Willis Towers Watson Beneish M-Score Historical Data
The historical data trend for Willis Towers Watson'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.
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Willis Towers Watson Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.37 |
-2.72 |
-2.36 |
-2.48 |
-2.28 |
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Willis Towers Watson 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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-2.48 |
-2.47 |
-2.50 |
-2.25 |
-2.28 |
Competitive Comparison
For the Insurance Brokers subindustry, Willis Towers Watson'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.
Willis Towers Watson Beneish M-Score Distribution
For the Insurance industry and Financial Services sector, Willis Towers Watson's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Willis Towers Watson's Beneish M-Score falls into.
Willis Towers Watson 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 Willis Towers Watson 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 * 0.9957 | + | 0.528 * 0.9822 | + | 0.404 * 1.0728 | + | 0.892 * 1.0696 | + | 0.115 * 1.0742 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.3796 | + | 4.679 * -0.000447 | - | 0.327 * 0.9775 |
| = | -2.28 |
* 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 $2,787 Mil.
Revenue was 2914 + 2166 + 2159 + 2244 = $9,483 Mil.
Gross Profit was 1589 + 807 + 812 + 931 = $4,139 Mil.
Total Current Assets was $13,433 Mil.
Total Assets was $29,090 Mil.
Property, Plant and Equipment(Net PPE) was $1,285 Mil.
Depreciation, Depletion and Amortization(DDA) was $505 Mil.
Selling, General, & Admin. Expense(SGA) was $-54 Mil.
Total Current Liabilities was $12,630 Mil.
Long-Term Debt & Capital Lease Obligation was $5,166 Mil.
Net Income was 622 + 136 + 94 + 203 = $1,055 Mil.
Non Operating Income was -54 + -93 + -93 + -37 = $-277 Mil.
Cash Flow from Operations was 522 + 393 + 296 + 134 = $1,345 Mil.
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Total Receivables was $2,617 Mil.
Revenue was 2722 + 1953 + 2031 + 2160 = $8,866 Mil.
Gross Profit was 1459 + 728 + 772 + 842 = $3,801 Mil.
Total Current Assets was $15,835 Mil.
Total Assets was $31,769 Mil.
Property, Plant and Equipment(Net PPE) was $1,304 Mil.
Depreciation, Depletion and Amortization(DDA) was $567 Mil.
Selling, General, & Admin. Expense(SGA) was $-133 Mil.
Total Current Liabilities was $14,779 Mil.
Long-Term Debt & Capital Lease Obligation was $5,103 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) |
| = | (2787 / 9483) | / | (2617 / 8866) |
| = | 0.293894 | / | 0.295173 |
| | = | 0.9957 |
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) |
| = | (3801 / 8866) | / | (4139 / 9483) |
| = | 0.428716 | / | 0.436465 |
| | = | 0.9822 |
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 - (13433 + 1285) / 29090) | / | (1 - (15835 + 1304) / 31769) |
| = | 0.494053 | / | 0.460512 |
| | = | 1.0728 |
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 |
| = | 9483 | / | 8866 |
| | = | 1.0696 |
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)) |
| = | (567 / (567 + 1304)) | / | (505 / (505 + 1285)) |
| = | 0.303046 | / | 0.282123 |
| | = | 1.0742 |
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) |
| = | (-54 / 9483) | / | (-133 / 8866) |
| = | -0.005694 | / | -0.015001 |
| | = | 0.3796 |
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) |
| = | ((5166 + 12630) / 29090) | / | ((5103 + 14779) / 31769) |
| = | 0.611757 | / | 0.62583 |
| | = | 0.9775 |
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 |
| = | (1055 - -277 | - | 1345) | / | 29090 |
| | = | -0.000447 |
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.
Willis Towers Watson has a M-score of -2.28 suggests that the company is unlikely to be a manipulator.
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