Protean eGov Technologies Beneish M-Score Historical Data
The historical data trend for Protean eGov Technologies'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.
Protean eGov Technologies Beneish M-Score Chart
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Protean eGov Technologies Annual Data
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|
Trend |
Mar21 |
Mar22 |
Mar23 |
Mar24 |
| Beneish M-Score |
|
- |
- |
-2.12 |
-2.22 |
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Protean eGov Technologies Semi-Annual Data
|
|
Mar21 |
Mar22 |
Mar23 |
Mar24 |
| Beneish M-Score |
- |
- |
-2.12 |
-2.22 |
Competitive Comparison of Protean eGov Technologies's Beneish M-Score
For the Information Technology Services subindustry, Protean eGov Technologies'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.
Protean eGov Technologies's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, Protean eGov Technologies's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Protean eGov Technologies's Beneish M-Score falls into.
Protean eGov Technologies 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 Protean eGov Technologies 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 * 0.6828 | + | 0.528 * 1.1115 | + | 0.404 * 0.9995 | + | 0.892 * 1.1884 | + | 0.115 * 0.7901 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0 | + | 4.679 * 0.033538 | - | 0.327 * 0.9485 |
| = | -2.22 |
* 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 ₹1,893 Mil.
Revenue was ₹8,820 Mil.
Gross Profit was ₹2,182 Mil.
Total Current Assets was ₹4,368 Mil.
Total Assets was ₹11,852 Mil.
Property, Plant and Equipment(Net PPE) was ₹651 Mil.
Depreciation, Depletion and Amortization(DDA) was ₹275 Mil.
Selling, General, & Admin. Expense(SGA) was ₹0 Mil.
Total Current Liabilities was ₹2,238 Mil.
Long-Term Debt & Capital Lease Obligation was ₹122 Mil.
Net Income was ₹973 Mil.
Gross Profit was ₹0 Mil.
Cash Flow from Operations was ₹575 Mil.
|
Total Receivables was ₹2,333 Mil.
Revenue was ₹7,422 Mil.
Gross Profit was ₹2,040 Mil.
Total Current Assets was ₹4,076 Mil.
Total Assets was ₹11,041 Mil.
Property, Plant and Equipment(Net PPE) was ₹597 Mil.
Depreciation, Depletion and Amortization(DDA) was ₹183 Mil.
Selling, General, & Admin. Expense(SGA) was ₹293 Mil.
Total Current Liabilities was ₹2,278 Mil.
Long-Term Debt & Capital Lease Obligation was ₹40 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) |
| = | (1892.9 / 8820.4) | / | (2332.68 / 7422) |
| = | 0.214605 | / | 0.314293 |
| | = | 0.6828 |
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) |
| = | (2040.4 / 7422) | / | (2181.5 / 8820.4) |
| = | 0.274912 | / | 0.247324 |
| | = | 1.1115 |
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 - (4367.9 + 651.3) / 11852.4) | / | (1 - (4075.55 + 596.95) / 11041.02) |
| = | 0.576525 | / | 0.576805 |
| | = | 0.9995 |
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 |
| = | 8820.4 | / | 7422 |
| | = | 1.1884 |
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)) |
| = | (182.8 / (182.8 + 596.95)) | / | (274.8 / (274.8 + 651.3)) |
| = | 0.234434 | / | 0.296728 |
| | = | 0.7901 |
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) |
| = | (0 / 8820.4) | / | (293.49 / 7422) |
| = | 0 | / | 0.039543 |
| | = | 0 |
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) |
| = | ((121.5 + 2237.8) / 11852.4) | / | ((39.51 + 2277.7) / 11041.02) |
| = | 0.199057 | / | 0.209873 |
| | = | 0.9485 |
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 |
| = | (972.9 - 0 | - | 575.4) | / | 11852.4 |
| | = | 0.033538 |
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.
Protean eGov Technologies has a M-score of -2.22 suggests that the company is unlikely to be a manipulator.
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