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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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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-2.69 |
-3.48 |
-3.51 |
-3.39 |
-3.03 |
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 * 0.9964 | + | 0.528 * 0.995 | + | 0.404 * 0.8281 | + | 0.892 * 1.0738 | + | 0.115 * 1.2247 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9564 | + | 4.679 * -0.104716 | - | 0.327 * 1.2549 |
| = | -3.03 |
* 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 $358 Mil.
Revenue was 677.2 + 677.6 + 675 + 651.6 = $2,681 Mil.
Gross Profit was 451 + 460.4 + 458.1 + 435.4 = $1,805 Mil.
Total Current Assets was $810 Mil.
Total Assets was $4,366 Mil.
Property, Plant and Equipment(Net PPE) was $797 Mil.
Depreciation, Depletion and Amortization(DDA) was $281 Mil.
Selling, General, & Admin. Expense(SGA) was $392 Mil.
Total Current Liabilities was $771 Mil.
Long-Term Debt & Capital Lease Obligation was $3,048 Mil.
Net Income was 173.8 + 187.4 + 196.9 + 56.4 = $615 Mil.
Non Operating Income was 20.3 + -2 + -6.2 + -1.1 = $11 Mil.
Cash Flow from Operations was 252.4 + 250.1 + 192.9 + 365.3 = $1,061 Mil.
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Total Receivables was $334 Mil.
Revenue was 630.5 + 610.1 + 612.8 + 643.6 = $2,497 Mil.
Gross Profit was 425.3 + 414.9 + 417.3 + 414.9 = $1,672 Mil.
Total Current Assets was $925 Mil.
Total Assets was $6,961 Mil.
Property, Plant and Equipment(Net PPE) was $724 Mil.
Depreciation, Depletion and Amortization(DDA) was $340 Mil.
Selling, General, & Admin. Expense(SGA) was $382 Mil.
Total Current Liabilities was $2,319 Mil.
Long-Term Debt & Capital Lease Obligation was $2,533 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) |
| = | (357.7 / 2681.4) | / | (334.3 / 2497) |
| = | 0.1334 | / | 0.133881 |
| | = | 0.9964 |
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) |
| = | (1672.4 / 2497) | / | (1804.9 / 2681.4) |
| = | 0.669764 | / | 0.673119 |
| | = | 0.995 |
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 - (810.1 + 796.6) / 4366.1) | / | (1 - (925.1 + 723.5) / 6961.1) |
| = | 0.632006 | / | 0.76317 |
| | = | 0.8281 |
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 |
| = | 2681.4 | / | 2497 |
| | = | 1.0738 |
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)) |
| = | (340 / (340 + 723.5)) | / | (281.4 / (281.4 + 796.6)) |
| = | 0.319699 | / | 0.261039 |
| | = | 1.2247 |
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) |
| = | (391.8 / 2681.4) | / | (381.5 / 2497) |
| = | 0.146118 | / | 0.152783 |
| | = | 0.9564 |
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) |
| = | ((3047.8 + 771.4) / 4366.1) | / | ((2533.1 + 2319.2) / 6961.1) |
| = | 0.874739 | / | 0.697059 |
| | = | 1.2549 |
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 |
| = | (614.5 - 11 | - | 1060.7) | / | 4366.1 |
| | = | -0.104716 |
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 -3.03 suggests that the company is unlikely to be a manipulator.
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