First Data Beneish M-Score Historical Data
The historical data trend for First Data'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.
First Data Beneish M-Score Chart
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First Data Annual Data
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Trend |
Dec09 |
Dec10 |
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Dec13 |
Dec14 |
Dec15 |
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Dec17 |
Dec18 |
| Beneish M-Score |
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-2.67 |
-2.60 |
-2.70 |
-2.45 |
-2.71 |
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First Data Quarterly Data
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Sep14 |
Dec14 |
Mar15 |
Jun15 |
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Jun16 |
Sep16 |
Dec16 |
Mar17 |
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Mar18 |
Jun18 |
Sep18 |
Dec18 |
Mar19 |
Jun19 |
| Beneish M-Score |
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-2.51 |
-2.69 |
-2.71 |
-2.77 |
-2.79 |
Competitive Comparison of First Data's Beneish M-Score
For the Specialty Business Services subindustry, First Data'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.
First Data's Beneish M-Score Distribution in the Business Services Industry
For the Business Services industry and Industrials sector, First Data's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where First Data's Beneish M-Score falls into.
First Data 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 First Data 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 * 1.1252 | + | 0.528 * 0.8233 | + | 0.404 * 0.8624 | + | 0.892 * 0.8734 | + | 0.115 * 1.0392 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.2412 | + | 4.679 * -0.027787 | - | 0.327 * 0.9959 |
| = | -2.79 |
* 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 (Jun19) TTM: | Last Year (Jun18) TTM: |
Total Receivables was $2,162 Mil.
Revenue was 2485 + 2316 + 2399 + 2369 = $9,569 Mil.
Gross Profit was 1532 + 1367 + 1459 + 1417 = $5,775 Mil.
Total Current Assets was $26,958 Mil.
Total Assets was $51,031 Mil.
Property, Plant and Equipment(Net PPE) was $922 Mil.
Depreciation, Depletion and Amortization(DDA) was $1,069 Mil.
Selling, General, & Admin. Expense(SGA) was $2,669 Mil.
Total Current Liabilities was $26,806 Mil.
Long-Term Debt & Capital Lease Obligation was $15,811 Mil.
Net Income was 275 + 169 + 162 + 401 = $1,007 Mil.
Non Operating Income was -21 + -64 + -166 + 179 = $-72 Mil.
Cash Flow from Operations was 713 + 615 + 498 + 671 = $2,497 Mil.
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Total Receivables was $2,200 Mil.
Revenue was 2448 + 2282 + 3150 + 3076 = $10,956 Mil.
Gross Profit was 1493 + 1305 + 1359 + 1287 = $5,444 Mil.
Total Current Assets was $20,201 Mil.
Total Assets was $44,447 Mil.
Property, Plant and Equipment(Net PPE) was $866 Mil.
Depreciation, Depletion and Amortization(DDA) was $1,093 Mil.
Selling, General, & Admin. Expense(SGA) was $2,462 Mil.
Total Current Liabilities was $19,556 Mil.
Long-Term Debt & Capital Lease Obligation was $17,717 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) |
| = | (2162 / 9569) | / | (2200 / 10956) |
| = | 0.225938 | / | 0.200803 |
| | = | 1.1252 |
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) |
| = | (5444 / 10956) | / | (5775 / 9569) |
| = | 0.496897 | / | 0.603511 |
| | = | 0.8233 |
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 - (26958 + 922) / 51031) | / | (1 - (20201 + 866) / 44447) |
| = | 0.453665 | / | 0.52602 |
| | = | 0.8624 |
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 |
| = | 9569 | / | 10956 |
| | = | 0.8734 |
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)) |
| = | (1093 / (1093 + 866)) | / | (1069 / (1069 + 922)) |
| = | 0.557938 | / | 0.536916 |
| | = | 1.0392 |
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) |
| = | (2669 / 9569) | / | (2462 / 10956) |
| = | 0.278922 | / | 0.224717 |
| | = | 1.2412 |
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) |
| = | ((15811 + 26806) / 51031) | / | ((17717 + 19556) / 44447) |
| = | 0.83512 | / | 0.838594 |
| | = | 0.9959 |
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 |
| = | (1007 - -72 | - | 2497) | / | 51031 |
| | = | -0.027787 |
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.
First Data has a M-score of -2.79 suggests that the company is unlikely to be a manipulator.
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