Bureau Veritas Beneish M-Score Historical Data
The historical data trend for Bureau Veritas'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.
Bureau Veritas Beneish M-Score Chart
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Bureau Veritas Annual Data
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Trend |
Dec14 |
Dec15 |
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Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.79 |
-3.08 |
-2.56 |
-2.67 |
-2.64 |
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Bureau Veritas Semi-Annual Data
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Dec14 |
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Jun19 |
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Jun24 |
| Beneish M-Score |
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-2.67 |
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-2.64 |
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Competitive Comparison of Bureau Veritas's Beneish M-Score
For the Consulting Services subindustry, Bureau Veritas'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.
Bureau Veritas's Beneish M-Score Distribution in the Business Services Industry
For the Business Services industry and Industrials sector, Bureau Veritas's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Bureau Veritas's Beneish M-Score falls into.
Bureau Veritas 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 Bureau Veritas 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 * 0.9872 | + | 0.528 * 0.9904 | + | 0.404 * 1.0583 | + | 0.892 * 1.0384 | + | 0.115 * 1.0374 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1 | + | 4.679 * -0.047559 | - | 0.327 * 0.9558 |
| = | -2.64 |
* 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 €1,910 Mil.
Revenue was €5,868 Mil.
Gross Profit was €4,226 Mil.
Total Current Assets was €3,131 Mil.
Total Assets was €6,644 Mil.
Property, Plant and Equipment(Net PPE) was €781 Mil.
Depreciation, Depletion and Amortization(DDA) was €292 Mil.
Selling, General, & Admin. Expense(SGA) was €0 Mil.
Total Current Liabilities was €1,873 Mil.
Long-Term Debt & Capital Lease Obligation was €2,399 Mil.
Net Income was €504 Mil.
Gross Profit was €0 Mil.
Cash Flow from Operations was €820 Mil.
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Total Receivables was €1,864 Mil.
Revenue was €5,651 Mil.
Gross Profit was €4,030 Mil.
Total Current Assets was €3,596 Mil.
Total Assets was €7,119 Mil.
Property, Plant and Equipment(Net PPE) was €756 Mil.
Depreciation, Depletion and Amortization(DDA) was €297 Mil.
Selling, General, & Admin. Expense(SGA) was €0 Mil.
Total Current Liabilities was €2,379 Mil.
Long-Term Debt & Capital Lease Obligation was €2,410 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) |
| = | (1910.4 / 5867.8) | / | (1863.5 / 5650.6) |
| = | 0.325573 | / | 0.329788 |
| | = | 0.9872 |
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) |
| = | (4030.1 / 5650.6) | / | (4225.5 / 5867.8) |
| = | 0.713216 | / | 0.720117 |
| | = | 0.9904 |
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 - (3131 + 780.5) / 6644.4) | / | (1 - (3596.2 + 756.1) / 7119.2) |
| = | 0.411309 | / | 0.388653 |
| | = | 1.0583 |
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 |
| = | 5867.8 | / | 5650.6 |
| | = | 1.0384 |
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)) |
| = | (297.1 / (297.1 + 756.1)) | / | (291.5 / (291.5 + 780.5)) |
| = | 0.282093 | / | 0.271922 |
| | = | 1.0374 |
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) |
| = | (0 / 5867.8) | / | (0 / 5650.6) |
| = | 0 | / | 0 |
| | = | 1 |
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) |
| = | ((2399.4 + 1873.1) / 6644.4) | / | ((2410.4 + 2379) / 7119.2) |
| = | 0.643023 | / | 0.672744 |
| | = | 0.9558 |
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 |
| = | (503.7 - 0 | - | 819.7) | / | 6644.4 |
| | = | -0.047559 |
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.
Bureau Veritas has a M-score of -2.64 suggests that the company is unlikely to be a manipulator.
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