Cerner Beneish M-Score Historical Data
The historical data trend for Cerner'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.
Cerner Beneish M-Score Chart
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Cerner Annual Data
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Dec12 |
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Dec17 |
Dec18 |
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Dec21 |
| Beneish M-Score |
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-2.70 |
-2.75 |
-3.12 |
-2.90 |
-3.19 |
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Cerner Quarterly Data
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Jun17 |
Sep17 |
Dec17 |
Mar18 |
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Mar19 |
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Mar21 |
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Mar22 |
| Beneish M-Score |
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-3.03 |
-3.34 |
-3.31 |
-3.19 |
-3.29 |
Competitive Comparison of Cerner's Beneish M-Score
For the Health Information Services subindustry, Cerner'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.
Cerner's Beneish M-Score Distribution in the Healthcare Providers & Services Industry
For the Healthcare Providers & Services industry and Healthcare sector, Cerner's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Cerner's Beneish M-Score falls into.
Cerner 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 Cerner 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 * 0.9464 | + | 0.528 * 1.0107 | + | 0.404 * 1.1714 | + | 0.892 * 1.0593 | + | 0.115 * 0.8992 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.979 | + | 4.679 * -0.151113 | - | 0.327 * 1.0431 |
| = | -3.13 |
* 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 (Mar22) TTM: | Last Year (Mar21) TTM: |
Total Receivables was $1,178 Mil.
Revenue was 1429.801 + 1452.315 + 1467.976 + 1456.755 = $5,807 Mil.
Gross Profit was 1185.953 + 1194.39 + 1216.865 + 1195.43 = $4,793 Mil.
Total Current Assets was $2,468 Mil.
Total Assets was $7,374 Mil.
Property, Plant and Equipment(Net PPE) was $1,687 Mil.
Depreciation, Depletion and Amortization(DDA) was $719 Mil.
Selling, General, & Admin. Expense(SGA) was $3,145 Mil.
Total Current Liabilities was $1,379 Mil.
Long-Term Debt & Capital Lease Obligation was $1,611 Mil.
Net Income was 206.129 + 174.842 + 175.795 + 32.707 = $589 Mil.
Non Operating Income was 0.026 + 14.225 + -5.07 + -1.678 = $8 Mil.
Cash Flow from Operations was 375.063 + 517.294 + 434.821 + 369.135 = $1,696 Mil.
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Total Receivables was $1,175 Mil.
Revenue was 1387.778 + 1395.025 + 1368.673 + 1330.349 = $5,482 Mil.
Gross Profit was 1157.122 + 1160.352 + 1136.784 + 1118.386 = $4,573 Mil.
Total Current Assets was $3,055 Mil.
Total Assets was $7,908 Mil.
Property, Plant and Equipment(Net PPE) was $1,906 Mil.
Depreciation, Depletion and Amortization(DDA) was $700 Mil.
Selling, General, & Admin. Expense(SGA) was $3,032 Mil.
Total Current Liabilities was $1,463 Mil.
Long-Term Debt & Capital Lease Obligation was $1,611 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) |
| = | (1178.037 / 5806.847) | / | (1175.139 / 5481.825) |
| = | 0.20287 | / | 0.21437 |
| | = | 0.9464 |
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) |
| = | (4572.644 / 5481.825) | / | (4792.638 / 5806.847) |
| = | 0.834146 | / | 0.825343 |
| | = | 1.0107 |
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 - (2467.857 + 1686.97) / 7374.231) | / | (1 - (3055.18 + 1905.898) / 7908.41) |
| = | 0.436575 | / | 0.372683 |
| | = | 1.1714 |
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 |
| = | 5806.847 | / | 5481.825 |
| | = | 1.0593 |
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)) |
| = | (700.09 / (700.09 + 1905.898)) | / | (718.764 / (718.764 + 1686.97)) |
| = | 0.268647 | / | 0.298771 |
| | = | 0.8992 |
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) |
| = | (3144.607 / 5806.847) | / | (3032.241 / 5481.825) |
| = | 0.541534 | / | 0.553144 |
| | = | 0.979 |
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) |
| = | ((1611.303 + 1378.872) / 7374.231) | / | ((1611.102 + 1463.14) / 7908.41) |
| = | 0.40549 | / | 0.388731 |
| | = | 1.0431 |
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 |
| = | (589.473 - 7.503 | - | 1696.313) | / | 7374.231 |
| | = | -0.151113 |
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.
Cerner has a M-score of -3.13 suggests that the company is unlikely to be a manipulator.
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