Beneish M-Score

Complete Guide to the Beneish M-Score with Example Calculations Explained

What is the Beneish M-Score?

Definition: The Beneish M-Score is a mathematical model created at the end of the 20th Century by Professor Messod Beneish to identify if a company has manipulated its earnings. The model includes eight financial ratios constructed with data taken from the company’s financial statements and weighted by coefficients.

Investors and financial analysts who want to identify potential manipulations of financial results are the main users of the Beneish M-Score.

In short, it is used as a fraud detection technique. Since the financial results are the key input to decide whether or not to favor a potential investment, senior managers are strongly tempted to apply accounting policies as a way to artificially inflate short-term profits.

The result of the M-Score is a number that indicates the degree to which the earnings have been manipulated. According to Beneish, companies tend to manipulate profits if they have high sales growth, deteriorating gross margins, rising operating expenses, and rising leverage.

They are likely to manipulate profits by accelerating sales recognition, increasing cost deferrals, raising accruals, and reducing depreciation.

Key Takeaways

Earnings Manipulation Indicator: The Beneish M-Score is a sophisticated tool designed to identify the likelihood of a company manipulating its reported earnings, using a formula that analyzes various financial ratios and indicators.

Threshold for Concern: A score higher than -2.22 typically indicates a higher probability of earnings manipulation, signaling investors and analysts to exercise caution and conduct further investigation into the company’s financial practices.

Sector Sensitivity: The effectiveness and interpretation of the Beneish M-Score can vary by industry, as different sectors may have inherent characteristics that influence the score, necessitating a nuanced approach to its application and analysis.

Beneish M-Score Formula

The M-Score is calculated through the following formula:

M-score = -4.840 + 0.920 * DSRI + 0.528 * GMI + 0.404 * AQ + 0.892 * SGI + 0.115 * DEPI – 0.172 * SGAI – 0.327 * LVGI + 4.697 * TATA

Where

Components of the Beneish M-Score Formula

DSRI = Day Sales Receivable Index. It measures the ratio of days’ sales in receivables versus prior year. When Days Receivable increase notably, it might indicate accelerated income recognition to inflate earnings.

GMI = Gross Margin Index. It is calculated as the ratio of gross margin versus prior year. When gross margin is decreasing the firm is incentivized to inflate profits as a way to avoid worrying signals to investors.

AQ = Asset Quality Index. This is estimated as the ratio of non-current assets to total assets, but excluding from non-current assets the business’ plants, properties and equipment. This ratio measures asset quality compared to the previous year. An increase in long term assets other than property plant and equipment, relative to total assets indicates that a firm has potentially increased its involvement in cost deferral to inflate profits.

SGI = Sales Growth Index. This calculates sales growth versus previous year figure. Although high sales growth is not and indication of manipulation itself, the model assumes that high growth companies are more probable to commit financial fraud. This happens because their capital needs put pressure on managers to achieve good financial results.

DEPI = Depreciation Index. This calculates the ratio of the rate of depreciation versus previous year. A falling level of depreciation relative to net fixed assets raises the possibility that a firm has increased the useful life of its assets above the recommended standard, or adopted a new method of estimating their depreciation estimations to increase profits.

SGAI = Selling, General and Administrative Expenses Index. This measures the ratio of SGA expenses compared to the previous year. When there is a large increase in SG&A relative to sales, companies have higher incentives to inflate profits as a way to avoid negative signals.

LVGI = Leverage Index. This calculates the ratio of total debt to total assets versus the previous year. Leverage is seen as total debt relative to total assets. When leverage is rising, managers have incentives to manipulate profits to maintain the image that the business is solvent.

TATA = Total Accruals to Total Assets. This metric assesses the extent to which managers make discretionary accounting choices to alter earnings. Total accruals are calculated as the change in working capital (other than cash) less depreciation relative to total assets. Accruals, or a portion thereof, reflect the extent to which managers make discretionary accounting choices to alter earnings.

Four of the elements measure earnings manipulation (DSR, AQI, DEPI and TATA) and the remaining four indicate a predisposition to engage in earnings manipulation (GMI, SGI, SGAI, LEVI).

The Beneish M-Score says that when a company obtains a score greater than -2.22, which means that it may be a less negative or a positive number, it is more likely that it may be manipulating its accounting to inflate earnings.

what-is-the-beneish-m-score

Beneish M-Score Example

Let’s analyze two hypothetical companies to apply the Beneish M-Score formula.

Company A has the following financial ratios.

DSRI = 1.6

GMI = 1.1

AQ = 0.99

SGI = 0.7

DEPI = 1.02

SGAI = 1.15

LVGI = 0.5

TATA = -1

M-score = -4.840 + 0.920 * 1.6 + 0.528 * 1.1 + 0.404 * 0.99 + 0.892 * 0.7 + 0.115 * 1.02 – 0.172 * 1.15 – 0.327 * 0.5 + 4.697 * -1 = -6.7

The result indicates that Company A has not manipulated its earnings, as the number is lower than -2.22

Company B has the following financial ratios.

DSRI = 2

GMI = 2.2

AQ = 0.98

SGI = 0.7

DEPI = 1.02

SGAI = 0.2

LVGI = 0.1

TATA = -0.1

M-score = -4.840 + 0.920 * 2 + 0.528 * 2.2 + 0.404 * 0.98 + 0.892 * 0.7 + 0.115 * 1.02 – 0.172 * 0.2 – 0.327 * 0.1 + 4.697 * -0.1 = -1.24

For Company B, the Beneish M-Score indicates that earnings have probably been manipulated, as the number is higher than -2.22

How to Interpret the Beneish M-Score Analysis

The Beneish M-Score states that a company with a result higher -2.22 is more likely to be engaged in the manipulation of its reported earnings. On the opposite side, a company with a result under -2.22 is more likely to be transparently reporting its results.

To test the model, Professor Beneish used all companies in the Compustat database between 1982 and 1992. After running the test, the results were good yet not perfect.

The model could rightly find 76% of the manipulators and wrongly identified 17.5% of non-manipulators. Students of Cornell University applied the model to Enron and correctly identified that corporation as a manipulator.

Cautions & Limitations

Due to the risk of being wrong, the Beneish M-Score should be used as a mere approximation to detect potential earnings manipulation. It is certainly useful but an investor should not make a final decision on an investment by only using this method.

More thorough analysis of the company’s books should serve as a complement to any definitive conclusion. In the example shown above, an analyst should look carefully at Company B to evaluate if the business is actually a good investment alternative, considering it may be engaged in this sort of manipulation.

Frequently Asked Questions

What is the Beneish M-Score and how is it used?

The Beneish M-Score is a mathematical model that uses eight financial ratios to identify the likelihood of a company manipulating its earnings. It serves as a tool for investors and analysts to assess the risk of earnings manipulation, with a score higher than -2.22 suggesting a high probability of manipulation.

Can the Beneish M-Score predict financial fraud in companies?

While the Beneish M-Score is designed to detect signs of earnings manipulation, it’s not foolproof in predicting financial fraud but significantly aids in raising red flags for further investigation, based on statistical analysis of accounting data.

How does the Beneish M-Score differ from traditional financial analysis?

The Beneish M-Score specifically targets the detection of earnings manipulation by examining changes in key financial ratios over time, unlike traditional financial analysis that might focus more broadly on evaluating financial health, performance, and future prospects of a company.

Is the Beneish M-Score applicable to all types of companies?

The Beneish M-Score is most effective with publicly traded companies due to the availability of detailed financial information required for its calculation; however, its applicability and accuracy can vary across different industries and sizes of companies, with some sectors potentially having naturally higher scores without engaging in manipulation.

error: Content is protected !!