Confluent Beneish M-Score Historical Data
The historical data trend for Confluent'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.
Confluent Beneish M-Score Chart
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Confluent Annual Data
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Trend |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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- |
- |
-3.00 |
-2.69 |
-2.75 |
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Confluent Quarterly Data
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Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-2.69 |
-2.49 |
-2.64 |
-2.70 |
-2.75 |
Competitive Comparison of Confluent's Beneish M-Score
For the Software - Infrastructure subindustry, Confluent'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.
Confluent's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, Confluent's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Confluent's Beneish M-Score falls into.
Confluent 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 Confluent 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 * 0.9723 | + | 0.528 * 0.9294 | + | 0.404 * 1.5682 | + | 0.892 * 1.2893 | + | 0.115 * 0.647 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.8335 | + | 4.679 * -0.154491 | - | 0.327 * 0.9894 |
| = | -2.79 |
* 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 €210.9 Mil.
Revenue was 195.49 + 187.57 + 174.71 + 162.798 = €720.6 Mil.
Gross Profit was 143.168 + 134.583 + 121.25 + 108.492 = €507.5 Mil.
Total Current Assets was €2,064.8 Mil.
Total Assets was €2,256.6 Mil.
Property, Plant and Equipment(Net PPE) was €58.8 Mil.
Depreciation, Depletion and Amortization(DDA) was €12.9 Mil.
Selling, General, & Admin. Expense(SGA) was €596.1 Mil.
Total Current Liabilities was €446.6 Mil.
Long-Term Debt & Capital Lease Obligation was €1,013.9 Mil.
Net Income was -86.286 + -86.832 + -95.461 + -142.486 = €-411.1 Mil.
Non Operating Income was 19.968 + 15.929 + 15.384 + -16.996 = €34.3 Mil.
Cash Flow from Operations was 11.219 + -8.489 + -26.822 + -72.639 = €-96.7 Mil.
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Total Receivables was €168.2 Mil.
Revenue was 159.221 + 153.249 + 131.879 + 114.534 = €558.9 Mil.
Gross Profit was 108.293 + 99.538 + 85.044 + 72.969 = €365.8 Mil.
Total Current Assets was €2,075.0 Mil.
Total Assets was €2,213.5 Mil.
Property, Plant and Equipment(Net PPE) was €55.3 Mil.
Depreciation, Depletion and Amortization(DDA) was €7.3 Mil.
Selling, General, & Admin. Expense(SGA) was €554.7 Mil.
Total Current Liabilities was €400.6 Mil.
Long-Term Debt & Capital Lease Obligation was €1,047.5 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) |
| = | (210.875 / 720.568) | / | (168.209 / 558.883) |
| = | 0.292651 | / | 0.300974 |
| | = | 0.9723 |
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) |
| = | (365.844 / 558.883) | / | (507.493 / 720.568) |
| = | 0.654599 | / | 0.704296 |
| | = | 0.9294 |
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 - (2064.768 + 58.755) / 2256.562) | / | (1 - (2075.03 + 55.287) / 2213.537) |
| = | 0.058957 | / | 0.037596 |
| | = | 1.5682 |
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 |
| = | 720.568 | / | 558.883 |
| | = | 1.2893 |
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)) |
| = | (7.289 / (7.289 + 55.287)) | / | (12.9 / (12.9 + 58.755)) |
| = | 0.116482 | / | 0.180029 |
| | = | 0.647 |
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) |
| = | (596.108 / 720.568) | / | (554.741 / 558.883) |
| = | 0.827275 | / | 0.992589 |
| | = | 0.8335 |
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) |
| = | ((1013.931 + 446.598) / 2256.562) | / | ((1047.496 + 400.568) / 2213.537) |
| = | 0.647236 | / | 0.654186 |
| | = | 0.9894 |
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 |
| = | (-411.065 - 34.285 | - | -96.731) | / | 2256.562 |
| | = | -0.154491 |
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.
Confluent has a M-score of -2.79 suggests that the company is unlikely to be a manipulator.
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