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 |
Dec24 |
| Beneish M-Score |
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- |
-3.00 |
-2.69 |
-2.75 |
-2.73 |
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Confluent Quarterly Data
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Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
Dec24 |
Mar25 |
| Beneish M-Score |
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-3.07 |
-2.99 |
-2.56 |
-2.73 |
-2.56 |
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 * 1.2678 | + | 0.528 * 0.9683 | + | 0.404 * 1.6864 | + | 0.892 * 1.4493 | + | 0.115 * 0.8582 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.8946 | + | 4.679 * -0.156505 | - | 0.327 * 0.9556 |
| = | -2.29 |
* 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 (Mar25) TTM: | Last Year (Mar24) TTM: |
Total Receivables was MXN6,094 Mil.
Revenue was 5546.627 + 5447.926 + 4926.493 + 4304.968 = MXN20,226 Mil.
Gross Profit was 4132.597 + 4038.811 + 3672.162 + 3114.509 = MXN14,958 Mil.
Total Current Assets was MXN47,930 Mil.
Total Assets was MXN55,210 Mil.
Property, Plant and Equipment(Net PPE) was MXN1,833 Mil.
Depreciation, Depletion and Amortization(DDA) was MXN484 Mil.
Selling, General, & Admin. Expense(SGA) was MXN14,312 Mil.
Total Current Liabilities was MXN10,840 Mil.
Long-Term Debt & Capital Lease Obligation was MXN22,501 Mil.
Net Income was -1382.442 + -1836.428 + -1459.918 + -1646.977 = MXN-6,326 Mil.
Non Operating Income was 417.552 + 402.265 + 442.933 + 400.349 = MXN1,663 Mil.
Cash Flow from Operations was -547.339 + 734.35 + 307.425 + 157.37 = MXN652 Mil.
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Total Receivables was MXN3,317 Mil.
Revenue was 3605.321 + 3618.638 + 3486.932 + 3245.083 = MXN13,956 Mil.
Gross Profit was 2589.281 + 2650.138 + 2501.911 + 2252.108 = MXN9,993 Mil.
Total Current Assets was MXN36,945 Mil.
Total Assets was MXN40,489 Mil.
Property, Plant and Equipment(Net PPE) was MXN1,175 Mil.
Depreciation, Depletion and Amortization(DDA) was MXN257 Mil.
Selling, General, & Admin. Expense(SGA) was MXN11,039 Mil.
Total Current Liabilities was MXN7,289 Mil.
Long-Term Debt & Capital Lease Obligation was MXN18,298 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) |
| = | (6093.72 / 20226.014) | / | (3316.629 / 13955.974) |
| = | 0.301281 | / | 0.237649 |
| | = | 1.2678 |
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) |
| = | (9993.438 / 13955.974) | / | (14958.079 / 20226.014) |
| = | 0.716069 | / | 0.739547 |
| | = | 0.9683 |
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 - (47930.248 + 1833.464) / 55210.012) | / | (1 - (36945.205 + 1175.065) / 40488.705) |
| = | 0.098647 | / | 0.058496 |
| | = | 1.6864 |
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 |
| = | 20226.014 | / | 13955.974 |
| | = | 1.4493 |
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)) |
| = | (256.822 / (256.822 + 1175.065)) | / | (484.44 / (484.44 + 1833.464)) |
| = | 0.179359 | / | 0.208999 |
| | = | 0.8582 |
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) |
| = | (14312.232 / 20226.014) | / | (11038.854 / 13955.974) |
| = | 0.707615 | / | 0.790977 |
| | = | 0.8946 |
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) |
| = | ((22500.522 + 10840.146) / 55210.012) | / | ((18298.201 + 7289.042) / 40488.705) |
| = | 0.603888 | / | 0.63196 |
| | = | 0.9556 |
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 |
| = | (-6325.765 - 1663.099 | - | 651.806) | / | 55210.012 |
| | = | -0.156505 |
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 -2.29 suggests that the company is unlikely to be a manipulator.
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