Blackbaud Beneish M-Score Historical Data
The historical data trend for Blackbaud'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.
Blackbaud Beneish M-Score Chart
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Blackbaud Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.82 |
-2.75 |
-2.57 |
-2.92 |
-2.83 |
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Blackbaud 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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-2.92 |
-3.05 |
-2.82 |
-2.77 |
-2.83 |
Competitive Comparison of Blackbaud's Beneish M-Score
For the Software - Application subindustry, Blackbaud'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.
Blackbaud's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, Blackbaud's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Blackbaud's Beneish M-Score falls into.
Blackbaud 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 Blackbaud 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 * 0.9494 | + | 0.528 * 0.9572 | + | 0.404 * 0.9881 | + | 0.892 * 1.0447 | + | 0.115 * 0.8963 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9134 | + | 4.679 * -0.069311 | - | 0.327 * 0.9702 |
| = | -2.83 |
* 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 $102 Mil.
Revenue was 295.011 + 277.626 + 271.042 + 261.753 = $1,105 Mil.
Gross Profit was 159.176 + 155.86 + 149.567 + 138.641 = $603 Mil.
Total Current Assets was $930 Mil.
Total Assets was $2,912 Mil.
Property, Plant and Equipment(Net PPE) was $136 Mil.
Depreciation, Depletion and Amortization(DDA) was $109 Mil.
Selling, General, & Admin. Expense(SGA) was $402 Mil.
Total Current Liabilities was $1,197 Mil.
Long-Term Debt & Capital Lease Obligation was $800 Mil.
Net Income was 5.399 + 9.017 + 2.105 + -14.701 = $2 Mil.
Non Operating Income was 0.149 + 2.65 + 0.47 + 0.771 = $4 Mil.
Cash Flow from Operations was -3.349 + 127.981 + 53.196 + 21.806 = $200 Mil.
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Total Receivables was $103 Mil.
Revenue was 274.757 + 261.297 + 264.927 + 257.124 = $1,058 Mil.
Gross Profit was 139.274 + 140.36 + 139.32 + 133.762 = $553 Mil.
Total Current Assets was $919 Mil.
Total Assets was $2,993 Mil.
Property, Plant and Equipment(Net PPE) was $153 Mil.
Depreciation, Depletion and Amortization(DDA) was $102 Mil.
Selling, General, & Admin. Expense(SGA) was $421 Mil.
Total Current Liabilities was $1,231 Mil.
Long-Term Debt & Capital Lease Obligation was $885 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) |
| = | (102.215 / 1105.432) | / | (103.058 / 1058.105) |
| = | 0.092466 | / | 0.097399 |
| | = | 0.9494 |
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) |
| = | (552.716 / 1058.105) | / | (603.244 / 1105.432) |
| = | 0.522364 | / | 0.545709 |
| | = | 0.9572 |
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 - (929.757 + 135.616) / 2912.279) | / | (1 - (918.643 + 153.325) / 2992.703) |
| = | 0.634179 | / | 0.641806 |
| | = | 0.9881 |
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 |
| = | 1105.432 | / | 1058.105 |
| | = | 1.0447 |
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)) |
| = | (102.369 / (102.369 + 153.325)) | / | (109.487 / (109.487 + 135.616)) |
| = | 0.400357 | / | 0.446698 |
| | = | 0.8963 |
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) |
| = | (402.096 / 1105.432) | / | (421.363 / 1058.105) |
| = | 0.363746 | / | 0.398224 |
| | = | 0.9134 |
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) |
| = | ((800.49 + 1197.137) / 2912.279) | / | ((885.159 + 1230.642) / 2992.703) |
| = | 0.685933 | / | 0.706987 |
| | = | 0.9702 |
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 |
| = | (1.82 - 4.04 | - | 199.634) | / | 2912.279 |
| | = | -0.069311 |
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.
Blackbaud has a M-score of -2.83 suggests that the company is unlikely to be a manipulator.
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