Accenture Beneish M-Score Historical Data
The historical data trend for Accenture'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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Accenture Annual Data
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Trend |
Aug14 |
Aug15 |
Aug16 |
Aug17 |
Aug18 |
Aug19 |
Aug20 |
Aug21 |
Aug22 |
Aug23 |
| Beneish M-Score |
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-2.60 |
-2.97 |
-2.62 |
-2.48 |
-2.68 |
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Accenture Quarterly Data
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May19 |
Aug19 |
Nov19 |
Feb20 |
May20 |
Aug20 |
Nov20 |
Feb21 |
May21 |
Aug21 |
Nov21 |
Feb22 |
May22 |
Aug22 |
Nov22 |
Feb23 |
May23 |
Aug23 |
Nov23 |
Feb24 |
| Beneish M-Score |
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-2.60 |
-2.66 |
-2.68 |
-2.68 |
-2.60 |
Competitive Comparison
For the Information Technology Services subindustry, Accenture'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.
Accenture Beneish M-Score Distribution
For the Software industry and Technology sector, Accenture's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Accenture's Beneish M-Score falls into.
Accenture 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 Accenture 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 * 1.0233 | + | 0.528 * 0.9859 | + | 0.404 * 1.1265 | + | 0.892 * 1.0226 | + | 0.115 * 0.8911 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0194 | + | 4.679 * -0.046533 | - | 0.327 * 0.9132 |
| = | -2.60 |
* 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 (Feb24) TTM: | Last Year (Feb23) TTM: |
Total Receivables was $13,081 Mil.
Revenue was 15799.514 + 16224.303 + 15985.2 + 16564.585 = $64,574 Mil.
Gross Profit was 4878.469 + 5447.941 + 5181.629 + 5529.07 = $21,037 Mil.
Total Current Assets was $20,329 Mil.
Total Assets was $51,307 Mil.
Property, Plant and Equipment(Net PPE) was $4,094 Mil.
Depreciation, Depletion and Amortization(DDA) was $1,425 Mil.
Selling, General, & Admin. Expense(SGA) was $11,080 Mil.
Total Current Liabilities was $16,136 Mil.
Long-Term Debt & Capital Lease Obligation was $2,365 Mil.
Net Income was 1674.859 + 1973.444 + 1372.963 + 2009.996 = $7,031 Mil.
Non Operating Income was -5.652 + -35.719 + -40.017 + 201.783 = $120 Mil.
Cash Flow from Operations was 2101.043 + 498.551 + 3409.388 + 3289.371 = $9,298 Mil.
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Total Receivables was $12,499 Mil.
Revenue was 15814.158 + 15747.802 + 15423.656 + 16158.803 = $63,144 Mil.
Gross Profit was 4834.766 + 5186.142 + 4946.057 + 5314.734 = $20,282 Mil.
Total Current Assets was $21,061 Mil.
Total Assets was $47,727 Mil.
Property, Plant and Equipment(Net PPE) was $4,467 Mil.
Depreciation, Depletion and Amortization(DDA) was $1,335 Mil.
Selling, General, & Admin. Expense(SGA) was $10,628 Mil.
Total Current Liabilities was $16,350 Mil.
Long-Term Debt & Capital Lease Obligation was $2,497 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) |
| = | (13080.504 / 64573.602) | / | (12499.168 / 63144.419) |
| = | 0.202567 | / | 0.197946 |
| | = | 1.0233 |
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) |
| = | (20281.699 / 63144.419) | / | (21037.109 / 64573.602) |
| = | 0.321195 | / | 0.325785 |
| | = | 0.9859 |
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 - (20328.821 + 4093.874) / 51307.471) | / | (1 - (21060.958 + 4466.872) / 47727.289) |
| = | 0.523993 | / | 0.465131 |
| | = | 1.1265 |
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 |
| = | 64573.602 | / | 63144.419 |
| | = | 1.0226 |
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)) |
| = | (1334.835 / (1334.835 + 4466.872)) | / | (1424.937 / (1424.937 + 4093.874)) |
| = | 0.230076 | / | 0.258196 |
| | = | 0.8911 |
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) |
| = | (11079.758 / 64573.602) | / | (10628.321 / 63144.419) |
| = | 0.171583 | / | 0.168318 |
| | = | 1.0194 |
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) |
| = | ((2364.887 + 16136.014) / 51307.471) | / | ((2497.116 + 16349.522) / 47727.289) |
| = | 0.360589 | / | 0.394882 |
| | = | 0.9132 |
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 |
| = | (7031.262 - 120.395 | - | 9298.353) | / | 51307.471 |
| | = | -0.046533 |
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.
Accenture has a M-score of -2.60 suggests that the company is unlikely to be a manipulator.
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