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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-0.61 |
-2.00 |
-2.48 |
-2.38 |
-2.82 |
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Twilio Quarterly Data
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Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
| Beneish M-Score |
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-2.61 |
-2.82 |
-2.99 |
-3.01 |
-2.95 |
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 * 0.9165 | + | 0.528 * 0.9543 | + | 0.404 * 1.0996 | + | 0.892 * 1.0374 | + | 0.115 * 0.8066 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.7977 | + | 4.679 * -0.097577 | - | 0.327 * 1.1341 |
| = | -3.00 |
* 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 (Sep24) TTM: | Last Year (Sep23) TTM: |
Total Receivables was €496 Mil.
Revenue was 1021.418 + 1005.644 + 963.286 + 986.646 = €3,977 Mil.
Gross Profit was 521.345 + 516.38 + 500.518 + 487.079 = €2,025 Mil.
Total Current Assets was €3,197 Mil.
Total Assets was €9,044 Mil.
Property, Plant and Equipment(Net PPE) was €131 Mil.
Depreciation, Depletion and Amortization(DDA) was €203 Mil.
Selling, General, & Admin. Expense(SGA) was €1,212 Mil.
Total Current Liabilities was €631 Mil.
Long-Term Debt & Capital Lease Obligation was €978 Mil.
Net Income was -8.763 + -29.596 + -50.921 + -335.079 = €-424 Mil.
Non Operating Income was -2.208 + -6.406 + -10.675 + -283.908 = €-303 Mil.
Cash Flow from Operations was 184.1 + 198.196 + 174.913 + 204.074 = €761 Mil.
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Total Receivables was €522 Mil.
Revenue was 968.549 + 957.853 + 940.131 + 967.198 = €3,834 Mil.
Gross Profit was 483.791 + 466.812 + 458.304 + 454.198 = €1,863 Mil.
Total Current Assets was €4,443 Mil.
Total Assets was €11,111 Mil.
Property, Plant and Equipment(Net PPE) was €282 Mil.
Depreciation, Depletion and Amortization(DDA) was €271 Mil.
Selling, General, & Admin. Expense(SGA) was €1,465 Mil.
Total Current Liabilities was €680 Mil.
Long-Term Debt & Capital Lease Obligation was €1,063 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) |
| = | (496.362 / 3976.994) | / | (522.097 / 3833.731) |
| = | 0.124808 | / | 0.136185 |
| | = | 0.9165 |
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) |
| = | (1863.105 / 3833.731) | / | (2025.322 / 3976.994) |
| = | 0.485977 | / | 0.50926 |
| | = | 0.9543 |
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 - (3197.038 + 131.395) / 9043.569) | / | (1 - (4442.859 + 282.396) / 11110.701) |
| = | 0.631956 | / | 0.574711 |
| | = | 1.0996 |
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 |
| = | 3976.994 | / | 3833.731 |
| | = | 1.0374 |
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)) |
| = | (271.165 / (271.165 + 282.396)) | / | (203.193 / (203.193 + 131.395)) |
| = | 0.489856 | / | 0.607293 |
| | = | 0.8066 |
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) |
| = | (1212.146 / 3976.994) | / | (1464.846 / 3833.731) |
| = | 0.304789 | / | 0.382094 |
| | = | 0.7977 |
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) |
| = | ((977.526 + 631.364) / 9043.569) | / | ((1062.504 + 680.372) / 11110.701) |
| = | 0.177904 | / | 0.156865 |
| | = | 1.1341 |
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 |
| = | (-424.359 - -303.197 | - | 761.283) | / | 9043.569 |
| | = | -0.097577 |
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 -3.00 suggests that the company is unlikely to be a manipulator.
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