Paycor HCM Beneish M-Score Historical Data
The historical data trend for Paycor HCM'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.
Paycor HCM Beneish M-Score Chart
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Paycor HCM Annual Data
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Trend |
Jun19 |
Jun20 |
Jun21 |
Jun22 |
Jun23 |
| Beneish M-Score |
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- |
- |
- |
-2.82 |
-2.21 |
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Paycor HCM Quarterly Data
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Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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-2.15 |
-2.21 |
-2.38 |
-2.45 |
-2.39 |
Competitive Comparison of Paycor HCM's Beneish M-Score
For the Software - Application subindustry, Paycor HCM'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.
Paycor HCM's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, Paycor HCM's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Paycor HCM's Beneish M-Score falls into.
Paycor HCM 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 Paycor HCM 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 * 1.1982 | + | 0.528 * 0.9957 | + | 0.404 * 0.9129 | + | 0.892 * 1.2035 | + | 0.115 * 0.9796 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9054 | + | 4.679 * -0.049521 | - | 0.327 * 1.0576 |
| = | -2.39 |
* 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 $44.0 Mil.
Revenue was 187.019 + 159.541 + 143.588 + 140.043 = $630.2 Mil.
Gross Profit was 128.283 + 104.416 + 92.21 + 91.595 = $416.5 Mil.
Total Current Assets was $1,644.2 Mil.
Total Assets was $2,905.3 Mil.
Property, Plant and Equipment(Net PPE) was $50.7 Mil.
Depreciation, Depletion and Amortization(DDA) was $141.2 Mil.
Selling, General, & Admin. Expense(SGA) was $430.1 Mil.
Total Current Liabilities was $1,516.0 Mil.
Long-Term Debt & Capital Lease Obligation was $14.0 Mil.
Net Income was 6.193 + -26.249 + -20.596 + -29.36 = $-70.0 Mil.
Non Operating Income was 1.133 + -1.745 + 0.931 + 2.116 = $2.4 Mil.
Cash Flow from Operations was 39.663 + 26.166 + -26.129 + 31.73 = $71.4 Mil.
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Total Receivables was $30.5 Mil.
Revenue was 161.482 + 132.864 + 118.303 + 110.991 = $523.6 Mil.
Gross Profit was 112.159 + 86.68 + 75.118 + 70.653 = $344.6 Mil.
Total Current Assets was $1,442.4 Mil.
Total Assets was $2,743.0 Mil.
Property, Plant and Equipment(Net PPE) was $48.9 Mil.
Depreciation, Depletion and Amortization(DDA) was $126.1 Mil.
Selling, General, & Admin. Expense(SGA) was $394.8 Mil.
Total Current Liabilities was $1,349.2 Mil.
Long-Term Debt & Capital Lease Obligation was $16.6 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) |
| = | (43.989 / 630.191) | / | (30.506 / 523.64) |
| = | 0.069803 | / | 0.058258 |
| | = | 1.1982 |
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) |
| = | (344.61 / 523.64) | / | (416.504 / 630.191) |
| = | 0.658105 | / | 0.660917 |
| | = | 0.9957 |
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 - (1644.233 + 50.748) / 2905.349) | / | (1 - (1442.384 + 48.904) / 2742.998) |
| = | 0.4166 | / | 0.456329 |
| | = | 0.9129 |
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 |
| = | 630.191 | / | 523.64 |
| | = | 1.2035 |
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)) |
| = | (126.102 / (126.102 + 48.904)) | / | (141.185 / (141.185 + 50.748)) |
| = | 0.720558 | / | 0.735595 |
| | = | 0.9796 |
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) |
| = | (430.145 / 630.191) | / | (394.771 / 523.64) |
| = | 0.682563 | / | 0.753898 |
| | = | 0.9054 |
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) |
| = | ((14.009 + 1516.023) / 2905.349) | / | ((16.644 + 1349.237) / 2742.998) |
| = | 0.526626 | / | 0.497952 |
| | = | 1.0576 |
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 |
| = | (-70.012 - 2.435 | - | 71.43) | / | 2905.349 |
| | = | -0.049521 |
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.
Paycor HCM has a M-score of -2.39 suggests that the company is unlikely to be a manipulator.
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