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.
Gartner Beneish M-Score Chart
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Gartner Annual Data
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Trend |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
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-2.95 |
-2.89 |
-2.59 |
-2.71 |
-2.74 |
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Gartner Quarterly Data
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Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
Dec24 |
Mar25 |
| Beneish M-Score |
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-2.70 |
-2.58 |
-2.74 |
-2.74 |
-2.89 |
Competitive Comparison of Gartner's Beneish M-Score
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's Beneish M-Score Distribution in the Software Industry
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 * 0.9059 | + | 0.528 * 0.999 | + | 0.404 * 0.9279 | + | 0.892 * 1.0599 | + | 0.115 * 0.8286 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0094 | + | 4.679 * -0.077013 | - | 0.327 * 0.9077 |
| = | -2.89 |
* 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 (Mar25) TTM: | Last Year (Mar24) TTM: |
Total Receivables was $1,504 Mil.
Revenue was 1534.13 + 1715.119 + 1484.306 + 1595.06 = $6,329 Mil.
Gross Profit was 1059.1 + 1140.194 + 1008.964 + 1081.746 = $4,290 Mil.
Total Current Assets was $4,132 Mil.
Total Assets was $8,480 Mil.
Property, Plant and Equipment(Net PPE) was $496 Mil.
Depreciation, Depletion and Amortization(DDA) was $204 Mil.
Selling, General, & Admin. Expense(SGA) was $2,925 Mil.
Total Current Liabilities was $3,792 Mil.
Long-Term Debt & Capital Lease Obligation was $2,785 Mil.
Net Income was 210.939 + 398.573 + 415.049 + 229.548 = $1,254 Mil.
Non Operating Income was 2.389 + -3.825 + 298.85 + 0.146 = $298 Mil.
Cash Flow from Operations was 313.512 + 335.355 + 590.767 + 369.964 = $1,610 Mil.
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Total Receivables was $1,566 Mil.
Revenue was 1472.926 + 1586.118 + 1408.784 + 1503.185 = $5,971 Mil.
Gross Profit was 1013.485 + 1056.276 + 957.943 + 1015.767 = $4,043 Mil.
Total Current Assets was $3,326 Mil.
Total Assets was $7,710 Mil.
Property, Plant and Equipment(Net PPE) was $609 Mil.
Depreciation, Depletion and Amortization(DDA) was $194 Mil.
Selling, General, & Admin. Expense(SGA) was $2,734 Mil.
Total Current Liabilities was $3,640 Mil.
Long-Term Debt & Capital Lease Obligation was $2,948 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) |
| = | (1503.582 / 6328.615) | / | (1565.96 / 5971.013) |
| = | 0.237585 | / | 0.26226 |
| | = | 0.9059 |
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) |
| = | (4043.471 / 5971.013) | / | (4290.004 / 6328.615) |
| = | 0.677183 | / | 0.677874 |
| | = | 0.999 |
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 - (4131.954 + 495.677) / 8479.761) | / | (1 - (3326.271 + 608.936) / 7709.81) |
| = | 0.454273 | / | 0.489584 |
| | = | 0.9279 |
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 |
| = | 6328.615 | / | 5971.013 |
| | = | 1.0599 |
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)) |
| = | (193.779 / (193.779 + 608.936)) | / | (203.768 / (203.768 + 495.677)) |
| = | 0.241404 | / | 0.291328 |
| | = | 0.8286 |
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) |
| = | (2925.289 / 6328.615) | / | (2734.285 / 5971.013) |
| = | 0.462232 | / | 0.457926 |
| | = | 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) |
| = | ((2785.498 + 3791.695) / 8479.761) | / | ((2948.059 + 3640.29) / 7709.81) |
| = | 0.775634 | / | 0.854541 |
| | = | 0.9077 |
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 |
| = | (1254.109 - 297.56 | - | 1609.598) | / | 8479.761 |
| | = | -0.077013 |
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 -2.89 suggests that the company is unlikely to be a manipulator.
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