Unisys Beneish M-Score Historical Data
The historical data trend for Unisys'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.
Unisys Beneish M-Score Chart
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Unisys Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.57 |
0.60 |
-2.54 |
-2.75 |
-2.74 |
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Unisys Quarterly Data
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Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
| Beneish M-Score |
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-3.43 |
-2.74 |
-2.73 |
-2.42 |
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Competitive Comparison of Unisys's Beneish M-Score
For the Information Technology Services subindustry, Unisys'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.
Unisys's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, Unisys's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Unisys's Beneish M-Score falls into.
Unisys 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 Unisys 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 * 1.1387 | + | 0.528 * 0.9483 | + | 0.404 * 0.8592 | + | 0.892 * 1.0029 | + | 0.115 * 1.2604 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.348 | + | 4.679 * 0.060002 | - | 0.327 * 1.0186 |
| = | -2.02 |
* 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 (Sep24) TTM: | Last Year (Sep23) TTM: |
Total Receivables was $460 Mil.
Revenue was 497 + 478.2 + 487.8 + 557.6 = $2,021 Mil.
Gross Profit was 145 + 129.9 + 136 + 181.2 = $592 Mil.
Total Current Assets was $947 Mil.
Total Assets was $1,862 Mil.
Property, Plant and Equipment(Net PPE) was $123 Mil.
Depreciation, Depletion and Amortization(DDA) was $113 Mil.
Selling, General, & Admin. Expense(SGA) was $222 Mil.
Total Current Liabilities was $585 Mil.
Long-Term Debt & Capital Lease Obligation was $518 Mil.
Net Income was -61.9 + -12 + -149.5 + -165.3 = $-389 Mil.
Non Operating Income was -47.3 + -9.4 + -142.1 + -383.1 = $-582 Mil.
Cash Flow from Operations was 32 + 2.7 + 23.8 + 23 = $82 Mil.
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Total Receivables was $403 Mil.
Revenue was 464.6 + 476.8 + 516.4 + 557 = $2,015 Mil.
Gross Profit was 95.3 + 115.8 + 159 + 189.8 = $560 Mil.
Total Current Assets was $892 Mil.
Total Assets was $1,971 Mil.
Property, Plant and Equipment(Net PPE) was $104 Mil.
Depreciation, Depletion and Amortization(DDA) was $158 Mil.
Selling, General, & Admin. Expense(SGA) was $635 Mil.
Total Current Liabilities was $640 Mil.
Long-Term Debt & Capital Lease Obligation was $507 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) |
| = | (460.2 / 2020.6) | / | (403 / 2014.8) |
| = | 0.227754 | / | 0.20002 |
| | = | 1.1387 |
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) |
| = | (559.9 / 2014.8) | / | (592.1 / 2020.6) |
| = | 0.277894 | / | 0.293032 |
| | = | 0.9483 |
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 - (947.1 + 122.7) / 1861.6) | / | (1 - (891.7 + 103.5) / 1970.9) |
| = | 0.425333 | / | 0.495053 |
| | = | 0.8592 |
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 |
| = | 2020.6 | / | 2014.8 |
| | = | 1.0029 |
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)) |
| = | (158.4 / (158.4 + 103.5)) | / | (113.2 / (113.2 + 122.7)) |
| = | 0.604811 | / | 0.479864 |
| | = | 1.2604 |
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) |
| = | (221.5 / 2020.6) | / | (634.7 / 2014.8) |
| = | 0.109621 | / | 0.315019 |
| | = | 0.348 |
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) |
| = | ((517.9 + 585.3) / 1861.6) | / | ((506.8 + 639.8) / 1970.9) |
| = | 0.592609 | / | 0.581765 |
| | = | 1.0186 |
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 |
| = | (-388.7 - -581.9 | - | 81.5) | / | 1861.6 |
| | = | 0.060002 |
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.
Unisys has a M-score of -2.02 suggests that the company is unlikely to be a manipulator.
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