Verisk Analytics Beneish M-Score Historical Data
The historical data trend for Verisk Analytics'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.
Verisk Analytics Beneish M-Score Chart
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Verisk Analytics Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.73 |
-2.62 |
-2.98 |
-2.69 |
-3.03 |
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Verisk Analytics Quarterly Data
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Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
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Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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-3.48 |
-3.51 |
-3.39 |
-3.03 |
-2.62 |
Competitive Comparison of Verisk Analytics's Beneish M-Score
For the Consulting Services subindustry, Verisk Analytics'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.
Verisk Analytics's Beneish M-Score Distribution in the Business Services Industry
For the Business Services industry and Industrials sector, Verisk Analytics's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Verisk Analytics's Beneish M-Score falls into.
Verisk Analytics 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 Verisk Analytics 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 * 1.0971 | + | 0.528 * 1.001 | + | 0.404 * 0.9477 | + | 0.892 * 1.0913 | + | 0.115 * 1.0671 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0543 | + | 4.679 * -0.066398 | - | 0.327 * 0.9445 |
| = | -2.62 |
* 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 (Mar24) TTM: | Last Year (Mar23) TTM: |
Total Receivables was $519 Mil.
Revenue was 704 + 677.2 + 677.6 + 675 = $2,734 Mil.
Gross Profit was 476.2 + 451 + 460.4 + 458.1 = $1,846 Mil.
Total Current Assets was $1,017 Mil.
Total Assets was $4,499 Mil.
Property, Plant and Equipment(Net PPE) was $800 Mil.
Depreciation, Depletion and Amortization(DDA) was $295 Mil.
Selling, General, & Admin. Expense(SGA) was $406 Mil.
Total Current Liabilities was $930 Mil.
Long-Term Debt & Capital Lease Obligation was $3,057 Mil.
Net Income was 219.6 + 173.8 + 187.4 + 196.9 = $778 Mil.
Non Operating Income was -3.3 + 20.3 + -2 + -6.2 = $9 Mil.
Cash Flow from Operations was 372.2 + 252.4 + 250.1 + 192.9 = $1,068 Mil.
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Total Receivables was $433 Mil.
Revenue was 651.6 + 630.5 + 610.1 + 612.8 = $2,505 Mil.
Gross Profit was 435.4 + 425.3 + 414.9 + 417.3 = $1,693 Mil.
Total Current Assets was $791 Mil.
Total Assets was $4,190 Mil.
Property, Plant and Equipment(Net PPE) was $764 Mil.
Depreciation, Depletion and Amortization(DDA) was $308 Mil.
Selling, General, & Admin. Expense(SGA) was $353 Mil.
Total Current Liabilities was $890 Mil.
Long-Term Debt & Capital Lease Obligation was $3,042 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) |
| = | (518.8 / 2733.8) | / | (433.3 / 2505) |
| = | 0.189772 | / | 0.172974 |
| | = | 1.0971 |
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) |
| = | (1692.9 / 2505) | / | (1845.7 / 2733.8) |
| = | 0.675808 | / | 0.675141 |
| | = | 1.001 |
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 - (1017 + 800) / 4498.6) | / | (1 - (790.8 + 763.6) / 4190) |
| = | 0.596097 | / | 0.629021 |
| | = | 0.9477 |
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 |
| = | 2733.8 | / | 2505 |
| | = | 1.0913 |
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)) |
| = | (308.1 / (308.1 + 763.6)) | / | (295 / (295 + 800)) |
| = | 0.287487 | / | 0.269406 |
| | = | 1.0671 |
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) |
| = | (405.7 / 2733.8) | / | (352.6 / 2505) |
| = | 0.148401 | / | 0.140758 |
| | = | 1.0543 |
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) |
| = | ((3057.4 + 929.8) / 4498.6) | / | ((3041.9 + 890.1) / 4190) |
| = | 0.88632 | / | 0.938425 |
| | = | 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 |
| = | (777.7 - 8.8 | - | 1067.6) | / | 4498.6 |
| | = | -0.066398 |
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.
Verisk Analytics has a M-score of -2.62 suggests that the company is unlikely to be a manipulator.
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