WEX Beneish M-Score Historical Data
The historical data trend for WEX'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.
WEX Beneish M-Score Chart
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WEX Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.72 |
-3.06 |
-2.17 |
-2.46 |
-2.72 |
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WEX Quarterly Data
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Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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-2.73 |
-2.90 |
-2.63 |
-2.72 |
-2.56 |
Competitive Comparison of WEX's Beneish M-Score
For the Software - Infrastructure subindustry, WEX'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.
WEX's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, WEX's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where WEX's Beneish M-Score falls into.
WEX 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 WEX 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 * 1.0947 | + | 0.528 * 0.9747 | + | 0.404 * 0.9164 | + | 0.892 * 1.0208 | + | 0.115 * 1.0504 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.07 | + | 4.679 * -0.027 | - | 0.327 * 1.0508 |
| = | -2.57 |
* 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 (Mar24) TTM: | Last Year (Mar23) TTM: |
Total Receivables was €3,549 Mil.
Revenue was 600.484 + 608.246 + 610.362 + 573.46 = €2,393 Mil.
Gross Profit was 354.66 + 373.586 + 390.073 + 356.555 = €1,475 Mil.
Total Current Assets was €8,772 Mil.
Total Assets was €13,268 Mil.
Property, Plant and Equipment(Net PPE) was €230 Mil.
Depreciation, Depletion and Amortization(DDA) was €266 Mil.
Selling, General, & Admin. Expense(SGA) was €703 Mil.
Total Current Liabilities was €8,267 Mil.
Long-Term Debt & Capital Lease Obligation was €2,835 Mil.
Net Income was 60.536 + 77.853 + 17.241 + 87.962 = €244 Mil.
Non Operating Income was -13.064 + 29.436 + -83.299 + 0.738 = €-66 Mil.
Cash Flow from Operations was -141.036 + 698.662 + 43.571 + 66.825 = €668 Mil.
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Total Receivables was €3,176 Mil.
Revenue was 571.608 + 584.053 + 622.261 + 565.897 = €2,344 Mil.
Gross Profit was 340.63 + 346.354 + 367.64 + 353.709 = €1,408 Mil.
Total Current Assets was €7,520 Mil.
Total Assets was €11,887 Mil.
Property, Plant and Equipment(Net PPE) was €196 Mil.
Depreciation, Depletion and Amortization(DDA) was €253 Mil.
Selling, General, & Admin. Expense(SGA) was €644 Mil.
Total Current Liabilities was €7,007 Mil.
Long-Term Debt & Capital Lease Obligation was €2,458 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) |
| = | (3548.624 / 2392.552) | / | (3175.693 / 2343.819) |
| = | 1.483196 | / | 1.354922 |
| | = | 1.0947 |
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) |
| = | (1408.333 / 2343.819) | / | (1474.874 / 2392.552) |
| = | 0.600871 | / | 0.616444 |
| | = | 0.9747 |
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 - (8771.74 + 229.54) / 13268.056) | / | (1 - (7519.821 + 195.953) / 11887.298) |
| = | 0.321583 | / | 0.350923 |
| | = | 0.9164 |
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 |
| = | 2392.552 | / | 2343.819 |
| | = | 1.0208 |
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)) |
| = | (253.23 / (253.23 + 195.953)) | / | (265.9 / (265.9 + 229.54)) |
| = | 0.563757 | / | 0.536695 |
| | = | 1.0504 |
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) |
| = | (703.273 / 2392.552) | / | (643.867 / 2343.819) |
| = | 0.293943 | / | 0.274708 |
| | = | 1.07 |
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) |
| = | ((2834.98 + 8266.66) / 13268.056) | / | ((2457.634 + 7007.428) / 11887.298) |
| = | 0.836719 | / | 0.796233 |
| | = | 1.0508 |
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 |
| = | (243.592 - -66.189 | - | 668.022) | / | 13268.056 |
| | = | -0.027 |
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.
WEX has a M-score of -2.57 suggests that the company is unlikely to be a manipulator.
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