Twilio Beneish M-Score Historical Data
The historical data trend for Twilio'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.
Twilio Beneish M-Score Chart
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Twilio Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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0.05 |
-2.00 |
-2.48 |
-2.37 |
-2.80 |
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Twilio 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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-2.37 |
-2.33 |
-2.47 |
-2.61 |
-2.80 |
Competitive Comparison of Twilio's Beneish M-Score
For the Internet Content & Information subindustry, Twilio'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.
Twilio's Beneish M-Score Distribution in the Interactive Media Industry
For the Interactive Media industry and Communication Services sector, Twilio's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Twilio's Beneish M-Score falls into.
Twilio 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 Twilio 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 * 0.9468 | + | 0.528 * 0.9633 | + | 0.404 * 0.966 | + | 0.892 * 1.0856 | + | 0.115 * 0.839 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.7782 | + | 4.679 * -0.070955 | - | 0.327 * 1.0144 |
| = | -2.80 |
* 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 $563 Mil.
Revenue was 1075.95 + 1033.67 + 1037.761 + 1006.564 = $4,154 Mil.
Gross Profit was 531.166 + 516.319 + 505.755 + 490.69 = $2,044 Mil.
Total Current Assets was $4,904 Mil.
Total Assets was $11,610 Mil.
Property, Plant and Equipment(Net PPE) was $284 Mil.
Depreciation, Depletion and Amortization(DDA) was $284 Mil.
Selling, General, & Admin. Expense(SGA) was $1,491 Mil.
Total Current Liabilities was $738 Mil.
Long-Term Debt & Capital Lease Obligation was $1,119 Mil.
Net Income was -365.408 + -141.707 + -166.187 + -342.139 = $-1,015 Mil.
Non Operating Income was -309.605 + -37.656 + -47.85 + -211.314 = $-606 Mil.
Cash Flow from Operations was 222.545 + 206.427 + 83.646 + -97.866 = $415 Mil.
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Total Receivables was $548 Mil.
Revenue was 1024.574 + 983.03 + 943.354 + 875.363 = $3,826 Mil.
Gross Profit was 481.142 + 462.075 + 445.289 + 425.071 = $1,814 Mil.
Total Current Assets was $4,984 Mil.
Total Assets was $12,564 Mil.
Property, Plant and Equipment(Net PPE) was $385 Mil.
Depreciation, Depletion and Amortization(DDA) was $279 Mil.
Selling, General, & Admin. Expense(SGA) was $1,765 Mil.
Total Current Liabilities was $808 Mil.
Long-Term Debt & Capital Lease Obligation was $1,173 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) |
| = | (562.773 / 4153.945) | / | (547.507 / 3826.321) |
| = | 0.135479 | / | 0.14309 |
| | = | 0.9468 |
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) |
| = | (1813.577 / 3826.321) | / | (2043.93 / 4153.945) |
| = | 0.473974 | / | 0.492046 |
| | = | 0.9633 |
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 - (4903.972 + 283.598) / 11609.707) | / | (1 - (4984.086 + 385.32) / 12564.304) |
| = | 0.55317 | / | 0.572646 |
| | = | 0.966 |
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 |
| = | 4153.945 | / | 3826.321 |
| | = | 1.0856 |
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)) |
| = | (279.127 / (279.127 + 385.32)) | / | (284.413 / (284.413 + 283.598)) |
| = | 0.420089 | / | 0.500717 |
| | = | 0.839 |
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) |
| = | (1491.444 / 4153.945) | / | (1765.446 / 3826.321) |
| = | 0.359043 | / | 0.461395 |
| | = | 0.7782 |
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) |
| = | ((1118.914 + 738.297) / 11609.707) | / | ((1173.223 + 808.158) / 12564.304) |
| = | 0.159971 | / | 0.157699 |
| | = | 1.0144 |
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 |
| = | (-1015.441 - -606.425 | - | 414.752) | / | 11609.707 |
| | = | -0.070955 |
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.
Twilio has a M-score of -2.80 suggests that the company is unlikely to be a manipulator.
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