EVO Payments Beneish M-Score Historical Data
The historical data trend for EVO Payments'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.
EVO Payments Beneish M-Score Chart
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EVO Payments Annual Data
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Trend |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
| Beneish M-Score |
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-3.14 |
-3.02 |
-2.92 |
-2.78 |
-2.56 |
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EVO Payments Quarterly Data
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Mar18 |
Jun18 |
Sep18 |
Dec18 |
Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
| Beneish M-Score |
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-2.78 |
-2.56 |
5.68 |
6.66 |
-2.56 |
Competitive Comparison of EVO Payments's Beneish M-Score
For the Software - Infrastructure subindustry, EVO Payments'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.
EVO Payments's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, EVO Payments's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where EVO Payments's Beneish M-Score falls into.
EVO Payments 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 EVO Payments 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 * 1.171 | + | 0.528 * 1.0144 | + | 0.404 * 0.9818 | + | 0.892 * 1.0935 | + | 0.115 * 1.0361 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0637 | + | 4.679 * -0.064989 | - | 0.327 * 1.0183 |
| = | -2.56 |
* 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 (Dec22) TTM: | Last Year (Dec21) TTM: |
Total Receivables was $43.7 Mil.
Revenue was 139.822 + 138.663 + 137.671 + 126.926 = $543.1 Mil.
Gross Profit was 116.73 + 116.832 + 115.24 + 104.91 = $453.7 Mil.
Total Current Assets was $1,167.5 Mil.
Total Assets was $2,490.8 Mil.
Property, Plant and Equipment(Net PPE) was $110.9 Mil.
Depreciation, Depletion and Amortization(DDA) was $84.1 Mil.
Selling, General, & Admin. Expense(SGA) was $309.5 Mil.
Total Current Liabilities was $1,053.1 Mil.
Long-Term Debt & Capital Lease Obligation was $657.7 Mil.
Net Income was -1.863 + 0.206 + 4.353 + 2.583 = $5.3 Mil.
Non Operating Income was 2.623 + 4.653 + -3.45 + 0.261 = $4.1 Mil.
Cash Flow from Operations was 37.63 + 29.861 + 62.723 + 32.854 = $163.1 Mil.
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Total Receivables was $34.2 Mil.
Revenue was 133.189 + 135.041 + 122.235 + 106.18 = $496.6 Mil.
Gross Profit was 111.7 + 115.92 + 104.207 + 89.053 = $420.9 Mil.
Total Current Assets was $780.9 Mil.
Total Assets was $1,753.4 Mil.
Property, Plant and Equipment(Net PPE) was $103.2 Mil.
Depreciation, Depletion and Amortization(DDA) was $83.4 Mil.
Selling, General, & Admin. Expense(SGA) was $266.1 Mil.
Total Current Liabilities was $585.1 Mil.
Long-Term Debt & Capital Lease Obligation was $597.6 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) |
| = | (43.731 / 543.082) | / | (34.152 / 496.645) |
| = | 0.080524 | / | 0.068765 |
| | = | 1.171 |
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) |
| = | (420.88 / 496.645) | / | (453.712 / 543.082) |
| = | 0.847446 | / | 0.835439 |
| | = | 1.0144 |
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 - (1167.462 + 110.937) / 2490.815) | / | (1 - (780.925 + 103.21) / 1753.385) |
| = | 0.486755 | / | 0.495755 |
| | = | 0.9818 |
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 |
| = | 543.082 | / | 496.645 |
| | = | 1.0935 |
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)) |
| = | (83.389 / (83.389 + 103.21)) | / | (84.143 / (84.143 + 110.937)) |
| = | 0.446889 | / | 0.431326 |
| | = | 1.0361 |
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) |
| = | (309.539 / 543.082) | / | (266.117 / 496.645) |
| = | 0.569967 | / | 0.535829 |
| | = | 1.0637 |
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) |
| = | ((657.7 + 1053.144) / 2490.815) | / | ((597.58 + 585.125) / 1753.385) |
| = | 0.686861 | / | 0.674527 |
| | = | 1.0183 |
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 |
| = | (5.279 - 4.087 | - | 163.068) | / | 2490.815 |
| | = | -0.064989 |
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.
EVO Payments has a M-score of -2.56 suggests that the company is unlikely to be a manipulator.
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