BILL Holdings Beneish M-Score Historical Data
The historical data trend for BILL Holdings'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.
BILL Holdings Beneish M-Score Chart
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BILL Holdings Annual Data
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Jun18 |
Jun19 |
Jun20 |
Jun21 |
Jun22 |
Jun23 |
| Beneish M-Score |
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- |
-2.22 |
40.20 |
-1.65 |
-2.08 |
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BILL Holdings Quarterly Data
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Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
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Dec20 |
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Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-1.95 |
-1.99 |
-2.08 |
-2.25 |
-2.34 |
Competitive Comparison of BILL Holdings's Beneish M-Score
For the Software - Application subindustry, BILL Holdings'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.
BILL Holdings's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, BILL Holdings's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where BILL Holdings's Beneish M-Score falls into.
BILL Holdings 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 BILL Holdings 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 * 0.9484 | + | 0.528 * 0.9741 | + | 0.404 * 0.9581 | + | 0.892 * 1.3908 | + | 0.115 * 0.9874 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.7823 | + | 4.679 * -0.034165 | - | 0.327 * 1.0339 |
| = | -2.34 |
* 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 $544 Mil.
Revenue was 318.495 + 304.985 + 295.983 + 272.555 = $1,192 Mil.
Gross Profit was 260.118 + 248.959 + 243.431 + 223.705 = $976 Mil.
Total Current Assets was $6,956 Mil.
Total Assets was $9,872 Mil.
Property, Plant and Equipment(Net PPE) was $150 Mil.
Depreciation, Depletion and Amortization(DDA) was $100 Mil.
Selling, General, & Admin. Expense(SGA) was $785 Mil.
Total Current Liabilities was $4,118 Mil.
Long-Term Debt & Capital Lease Obligation was $1,776 Mil.
Net Income was -40.421 + -27.861 + -15.871 + -31.138 = $-115 Mil.
Non Operating Income was -25.2 + -0.307 + -0.196 + -0.029 = $-26 Mil.
Cash Flow from Operations was 79.681 + 53.661 + 80.355 + 34.031 = $248 Mil.
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Total Receivables was $412 Mil.
Revenue was 260.006 + 229.924 + 200.221 + 166.911 = $857 Mil.
Gross Profit was 212.539 + 184.817 + 156.78 + 129.569 = $684 Mil.
Total Current Assets was $6,748 Mil.
Total Assets was $9,738 Mil.
Property, Plant and Equipment(Net PPE) was $142 Mil.
Depreciation, Depletion and Amortization(DDA) was $93 Mil.
Selling, General, & Admin. Expense(SGA) was $722 Mil.
Total Current Liabilities was $3,731 Mil.
Long-Term Debt & Capital Lease Obligation was $1,892 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) |
| = | (543.632 / 1192.018) | / | (412.156 / 857.062) |
| = | 0.45606 | / | 0.480894 |
| | = | 0.9484 |
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) |
| = | (683.705 / 857.062) | / | (976.213 / 1192.018) |
| = | 0.797731 | / | 0.818958 |
| | = | 0.9741 |
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 - (6956.047 + 150.082) / 9872.411) | / | (1 - (6748.188 + 142.108) / 9738.274) |
| = | 0.280203 | / | 0.292452 |
| | = | 0.9581 |
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 |
| = | 1192.018 | / | 857.062 |
| | = | 1.3908 |
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)) |
| = | (92.786 / (92.786 + 142.108)) | / | (100.073 / (100.073 + 150.082)) |
| = | 0.395012 | / | 0.400044 |
| | = | 0.9874 |
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) |
| = | (785.322 / 1192.018) | / | (721.755 / 857.062) |
| = | 0.658817 | / | 0.842127 |
| | = | 0.7823 |
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) |
| = | ((1775.933 + 4118.192) / 9872.411) | / | ((1892.174 + 3731.24) / 9738.274) |
| = | 0.59703 | / | 0.577455 |
| | = | 1.0339 |
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 |
| = | (-115.291 - -25.732 | - | 247.728) | / | 9872.411 |
| | = | -0.034165 |
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.
BILL Holdings has a M-score of -2.34 suggests that the company is unlikely to be a manipulator.
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