Fujitsu Beneish M-Score Historical Data
The historical data trend for Fujitsu'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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Fujitsu Annual Data
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Trend |
Mar14 |
Mar15 |
Mar16 |
Mar17 |
Mar18 |
Mar19 |
Mar20 |
Mar21 |
Mar22 |
Mar23 |
| Beneish M-Score |
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-2.49 |
-2.82 |
-2.56 |
-2.52 |
-2.41 |
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Fujitsu 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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-1.93 |
-2.41 |
-2.49 |
-2.54 |
-2.69 |
Competitive Comparison
For the Information Technology Services subindustry, Fujitsu'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.
Fujitsu Beneish M-Score Distribution
For the Software industry and Technology sector, Fujitsu's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Fujitsu's Beneish M-Score falls into.
Fujitsu 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 Fujitsu 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 * 1.0176 | + | 0.528 * 0.989 | + | 0.404 * 1.0184 | + | 0.892 * 0.9216 | + | 0.115 * 1.083 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0278 | + | 4.679 * -0.054578 | - | 0.327 * 0.9992 |
| = | -2.78 |
* 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 €6,188 Mil.
Revenue was 5928.307 + 5781.628 + 5221.262 + 7525.928 = €24,457 Mil.
Gross Profit was 1859.425 + 1728.492 + 1447.385 + 2558.537 = €7,594 Mil.
Total Current Assets was €11,687 Mil.
Total Assets was €20,572 Mil.
Property, Plant and Equipment(Net PPE) was €3,788 Mil.
Depreciation, Depletion and Amortization(DDA) was €1,153 Mil.
Selling, General, & Admin. Expense(SGA) was €5,819 Mil.
Total Current Liabilities was €7,689 Mil.
Long-Term Debt & Capital Lease Obligation was €672 Mil.
Net Income was -74.694 + 212.047 + 28.43 + 715.766 = €882 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = €0 Mil.
Cash Flow from Operations was 105.277 + -201.558 + 1098.683 + 1001.946 = €2,004 Mil.
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Total Receivables was €6,598 Mil.
Revenue was 6517.182 + 6248.511 + 5782.565 + 7989.028 = €26,537 Mil.
Gross Profit was 1949.863 + 1840.791 + 1681.499 + 2676.775 = €8,149 Mil.
Total Current Assets was €12,705 Mil.
Total Assets was €21,923 Mil.
Property, Plant and Equipment(Net PPE) was €3,884 Mil.
Depreciation, Depletion and Amortization(DDA) was €1,314 Mil.
Selling, General, & Admin. Expense(SGA) was €6,144 Mil.
Total Current Liabilities was €8,158 Mil.
Long-Term Debt & Capital Lease Obligation was €759 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) |
| = | (6187.794 / 24457.125) | / | (6597.85 / 26537.286) |
| = | 0.253006 | / | 0.248626 |
| | = | 1.0176 |
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) |
| = | (8148.928 / 26537.286) | / | (7593.839 / 24457.125) |
| = | 0.307075 | / | 0.310496 |
| | = | 0.989 |
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 - (11687.393 + 3787.607) / 20572.424) | / | (1 - (12704.748 + 3884.046) / 21922.621) |
| = | 0.247779 | / | 0.243302 |
| | = | 1.0184 |
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 |
| = | 24457.125 | / | 26537.286 |
| | = | 0.9216 |
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)) |
| = | (1314.194 / (1314.194 + 3884.046)) | / | (1153.469 / (1153.469 + 3787.607)) |
| = | 0.252815 | / | 0.233445 |
| | = | 1.083 |
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) |
| = | (5819.177 / 24457.125) | / | (6143.532 / 26537.286) |
| = | 0.237934 | / | 0.231506 |
| | = | 1.0278 |
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) |
| = | ((671.604 + 7689.008) / 20572.424) | / | ((758.952 + 8157.63) / 21922.621) |
| = | 0.406399 | / | 0.40673 |
| | = | 0.9992 |
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 |
| = | (881.549 - 0 | - | 2004.348) | / | 20572.424 |
| | = | -0.054578 |
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.
Fujitsu has a M-score of -2.78 suggests that the company is unlikely to be a manipulator.
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