Gartner Beneish M-Score Historical Data
The historical data trend for Gartner's Beneish M-Score can be seen below:
* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.
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Gartner Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.50 |
-2.95 |
-2.89 |
-2.59 |
-2.71 |
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Gartner Quarterly Data
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Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-2.59 |
-2.56 |
-2.62 |
-2.63 |
-2.71 |
Competitive Comparison
For the Information Technology Services subindustry, Gartner's Beneish M-Score, along with its competitors' market caps and Beneish M-Score data, can be viewed below:
* Competitive companies are chosen from companies within the same industry, with headquarter located in same country, with closest market capitalization; x-axis shows the market cap, and y-axis shows the term value; the bigger the dot, the larger the market cap. Note that "N/A" values will not show up in the chart.
Gartner Beneish M-Score Distribution
For the Software industry and Technology sector, Gartner's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Gartner's Beneish M-Score falls into.
Gartner Beneish M-Score Calculation
The M-score was created by Professor Messod Beneish. Instead of measuring the bankruptcy risk (Altman Z-Score) or business trend (Piotroski F-Score), M-score can be used to detect the risk of earnings manipulation. This is the original research paper on M-score.
The M-Score Variables:
The M-score of Gartner for today is based on a combination of the following eight different indices:
| M | = | -4.84 | + | 0.92 * DSRI | + | 0.528 * GMI | + | 0.404 * AQI | + | 0.892 * SGI | + | 0.115 * DEPI |
| = | -4.84 | + | 0.92 * 0.9535 | + | 0.528 * 1.019 | + | 0.404 * 0.9233 | + | 0.892 * 1.0787 | + | 0.115 * 0.9229 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0094 | + | 4.679 * -0.051503 | - | 0.327 * 0.9444 |
| = | -2.71 |
* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.
| This Year (Dec23) TTM: | Last Year (Dec22) TTM: |
Total Receivables was $1,601 Mil.
Revenue was 1586.118 + 1408.784 + 1503.185 + 1408.869 = $5,907 Mil.
Gross Profit was 1056.276 + 957.943 + 1015.767 + 973.73 = $4,004 Mil.
Total Current Assets was $3,428 Mil.
Total Assets was $7,836 Mil.
Property, Plant and Equipment(Net PPE) was $630 Mil.
Depreciation, Depletion and Amortization(DDA) was $191 Mil.
Selling, General, & Admin. Expense(SGA) was $2,702 Mil.
Total Current Liabilities was $3,778 Mil.
Long-Term Debt & Capital Lease Obligation was $2,962 Mil.
Net Income was 208.631 + 180.009 + 198.043 + 295.783 = $882 Mil.
Non Operating Income was -5.465 + -2.586 + -0.304 + 138.659 = $130 Mil.
Cash Flow from Operations was 224.33 + 330.946 + 435.782 + 164.679 = $1,156 Mil.
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Total Receivables was $1,557 Mil.
Revenue was 1504.717 + 1331.868 + 1376.521 + 1262.74 = $5,476 Mil.
Gross Profit was 1029.351 + 915.031 + 951.986 + 885.707 = $3,782 Mil.
Total Current Assets was $2,786 Mil.
Total Assets was $7,300 Mil.
Property, Plant and Equipment(Net PPE) was $701 Mil.
Depreciation, Depletion and Amortization(DDA) was $192 Mil.
Selling, General, & Admin. Expense(SGA) was $2,481 Mil.
Total Current Liabilities was $3,598 Mil.
Long-Term Debt & Capital Lease Obligation was $3,051 Mil.
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1. DSRI = Days Sales in Receivables Index
Measured as the ratio of Revenue in Total Receivables in year t to year t-1.
A large increase in DSR could be indicative of revenue inflation.
| DSRI | = | (Receivables_t / Revenue_t) | / | (Receivables_t-1 / Revenue_t-1) |
| = | (1601.228 / 5906.956) | / | (1556.786 / 5475.846) |
| = | 0.271075 | / | 0.284301 |
| | = | 0.9535 |
2. GMI = Gross Margin Index
Measured as the ratio of gross margin in year t-1 to gross margin in year t.
Gross margin has deteriorated when this index is above 1. A firm with poorer prospects is more likely to manipulate earnings.
| GMI | = | GrossMargin_t-1 | / | GrossMargin_t |
| = | (GrossProfit_t-1 / Revenue_t-1) | / | (GrossProfit_t / Revenue_t) |
| = | (3782.075 / 5475.846) | / | (4003.716 / 5906.956) |
| = | 0.690683 | / | 0.677797 |
| | = | 1.019 |
3. AQI = Asset Quality Index
AQI is the ratio of asset quality in year t to year t-1.
Asset quality is measured as the ratio of non-current assets other than Property, Plant and Equipment to Total Assets.
| AQI | = | (1 - (CurrentAssets_t + PPE_t) / TotalAssets_t) | / | (1 - (CurrentAssets_t-1 + PPE_t-1) / TotalAssets_t-1) |
| = | (1 - (3427.886 + 629.527) / 7835.919) | / | (1 - (2786.107 + 701.173) / 7299.736) |
| = | 0.482203 | / | 0.522273 |
| | = | 0.9233 |
4. SGI = Sales Growth Index
Ratio of Revenue in year t to sales in year t-1.
Sales growth is not itself a measure of manipulation. However, growth companies are likely to find themselves under pressure to manipulate in order to keep up appearances.
| SGI | = | Sales_t | / | Sales_t-1 |
| = | Revenue_t | / | Revenue_t-1 |
| = | 5906.956 | / | 5475.846 |
| | = | 1.0787 |
5. DEPI = Depreciation Index
Measured as the ratio of the rate of Depreciation, Depletion and Amortization in year t-1 to the corresponding rate in year t.
DEPI greater than 1 indicates that assets are being depreciated at a slower rate. This suggests that the firm might be revising useful asset life assumptions upwards, or adopting a new method that is income friendly.
| DEPI | = | (Depreciation_t-1 / (Depreciaton_t-1 + PPE_t-1)) | / | (Depreciation_t / (Depreciaton_t + PPE_t)) |
| = | (191.946 / (191.946 + 701.173)) | / | (191.103 / (191.103 + 629.527)) |
| = | 0.214916 | / | 0.232874 |
| | = | 0.9229 |
Note: If the Depreciation, Depletion and Amortization data is not available, we assume that the depreciation rate is constant and set the Depreciation Index to 1.
6. SGAI = Sales, General and Administrative expenses Index
The ratio of Selling, General, & Admin. Expense(SGA) to Sales in year t relative to year t-1.
SGA expenses index > 1 means that the company is becoming less efficient in generate sales.
| SGAI | = | (SGA_t / Sales_t) | / | (SGA_t-1 /Sales_t-1) |
| = | (2701.542 / 5906.956) | / | (2480.944 / 5475.846) |
| = | 0.457349 | / | 0.45307 |
| | = | 1.0094 |
7. LVGI = Leverage Index
The ratio of total debt to Total Assets in year t relative to yeat t-1.
An LVGI > 1 indicates an increase in leverage
| LVGI | = | ((LTD_t + CurrentLiabilities_t) / TotalAssets_t) | / | ((LTD_t-1 + CurrentLiabilities_t-1) / TotalAssets_t-1) |
| = | ((2962.102 + 3777.719) / 7835.919) | / | ((3050.874 + 3597.6) / 7299.736) |
| = | 0.860119 | / | 0.910783 |
| | = | 0.9444 |
8. TATA = Total Accruals to Total Assets
Total accruals calculated as the change in working capital accounts other than cash less depreciation.
| TATA | = | (IncomefromContinuingOperations_t | - | CashFlowsfromOperations_t) | / | TotalAssets_t |
| = | (NetIncome_t - NonOperatingIncome_t | - | CashFlowsfromOperations_t) | / | TotalAssets_t |
| = | (882.466 - 130.304 | - | 1155.737) | / | 7835.919 |
| | = | -0.051503 |
An M-Score of equal or less than -1.78 suggests that the company is unlikely to be a manipulator. An M-Score of greater than -1.78 signals that the company is likely to be a manipulator.
Gartner has a M-score of -2.71 suggests that the company is unlikely to be a manipulator.
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