BlackLine Beneish M-Score Historical Data
The historical data trend for BlackLine'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.
BlackLine Beneish M-Score Chart
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BlackLine Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.89 |
-2.64 |
-3.08 |
-2.37 |
-2.49 |
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BlackLine 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 |
-2.70 |
-2.60 |
-2.42 |
-2.49 |
Competitive Comparison of BlackLine's Beneish M-Score
For the Software - Application subindustry, BlackLine'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.
BlackLine's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, BlackLine's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where BlackLine's Beneish M-Score falls into.
BlackLine 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 BlackLine 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 * 1.0083 | + | 0.528 * 1.0018 | + | 0.404 * 0.925 | + | 0.892 * 1.1282 | + | 0.115 * 0.9298 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.8276 | + | 4.679 * -0.029901 | - | 0.327 * 0.9445 |
| = | -2.49 |
* 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 $171.6 Mil.
Revenue was 155.73 + 150.708 + 144.574 + 138.984 = $590.0 Mil.
Gross Profit was 118.118 + 113.914 + 107.458 + 103.713 = $443.2 Mil.
Total Current Assets was $1,407.3 Mil.
Total Assets was $2,100.8 Mil.
Property, Plant and Equipment(Net PPE) was $34.0 Mil.
Depreciation, Depletion and Amortization(DDA) was $50.1 Mil.
Selling, General, & Admin. Expense(SGA) was $314.7 Mil.
Total Current Liabilities was $642.6 Mil.
Long-Term Debt & Capital Lease Obligation was $1,156.4 Mil.
Net Income was 22.069 + 11.923 + 30.849 + -12.008 = $52.8 Mil.
Non Operating Income was -1.151 + -8.664 + -0.135 + -1.014 = $-11.0 Mil.
Cash Flow from Operations was 42.169 + 37.026 + 24.551 + 22.867 = $126.6 Mil.
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Total Receivables was $150.9 Mil.
Revenue was 139.957 + 134.268 + 128.477 + 120.236 = $522.9 Mil.
Gross Profit was 106.594 + 101.842 + 95.554 + 89.563 = $393.6 Mil.
Total Current Assets was $1,249.6 Mil.
Total Assets was $1,943.7 Mil.
Property, Plant and Equipment(Net PPE) was $34.5 Mil.
Depreciation, Depletion and Amortization(DDA) was $42.8 Mil.
Selling, General, & Admin. Expense(SGA) was $337.0 Mil.
Total Current Liabilities was $367.8 Mil.
Long-Term Debt & Capital Lease Obligation was $1,394.4 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) |
| = | (171.608 / 589.996) | / | (150.858 / 522.938) |
| = | 0.290863 | / | 0.288482 |
| | = | 1.0083 |
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) |
| = | (393.553 / 522.938) | / | (443.203 / 589.996) |
| = | 0.752581 | / | 0.751197 |
| | = | 1.0018 |
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 - (1407.324 + 34.04) / 2100.765) | / | (1 - (1249.567 + 34.519) / 1943.656) |
| = | 0.313886 | / | 0.339345 |
| | = | 0.925 |
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 |
| = | 589.996 | / | 522.938 |
| | = | 1.1282 |
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)) |
| = | (42.816 / (42.816 + 34.519)) | / | (50.099 / (50.099 + 34.04)) |
| = | 0.553643 | / | 0.595431 |
| | = | 0.9298 |
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) |
| = | (314.684 / 589.996) | / | (337.017 / 522.938) |
| = | 0.533366 | / | 0.644468 |
| | = | 0.8276 |
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) |
| = | ((1156.35 + 642.565) / 2100.765) | / | ((1394.383 + 367.821) / 1943.656) |
| = | 0.856314 | / | 0.906644 |
| | = | 0.9445 |
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 |
| = | (52.833 - -10.964 | - | 126.613) | / | 2100.765 |
| | = | -0.029901 |
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.
BlackLine has a M-score of -2.49 suggests that the company is unlikely to be a manipulator.
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