Automatic Data Processing Beneish M-Score Historical Data
The historical data trend for Automatic Data Processing'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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Automatic Data Processing Annual Data
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Trend |
Jun14 |
Jun15 |
Jun16 |
Jun17 |
Jun18 |
Jun19 |
Jun20 |
Jun21 |
Jun22 |
Jun23 |
| Beneish M-Score |
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-2.34 |
-2.49 |
-2.52 |
-2.46 |
-2.48 |
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Automatic Data Processing 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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-2.35 |
-2.50 |
-2.48 |
-2.49 |
-2.48 |
Competitive Comparison
For the Staffing & Employment Services subindustry, Automatic Data Processing'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.
Automatic Data Processing Beneish M-Score Distribution
For the Business Services industry and Industrials sector, Automatic Data Processing's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Automatic Data Processing's Beneish M-Score falls into.
Automatic Data Processing 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 Automatic Data Processing 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 * 1.0061 | + | 0.528 * 0.9813 | + | 0.404 * 0.9843 | + | 0.892 * 1.0599 | + | 0.115 * 0.9597 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0299 | + | 4.679 * -0.007761 | - | 0.327 * 0.9785 |
| = | -2.48 |
* 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 $3,372 Mil.
Revenue was 4442.7 + 4310.7 + 4242.1 + 4678.4 = $17,674 Mil.
Gross Profit was 1881.1 + 1795.3 + 1756.8 + 2054.6 = $7,488 Mil.
Total Current Assets was $48,543 Mil.
Total Assets was $57,069 Mil.
Property, Plant and Equipment(Net PPE) was $1,043 Mil.
Depreciation, Depletion and Amortization(DDA) was $559 Mil.
Selling, General, & Admin. Expense(SGA) was $3,698 Mil.
Total Current Liabilities was $48,098 Mil.
Long-Term Debt & Capital Lease Obligation was $3,317 Mil.
Net Income was 878.4 + 859.4 + 776.7 + 1043.1 = $3,558 Mil.
Non Operating Income was 7.9 + 21.2 + 10.5 + 12.2 = $52 Mil.
Cash Flow from Operations was 1032.4 + 326.5 + 1185.7 + 1404.1 = $3,949 Mil.
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Total Receivables was $3,162 Mil.
Revenue was 4203.8 + 4074.6 + 4000.9 + 4395 = $16,674 Mil.
Gross Profit was 1753.1 + 1681 + 1615 + 1882.8 = $6,932 Mil.
Total Current Assets was $46,144 Mil.
Total Assets was $54,453 Mil.
Property, Plant and Equipment(Net PPE) was $1,055 Mil.
Depreciation, Depletion and Amortization(DDA) was $531 Mil.
Selling, General, & Admin. Expense(SGA) was $3,388 Mil.
Total Current Liabilities was $46,814 Mil.
Long-Term Debt & Capital Lease Obligation was $3,322 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) |
| = | (3372.4 / 17673.9) | / | (3162.3 / 16674.3) |
| = | 0.190812 | / | 0.189651 |
| | = | 1.0061 |
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) |
| = | (6931.9 / 16674.3) | / | (7487.8 / 17673.9) |
| = | 0.415724 | / | 0.423664 |
| | = | 0.9813 |
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 - (48543.4 + 1043) / 57069.4) | / | (1 - (46143.6 + 1055.4) / 54453) |
| = | 0.131121 | / | 0.133216 |
| | = | 0.9843 |
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 |
| = | 17673.9 | / | 16674.3 |
| | = | 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)) |
| = | (531.4 / (531.4 + 1055.4)) | / | (559 / (559 + 1043)) |
| = | 0.334888 | / | 0.348939 |
| | = | 0.9597 |
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) |
| = | (3698 / 17673.9) | / | (3387.7 / 16674.3) |
| = | 0.209235 | / | 0.203169 |
| | = | 1.0299 |
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) |
| = | ((3317 + 48097.7) / 57069.4) | / | ((3322.2 + 46813.7) / 54453) |
| = | 0.900915 | / | 0.920719 |
| | = | 0.9785 |
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 |
| = | (3557.6 - 51.8 | - | 3948.7) | / | 57069.4 |
| | = | -0.007761 |
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.
Automatic Data Processing has a M-score of -2.48 suggests that the company is unlikely to be a manipulator.
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