Detecting Financial Statement Fraud Schemes for the Amateur

The Association of Certified Fraud Examiners (ACFE) has published its Report to the Nations¹ (“Report”) for many years. In compiling the 2020 Report the organization studied 2,504 cases of occupational fraud and abuse from 125 countries.

This article will focus on financial statement fraud schemes because they are the least common but most costly type of fraud. According to the 2020 Report, while these schemes only accounted for 10% of the cases studied, they resulted in an average loss of $954,000. Other sources, including the Journal of Strategic Finance,² suggest a much higher incidence of financial statement fraud — in the range of 20-30% for publicly traded companies (particularly in what is referred to as “earnings management”).

Earnings management refers to a range of behaviors, including the manipulation of earnings through the financial statements by manipulating U.S. Generally Accepted Accounting Principles, to out-and-out false financial reporting, or something in between. That said, it is necessary to understand why such behavior occurs and to develop a better sense of what you need to look for.

In 2015, Forbes³ reported that results there are four factors that give rise to earnings management. They include:

1. People’s bonuses and jobs depend on it. Because performance-based bonuses are the norm, a high percentage of executive compensation is tied to performance targets; and those in charge feel compelled to meet those targets. Failure to meet one’s annual targets is a primary cause of executive turnover.
2. The manipulator wants to “lower the bar.” The objective may be to reduce earnings to create an easy target the following year. They do this by increasing reserve accounts and reducing earnings in the current year and decreasing the reserve accounts and increasing earnings in the following year. This is referred to as income smoothing.
3. They think “everyone is doing it.” Executive compensation is often compared within peer groups, and the result is what Forbes describes as “a sort of arms race of financial manipulation.” Additionally, senior executives have a vested interest in increasing stock prices.
4. Executives face very little accountability. The 2002 Sarbanes-Oxley Act may have changed that somewhat in publicly traded companies, but the ACFE Report suggests there is a long way to go. A February 2021 article published by Investopedia⁴ makes clear there is an “ongoing problem in corporate America” related to earnings manipulation.

Executives at all levels should be aware of earnings manipulation in their own organizations, as should people who make direct investments in common stock. We all recall the havoc related to Enron and other public companies that engaged in dishonest reporting.

The question is, how can you detect these behaviors quickly if you don’t happen to be a forensic accountant? There is a way to create a short and straightforward dashboard that detects anomalies in approximately 76% of cases.

The technique we describe below is based on a scholarly article entitled “The Detection of Earnings Manipulation” by M. Daniel Beneish, PhD in the Sept. /Oct. 1999 issue of the Financial Analysts Journal. Dr. Beneisch developed the factors (constants, in the language of mathematics) over several years of academic research. The model applies equally to both publicly traded and privately owned companies. The factors used in the formula are as follows, where, Y1 = Current Year and Y0 = Prior Year:

1. Days’ Sales in Receivables Index (DSRI) – (Receivables Y1/Sales Y1)/(Receivables Y0/Sales Y0)
2. Gross Margin Index (GMI) – ((Sales Y0 – Cost of Sales Y0)/Sales Y0)/((Sales Y1 – Cost of Sales Y1)/Sales Y1)
3. Asset Quality Index (AQI) – [1 – (Current Assets Y1 + PP&E Y1 + Securities Y1)/Total Assets Y1]/[1 – ((Current Assets Y0 + PP&E Y0 + Securities Y0)/Total Assets Y0)]
4. Sales Growth Index (SGI) – Sales Y1/Sales Y0
5. Depreciation Index (DEPI) – (Depreciation Y0/(PP&E Y0 + Depreciation Y0))/(Depreciation Y1/(PP&E Y1 + Depreciation Y1))
6. Selling General and Administrative Expenses Index (SGAI) – (SG&A Expense Y1/Sales Y1) / (SG&A Expense Y0/ Sales Y0)
7. Total Accruals to Total Assets (TATA) – (Income from Continuing Operations Y1 – Cash Flows from Operations Y1)/Total Assets Y1
8. Leverage Index (LVGI) – [(Current Liabilities Y1 + Total Long Term Debt Y1)/Total Assets Y1]/[(Current Liabilities Y0 + Total Long Term Debt Y0) / Total Assets Y0]

The Beneish M-Score formula is as follows:

M = -4.84 + 0.92*DSRI + 0.528*GMI + 0.404*AQI + 0.892*SGI + 0.115*DEPI – 0.172*SGAI + 4.679*TATA – 0.327*LVGI

In interpreting the overall M Score, the range of values from -2.22 to -1.78 suggests possible manipulation. Values less than -2.22 suggest there is likely no manipulation. Values greater than -1.78 suggest likely manipulation.

To provide a simple comparison between announced competitors, we applied the Beneish model to three publicly traded companies that are in the energy and resources industry: California Resources Corporation (NYSE:CRC), Calon Petroleum Company (NYSE:CPE) and PDC Energy (NasdaqGS:PDCE). We find M Scores of -2.27, -2.95 and -3.29, respectively, as of the latest financial reporting date. While we see no true evidence of manipulation, it’s worth noting that CRC comes very close to the line at -2.27. At a minimum, that score should pique the interest of a forensic accountant. A direct investor in energy might think Calon and PDC are more sound investments than CRC.

Again, the Beneisch M-Score allows the user to detect likely earnings manipulation and fraud in approximately 76% of cases. It can act as a simple tool to spot signs of earnings manipulation in a very short period of time. Whether you are actively managing a corporation or your own investments, this tool will serve you well. It can also be used as a stock-picking tool based on its ability to identify undervalued equity.

If you find issues in your own company using this relatively simple and straightforward model, ask Marcum.

Sources

1. 2020-Report-to-the-Nations.pdf (acfepublic.s3-us-west-2.amazonaws.com)
2. THE TROUBLE WITH EARNINGS MANAGEMENT – Strategic Finance (sfmagazine.com)
3. Four Reasons Executives Manipulate Earnings (forbes.com)
4. Financial Statement Manipulation an Ever-Present Problem for Investors (investopedia.com)