Beneish M Score

This is a posting on evaluating financial statements. Beneish M Score is a calculation to determine how likely it is that a statement is fraudulent. Generally the score is negative. As long as its is less than –1.78, the probability of fraud is low.

The score was developed by Messod Daniel Beneish, professor of accounting at the Kelley School of Busines at Indiana University.

The calculation for 3M for the year ended February 8, 2023, is


0.92 × day’s sales in rec. index 1.00 0.92
0.528 × Gross margin index 1.07 0.56
0.404 × Asset quality index 0.94 0.38
0.892 × Sales index 0.97 0.86
0.115 × Depreciation index 1.23 0.14
-0.172 × S, G and A expense index 1.30 -0.22
–0.327 × Leverage index 0.95 –0.31
4.679 × Total accruals to assets index 0.02 0.10
Intercept –4.84

My conclusion, based on the score of –2.40, is that these statements are unlikely to contain fraud.

The score is the weighted total of eight indices.

The first index is day’s sales in receivables, a ratio of accounts receivable to sales divided by 365; it is a usual financial statement ratio. It shows on average how long it takes the company to collect its revenues. The index is the ratio of the current year to the prior one. If the company is recording sales that don’t exist, this should be greater than one.

The second index is gross margin index, that is, sales less cost of sales. Many financial statements show this as a subtotal on the income statement. The index is this year’s gross margin as a percent of sales to last year’s. Beneish believes that a declining margin is motivation for creative accounting.

The third is asset quality index. In some sense every asset is held to produce income. Each asset but cash and receivables has a life and should get written off over that life. Beneish identifies assets whose life and contribution to operations is clear. Those are current assets; plant, property, and equipment (PP&E); and securities, or quality assets. The asset quality ratio is (total_assets – quality_assets) ÷ total_assets.

Fourth is the sales growth index. That is this year’s sales to last year’s. Beneish believes that increasing sales may motivate management to overstate income in years when income does not meet expectations.

Fifth is depreciation index, the ratio of the percentage of PP&E written off this year to last. Overstating the value of PP&E and understating the depreciation charge are both techniques of managing income that are not generally accepted.

Selling, general, and administrative costs (SG&A) are the source of the next index. This year’s SG&A as a percent of sales is divided by last year’s. Subtract this index.

The leverage index, item 7, is the ratio of current liabilities plus long-term debt to total assets. It is a current-year statistic only. Beneish believes that highly leveraged firms are particularly likely to overstate income. Subtract this index from the score.

The last index is accruals to assets. That is (Cash provided by operations – Operating income)/Total Assets. Beneish’s observation is that misstatements rarely affect cash and therefore contribute to the difference between income and cash flow.

I wrote a workspace to perform this calculation. You can find it here. Fill in the array Beneish input. The function bi_Beneish_M will return the score and bi_Beneish_M_report will show the calculation of the score.

I found many websites explaining the Beneish M score and how to calculate it. Many noted that Enron scored in the fraud likely range but no one paid attention. Few websites actually offered a set of financial statements and calculated the M score.

One website that did calculate the M score got it wrong. The assets quality index (which measures the assets without quality [unquality being not a word.—KD]) was calculated with the quality assets as the numerator of the ratio. Their data was also flawed, as quality assets were greater than total assets.

~This all leads to my tentative conclusion: the Beneish M score, while it has demonstrated the ability to predict fraud, is too complicated. Beneish himself acknowledged that his eponymous score has too many false positives that require a great deal of digging to resolve.

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