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 * 1.0715 | + | 0.528 * 0.9752 | + | 0.404 * 0.9164 | + | 0.892 * 1.0588 | + | 0.115 * 1.0406 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0696 | + | 4.679 * -0.027243 | - | 0.327 * 1.0508 |
| = | -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 (Mar24) TTM: | Last Year (Mar23) TTM: |
Total Receivables was $3,857 Mil.
Revenue was 652.7 + 663.3 + 651.4 + 621.3 = $2,589 Mil.
Gross Profit was 385.5 + 407.4 + 416.3 + 386.3 = $1,596 Mil.
Total Current Assets was $9,535 Mil.
Total Assets was $14,422 Mil.
Property, Plant and Equipment(Net PPE) was $250 Mil.
Depreciation, Depletion and Amortization(DDA) was $288 Mil.
Selling, General, & Admin. Expense(SGA) was $761 Mil.
Total Current Liabilities was $8,986 Mil.
Long-Term Debt & Capital Lease Obligation was $3,082 Mil.
Net Income was 65.8 + 84.9 + 18.4 + 95.3 = $264 Mil.
Non Operating Income was -14.2 + 32.1 + -88.9 + 0.8 = $-70 Mil.
Cash Flow from Operations was -153.3 + 761.9 + 46.5 + 72.4 = $728 Mil.
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Total Receivables was $3,400 Mil.
Revenue was 612 + 618.7 + 616.1 + 598.2 = $2,445 Mil.
Gross Profit was 364.7 + 366.9 + 364 + 373.9 = $1,470 Mil.
Total Current Assets was $8,051 Mil.
Total Assets was $12,727 Mil.
Property, Plant and Equipment(Net PPE) was $210 Mil.
Depreciation, Depletion and Amortization(DDA) was $264 Mil.
Selling, General, & Admin. Expense(SGA) was $672 Mil.
Total Current Liabilities was $7,503 Mil.
Long-Term Debt & Capital Lease Obligation was $2,631 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) |
| = | (3857.2 / 2588.7) | / | (3400.1 / 2445) |
| = | 1.490014 | / | 1.390634 |
| | = | 1.0715 |
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) |
| = | (1469.5 / 2445) | / | (1595.5 / 2588.7) |
| = | 0.601022 | / | 0.616333 |
| | = | 0.9752 |
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 - (9534.5 + 249.5) / 14421.8) | / | (1 - (8051.2 + 209.8) / 12727.3) |
| = | 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 |
| = | 2588.7 | / | 2445 |
| | = | 1.0588 |
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)) |
| = | (264.2 / (264.2 + 209.8)) | / | (287.8 / (287.8 + 249.5)) |
| = | 0.557384 | / | 0.535641 |
| | = | 1.0406 |
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) |
| = | (760.8 / 2588.7) | / | (671.8 / 2445) |
| = | 0.293893 | / | 0.274765 |
| | = | 1.0696 |
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) |
| = | ((3081.5 + 8985.5) / 14421.8) | / | ((2631.3 + 7502.6) / 12727.3) |
| = | 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 |
| = | (264.4 - -70.2 | - | 727.5) | / | 14421.8 |
| | = | -0.027243 |
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 -2.56 suggests that the company is unlikely to be a manipulator.
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