N-able Beneish M-Score Historical Data
The historical data trend for N-able'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.
N-able Beneish M-Score Chart
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N-able Annual Data
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Trend |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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- |
- |
-2.37 |
-2.64 |
-2.64 |
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N-able Quarterly Data
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Dec18 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-2.64 |
-2.54 |
-2.42 |
-2.41 |
-2.64 |
Competitive Comparison of N-able's Beneish M-Score
For the Information Technology Services subindustry, N-able'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.
N-able's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, N-able's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where N-able's Beneish M-Score falls into.
N-able 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 N-able 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 * 0.9929 | + | 0.528 * 1.0048 | + | 0.404 * 0.9425 | + | 0.892 * 1.1348 | + | 0.115 * 1.0932 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9178 | + | 4.679 * -0.061005 | - | 0.327 * 0.9665 |
| = | -2.64 |
* 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 $48.0 Mil.
Revenue was 108.415 + 107.567 + 106.08 + 99.818 = $421.9 Mil.
Gross Profit was 90.794 + 90.211 + 89.058 + 83.609 = $353.7 Mil.
Total Current Assets was $224.8 Mil.
Total Assets was $1,162.8 Mil.
Property, Plant and Equipment(Net PPE) was $68.9 Mil.
Depreciation, Depletion and Amortization(DDA) was $21.6 Mil.
Selling, General, & Admin. Expense(SGA) was $204.6 Mil.
Total Current Liabilities was $81.7 Mil.
Long-Term Debt & Capital Lease Obligation was $364.6 Mil.
Net Income was 9.351 + 6.013 + 4.509 + 3.539 = $23.4 Mil.
Non Operating Income was 2.69 + -0.423 + 1.004 + 0.988 = $4.3 Mil.
Cash Flow from Operations was 31.22 + 27.512 + 20.726 + 10.631 = $90.1 Mil.
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Total Receivables was $42.6 Mil.
Revenue was 95.755 + 93.527 + 91.627 + 90.86 = $371.8 Mil.
Gross Profit was 80.68 + 78.424 + 77.458 + 76.597 = $313.2 Mil.
Total Current Assets was $154.2 Mil.
Total Assets was $1,078.9 Mil.
Property, Plant and Equipment(Net PPE) was $69.2 Mil.
Depreciation, Depletion and Amortization(DDA) was $24.4 Mil.
Selling, General, & Admin. Expense(SGA) was $196.4 Mil.
Total Current Liabilities was $61.8 Mil.
Long-Term Debt & Capital Lease Obligation was $366.6 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) |
| = | (48.014 / 421.88) | / | (42.612 / 371.769) |
| = | 0.11381 | / | 0.11462 |
| | = | 0.9929 |
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) |
| = | (313.159 / 371.769) | / | (353.672 / 421.88) |
| = | 0.842348 | / | 0.838324 |
| | = | 1.0048 |
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 - (224.791 + 68.905) / 1162.791) | / | (1 - (154.156 + 69.156) / 1078.857) |
| = | 0.747422 | / | 0.793011 |
| | = | 0.9425 |
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 |
| = | 421.88 | / | 371.769 |
| | = | 1.1348 |
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)) |
| = | (24.44 / (24.44 + 69.156)) | / | (21.623 / (21.623 + 68.905)) |
| = | 0.261122 | / | 0.238854 |
| | = | 1.0932 |
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) |
| = | (204.576 / 421.88) | / | (196.426 / 371.769) |
| = | 0.484915 | / | 0.528355 |
| | = | 0.9178 |
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) |
| = | ((364.573 + 81.717) / 1162.791) | / | ((366.598 + 61.814) / 1078.857) |
| = | 0.383809 | / | 0.397098 |
| | = | 0.9665 |
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 |
| = | (23.412 - 4.259 | - | 90.089) | / | 1162.791 |
| | = | -0.061005 |
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.
N-able has a M-score of -2.64 suggests that the company is unlikely to be a manipulator.
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