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 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
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-2.00 |
-2.48 |
-2.38 |
-2.78 |
-2.81 |
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Twilio Quarterly Data
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Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
Dec24 |
| Beneish M-Score |
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-2.78 |
-2.99 |
-3.01 |
-2.95 |
-2.81 |
Competitive Comparison of Twilio's Beneish M-Score
For the Software - Infrastructure 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 Software Industry
For the Software industry and Technology 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 * 0.9745 | + | 0.528 * 0.9628 | + | 0.404 * 1.1341 | + | 0.892 * 1.0732 | + | 0.115 * 0.9939 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.8319 | + | 4.679 * -0.078807 | - | 0.327 * 1.2078 |
| = | -2.81 |
* 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 (Dec24) TTM: | Last Year (Dec23) TTM: |
Total Receivables was $589 Mil.
Revenue was 1194.835 + 1133.649 + 1082.502 + 1047.05 = $4,458 Mil.
Gross Profit was 599.697 + 578.629 + 555.845 + 544.041 = $2,278 Mil.
Total Current Assets was $3,447 Mil.
Total Assets was $9,865 Mil.
Property, Plant and Equipment(Net PPE) was $126 Mil.
Depreciation, Depletion and Amortization(DDA) was $206 Mil.
Selling, General, & Admin. Expense(SGA) was $1,263 Mil.
Total Current Liabilities was $820 Mil.
Long-Term Debt & Capital Lease Obligation was $1,076 Mil.
Net Income was -12.47 + -9.726 + -31.858 + -55.349 = $-109 Mil.
Non Operating Income was -27.228 + -2.451 + -6.896 + -11.603 = $-48 Mil.
Cash Flow from Operations was 108.446 + 204.329 + 213.343 + 190.123 = $716 Mil.
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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 $177 Mil.
Depreciation, Depletion and Amortization(DDA) was $284 Mil.
Selling, General, & Admin. Expense(SGA) was $1,414 Mil.
Total Current Liabilities was $738 Mil.
Long-Term Debt & Capital Lease Obligation was $1,110 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) |
| = | (588.54 / 4458.036) | / | (562.773 / 4153.945) |
| = | 0.132018 | / | 0.135479 |
| | = | 0.9745 |
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) |
| = | (2043.93 / 4153.945) | / | (2278.212 / 4458.036) |
| = | 0.492046 | / | 0.511035 |
| | = | 0.9628 |
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 - (3447.299 + 126.039) / 9865.472) | / | (1 - (4903.972 + 176.861) / 11609.707) |
| = | 0.637794 | / | 0.562363 |
| | = | 1.1341 |
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 |
| = | 4458.036 | / | 4153.945 |
| | = | 1.0732 |
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)) |
| = | (284.413 / (284.413 + 176.861)) | / | (205.984 / (205.984 + 126.039)) |
| = | 0.616581 | / | 0.620391 |
| | = | 0.9939 |
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) |
| = | (1262.644 / 4458.036) | / | (1414.316 / 4153.945) |
| = | 0.283229 | / | 0.340475 |
| | = | 0.8319 |
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) |
| = | ((1076.462 + 820.22) / 9865.472) | / | ((1109.723 + 738.297) / 11609.707) |
| = | 0.192255 | / | 0.159179 |
| | = | 1.2078 |
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 |
| = | (-109.403 - -48.178 | - | 716.241) | / | 9865.472 |
| | = | -0.078807 |
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 -2.81 suggests that the company is unlikely to be a manipulator.
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