–17.6%
- Numerals 3 through 9 will be the leading digits with decreasing frequency.
When Benford tested this in 1938, he used data that spanned 20 domains and 20,229 unique observations. These data sets were diverse, including the surface areas of 335 rivers, 1,800 molecular weights, and the sizes of 3,259 U.S. populations.
An important note is that, although this can be used to detect fraud, it is not proof that fraud occurred. So it is a tool that should be used with discernment and not as absolute truth.
What Kinds of Data Can It Be Applied To?
Benford’s law is so popular because of its ability to be used with a wide variety of data and its ease of use without complicated software programming. A simple Excel spreadsheet could be all that is needed. This principle can be applied to data sets including but not limited to general ledgers, invoice listings, trial balance reports, income statements, balance sheets, inventory listings, depreciation schedules, investment statements, accounts payable and receivable reports, portfolios, and expense reports.
It is crucial in business because budget data gathered from the budget reports each year of thousands of corporations may look random at first. But, you have to consider that these budgets will all depend on specific parameters, including size, industry, and even the state of the market. That is why there are many functional dependencies on the application of the law.
Almost no significant group of data containing naturally occurring numbers cannot benefit from applying the law. Counting and charting a data set’s leading digits is the same for any size data set. Although, according to the Information Systems Audit and Control Association (ISACA), there are examples of data sets that are likely not suitable for Benford’s law. These can include:
- Telephone numbers
- Data that formulas have generated
- Airline passenger counts by plane
- Data sets that have 500 or fewer transactions
- Data that is restricted by a maximum or minimum number (i.e., hourly wage rates)
Although these are just a few examples, the law tends to be the most accurate whenever values are distributed amongst multiple orders of magnitude. This is especially true if the process of generating the numbers is described by a power law, which is very common in nature.
So How Exactly Does It Help Businesses Avoid Tax Audits?
This simple to — use principle can detect fraud by the IRS, CPAs, and auditors as a “red flag test” that triggers a fraud alert. The IRS has been using this law for decades to identify returns that may be fraudulent before turning them over to auditors to do digging to uncover hard evidence of fraudulent activity. This is an effective tool as it is said that offenders rarely consider Benford’s law when they are creating false transaction documents.
Benford’s law to spot the possible signs of accounting fraud was studied extensively for almost a century.
Many CPAs actively study and use Benford’s law in their practice as a safeguard and final check before submitting financial transactional documents on behalf of their clients. The application of it in Excel is relatively simple and can be done by almost everyone. In 2017, the Journal of Accountancy broke down a simple step-by-step process that you can follow.
A Real Example
If you still aren’t 100% sure how the law can be used as a red flag indicator for potential fraud, let’s try it with an example from The Software Engineering Institute at Carnegie Mellon University.
If an organization has its alert thresholds set at $500 and $1,000 and an employee writes bad checks for $499 and $999, they have been undetected because they are just under the alert thresholds. But if the organization performs an audit to compare the data from the books to the Benford’s Law curve, the employee will be caught.
This is because the digits 4 and 9 are occurring as the leading digits much more frequently than they would in a natural data set. The data does not conform to Benford’s law and will raise red flags to dig a bit deeper.
Even if mathematics is not your strong suit, you can now see that Benford’s law can be incredibly user-friendly and efficient in evaluating data sets for any potential fraud resulting in tax audits. If you are a business owner who wants to make sure that come tax time, you aren’t in danger of audits that can be time-consuming and frustrating. It is worthwhile to learn how to apply this principle yourself or ensure that the accountants you use for your business returns are well-versed in its use.
Cho, W., & Gaines, B. (n.d.). BREAKING THE (BENFORD) LAW STATISTICAL FRAUD DETECTION IN CAMPAIGN FINANCE. http://cho.pol.illinois.edu/wendy/papers/bentas.pdf
Collins, J. C. (2017, April 1). Using Excel and Benford’s Law to detect fraud. Journal of Accountancy. https://www.journalofaccountancy.com/issues/2017/apr/excel-and-benfords-law-to-detect-fraud.html
Kessel, E. (2020, December 17). Benford’s Law: Potential Applications for Insider Threat Detection. Software Engineering Institute Blog. https://insights.sei.cmu.edu/blog/benfords-law-potential-applications-insider-threat-detection/#:~:text=Benford
Singleton, T. W. (2011, May 1). Understanding and Applying Benfords Law. ISACA. https://www.isaca.org/resources/isaca-journal/past-issues/2011/understanding-and-applying-benfords-law
Weisstein, E. W. (n.d.). Benford’s Law. Mathworld.wolfram.com. https://mathworld.wolfram.com/BenfordsLaw.html