Corpay Beneish M-Score Historical Data
The historical data trend for Corpay'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.
Corpay Beneish M-Score Chart
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Corpay Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.50 |
-2.89 |
-2.47 |
-2.28 |
-2.78 |
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Corpay 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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-2.28 |
-2.50 |
-2.62 |
-2.35 |
-2.78 |
Competitive Comparison of Corpay's Beneish M-Score
For the Software - Infrastructure subindustry, Corpay'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.
Corpay's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, Corpay's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Corpay's Beneish M-Score falls into.
Corpay 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 Corpay 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 * 0.9548 | + | 0.528 * 0.9937 | + | 0.404 * 0.9531 | + | 0.892 * 1.0965 | + | 0.115 * 1.0549 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9635 | + | 4.679 * -0.073402 | - | 0.327 * 0.9658 |
| = | -2.78 |
* 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 $2,162 Mil.
Revenue was 937.32 + 970.892 + 948.174 + 901.333 = $3,758 Mil.
Gross Profit was 735.861 + 762.675 + 742.909 + 696.366 = $2,938 Mil.
Total Current Assets was $7,084 Mil.
Total Assets was $15,476 Mil.
Property, Plant and Equipment(Net PPE) was $343 Mil.
Depreciation, Depletion and Amortization(DDA) was $337 Mil.
Selling, General, & Admin. Expense(SGA) was $944 Mil.
Total Current Liabilities was $6,826 Mil.
Long-Term Debt & Capital Lease Obligation was $4,596 Mil.
Net Income was 255.857 + 271.496 + 239.702 + 214.835 = $982 Mil.
Non Operating Income was 1.487 + 13.402 + 2.406 + -0.556 = $17 Mil.
Cash Flow from Operations was 1197.263 + 77.189 + 499.015 + 327.665 = $2,101 Mil.
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Total Receivables was $2,065 Mil.
Revenue was 883.61 + 893 + 861.278 + 789.241 = $3,427 Mil.
Gross Profit was 682 + 689.685 + 675.69 + 615.047 = $2,662 Mil.
Total Current Assets was $6,106 Mil.
Total Assets was $14,089 Mil.
Property, Plant and Equipment(Net PPE) was $295 Mil.
Depreciation, Depletion and Amortization(DDA) was $322 Mil.
Selling, General, & Admin. Expense(SGA) was $893 Mil.
Total Current Liabilities was $6,043 Mil.
Long-Term Debt & Capital Lease Obligation was $4,723 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) |
| = | (2161.586 / 3757.719) | / | (2064.745 / 3427.129) |
| = | 0.575239 | / | 0.602471 |
| | = | 0.9548 |
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) |
| = | (2662.422 / 3427.129) | / | (2937.811 / 3757.719) |
| = | 0.776867 | / | 0.781807 |
| | = | 0.9937 |
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 - (7084.265 + 343.154) / 15476.252) | / | (1 - (6106.152 + 294.692) / 14089.26) |
| = | 0.520076 | / | 0.545693 |
| | = | 0.9531 |
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 |
| = | 3757.719 | / | 3427.129 |
| | = | 1.0965 |
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)) |
| = | (322.282 / (322.282 + 294.692)) | / | (336.604 / (336.604 + 343.154)) |
| = | 0.522359 | / | 0.495182 |
| | = | 1.0549 |
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) |
| = | (943.581 / 3757.719) | / | (893.217 / 3427.129) |
| = | 0.251105 | / | 0.260631 |
| | = | 0.9635 |
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) |
| = | ((4596.156 + 6825.753) / 15476.252) | / | ((4722.838 + 6043.455) / 14089.26) |
| = | 0.738028 | / | 0.764149 |
| | = | 0.9658 |
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 |
| = | (981.89 - 16.739 | - | 2101.132) | / | 15476.252 |
| | = | -0.073402 |
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.
Corpay has a M-score of -2.78 suggests that the company is unlikely to be a manipulator.
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