BENEISH’S M-SCORE Beneish’s M-Score is a mathematical model that uses eight financial ratios weighted by coefficients to identify whether a company has manipulated its profits. It was created by Professor Messod Beneish who published a paper in June 1999 called The Detection of Earnings Manipulation. Beneish surmises that companies are incentivised 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. These eight ratios are explained in greater detail as follows:

• Days’ Sales in Receivables Index (DSRI): A large increase in receivable days might suggest accelerated revenue recognition to inflate profits.
• Gross Margin Index (GMI): A deteriorating gross margin sends a negative signal about a firm’s prospects and creates an incentive to inflate profits.
• Asset Quality Index (AQI): An increase in long term assets (for example, the capitalisation of costs), 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.
• Sales Growth Index (SGI): High sales growth does not imply manipulation but high growth companies are more likely to commit financial fraud because their financial position and capital needs put pressure on managers to achieve earnings targets. If growth firms face large stock prices losses at the first indication of a slowdown, they may have greater incentives to manipulate earnings.
• Depreciation (DEPI): A falling level of depreciation relative to net fixed assets raises the possibility that a firm has revised upwards the estimated useful life of assets, or adopted a new method that is income increasing.
• Sales, General and Administrative Expenses (SGAI): Analysts might interpret a disproportionate increase in SG&A relative to sales as a negative signal about a firm’s future prospects, thereby creating an inventive to inflate profits.
• Leverage Index (LVGI): Leverage is measured as total debt relative to total assets. An increase in leverage creates an incentive to manipulate profits in order to meet debt covenants.
• Total Accruals to Total Assets (TATA): 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. A higher level of accruals is, therefore, associated with a higher likelihood of profit manipulation.

The eight variables are then weighted together according to the following formula:

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

Beneish concluded that if a company scored greater than -2.22 (i.e. a less negative or positive number) there was a likely probability of profit manipulation. We have recreated the formula and attempted to calculate the results for 3,600 Asian companies with a market capitalisation exceeding US$1bn. Unfortunately, Beneish designed his formula with US disclosure in mind and many Asian companies do not distinguish between COGS and SG&A. As such, we can’t calculate the formula for 19% of our sample, including the majority of those in Australiana and India. That’s a shame because the latter market would have been particularly interesting. Our calculations suggest that 96% of all companies score within a range of +/-5.

The M-score is the score indicating the probability of earnings manipulation. (Refer to the previous section for analysis of the model variables.) The M-score is a normally distributed random variable with a mean of 0 and a standard deviation of 1. Therefore, the probability of earnings manipulation can be calculated using the cumulative probabilities for a standard normal distribution or the NORMSDIST function in Excel. For example, M-scores of –1.49 and –1.78 indicate that the probability of earnings manipulation is 6.8% and 3.8%, respectively. Higher M-scores, i.e., less negative numbers, indicate an increased probability of earnings manipulation.

Additionally, the use of the M-score for classifying companies as potential manipulators depend on the relative cost of Type I errors and Type II errors. Type I errors occur due to incorrectly classifying a manipulator company as a non-manipulator. On the other hand, Type II errors are as a result of incorrectly classifying a non-manipulator as a manipulator. Beneish assessed that the likely relevant cutoff for investors is a probability of earnings manipulation of 3.8% (an M-score exceeding –1.78).