Wipro Beneish M-Score Historical Data
The historical data trend for Wipro'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.
Wipro Beneish M-Score Chart
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Wipro Annual Data
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Trend |
Mar15 |
Mar16 |
Mar17 |
Mar18 |
Mar19 |
Mar20 |
Mar21 |
Mar22 |
Mar23 |
Mar24 |
| Beneish M-Score |
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-2.37 |
-2.88 |
-2.04 |
-2.40 |
-2.37 |
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Wipro Quarterly Data
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Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
Dec24 |
| Beneish M-Score |
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-2.55 |
-2.37 |
-2.26 |
-2.32 |
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Competitive Comparison of Wipro's Beneish M-Score
For the Information Technology Services subindustry, Wipro'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.
Wipro's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, Wipro's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Wipro's Beneish M-Score falls into.
Wipro 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 Wipro 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 * | + | 0.528 * | + | 0.404 * | + | 0.892 * | + | 0.115 * |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * | + | 4.679 * | - | 0.327 * |
| = | |
* 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 (Dec24) TTM: | Last Year (Dec23) TTM: |
Total Receivables was ₹206,931 Mil.
Revenue was 223188 + 223016 + 219638 + 222083 = ₹887,925 Mil.
Gross Profit was 69266 + 67967 + 66332 + 64864 = ₹268,429 Mil.
Total Current Assets was ₹794,718 Mil.
Total Assets was ₹1,302,019 Mil.
Property, Plant and Equipment(Net PPE) was ₹99,646 Mil.
Depreciation, Depletion and Amortization(DDA) was ₹15,597 Mil.
Selling, General, & Admin. Expense(SGA) was ₹109,960 Mil.
Total Current Liabilities was ₹280,875 Mil.
Long-Term Debt & Capital Lease Obligation was ₹82,817 Mil.
Net Income was 33538 + 32088 + 30032 + 28346 = ₹124,004 Mil.
Non Operating Income was 2645 + 2226 + 1602 + 3117 = ₹9,590 Mil.
Cash Flow from Operations was 0 + 42689 + 39959 + 0 = ₹82,648 Mil.
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Total Receivables was ₹0 Mil.
Revenue was 222051 + 225159 + 228310 + 231903 = ₹907,423 Mil.
Gross Profit was 68225 + 65968 + 67049 + 69165 = ₹270,407 Mil.
Total Current Assets was ₹0 Mil.
Total Assets was ₹0 Mil.
Property, Plant and Equipment(Net PPE) was ₹0 Mil.
Depreciation, Depletion and Amortization(DDA) was ₹24,816 Mil.
Selling, General, & Admin. Expense(SGA) was ₹124,102 Mil.
Total Current Liabilities was ₹0 Mil.
Long-Term Debt & Capital Lease Obligation was ₹0 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) |
| = | (206931 / 887925) | / | (0 / 907423) |
| = | 0.23305 | / | 0 |
| | = | |
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) |
| = | (270407 / 907423) | / | (268429 / 887925) |
| = | 0.297994 | / | 0.30231 |
| | = | |
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 - (794718 + 99646) / 1302019) | / | (1 - (0 + 0) / 0) |
| = | 0.313095 | / | |
| | = | |
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 |
| = | 887925 | / | 907423 |
| | = | |
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)) |
| = | (24816 / (24816 + 0)) | / | (15597 / (15597 + 99646)) |
| = | 1 | / | 0.13534 |
| | = | |
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) |
| = | (109960 / 887925) | / | (124102 / 907423) |
| = | 0.123839 | / | 0.136763 |
| | = | |
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) |
| = | ((82817 + 280875) / 1302019) | / | ((0 + 0) / 0) |
| = | 0.279329 | / | |
| | = | |
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 |
| = | (124004 - 9590 | - | 82648) | / | 1302019 |
| | = | 0.024397 |
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.
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