SCSK Beneish M-Score Historical Data
The historical data trend for SCSK'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.
SCSK Beneish M-Score Chart
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SCSK Annual Data
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Trend |
Mar15 |
Mar16 |
Mar17 |
Mar18 |
Mar19 |
Mar20 |
Mar21 |
Mar22 |
Mar23 |
Mar24 |
| Beneish M-Score |
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-2.78 |
-2.65 |
-2.76 |
-2.39 |
-2.67 |
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SCSK Quarterly Data
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Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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-2.39 |
-2.42 |
-2.59 |
-2.59 |
-2.67 |
Competitive Comparison of SCSK's Beneish M-Score
For the Information Technology Services subindustry, SCSK'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.
SCSK's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, SCSK's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where SCSK's Beneish M-Score falls into.
SCSK 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 SCSK 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 * 0.9586 | + | 0.528 * 0.9905 | + | 0.404 * 1.1111 | + | 0.892 * 1.0771 | + | 0.115 * 0.9198 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9905 | + | 4.679 * -0.058207 | - | 0.327 * 0.9533 |
| = | -2.67 |
* 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 円100,491 Mil.
Revenue was 128944 + 120167 + 117824 + 113371 = 円480,306 Mil.
Gross Profit was 35264 + 31483 + 31404 + 29819 = 円127,970 Mil.
Total Current Assets was 円272,834 Mil.
Total Assets was 円471,400 Mil.
Property, Plant and Equipment(Net PPE) was 円113,915 Mil.
Depreciation, Depletion and Amortization(DDA) was 円21,433 Mil.
Selling, General, & Admin. Expense(SGA) was 円70,939 Mil.
Total Current Liabilities was 円105,535 Mil.
Long-Term Debt & Capital Lease Obligation was 円52,940 Mil.
Net Income was 12126 + 9867 + 9461 + 9007 = 円40,461 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = 円0 Mil.
Cash Flow from Operations was 20214 + 9631 + 14451 + 23604 = 円67,900 Mil.
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Total Receivables was 円97,320 Mil.
Revenue was 122888 + 109924 + 108682 + 104417 = 円445,911 Mil.
Gross Profit was 33441 + 29013 + 29235 + 25989 = 円117,678 Mil.
Total Current Assets was 円244,099 Mil.
Total Assets was 円435,469 Mil.
Property, Plant and Equipment(Net PPE) was 円120,993 Mil.
Depreciation, Depletion and Amortization(DDA) was 円20,629 Mil.
Selling, General, & Admin. Expense(SGA) was 円66,490 Mil.
Total Current Liabilities was 円108,367 Mil.
Long-Term Debt & Capital Lease Obligation was 円45,197 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) |
| = | (100491 / 480306) | / | (97320 / 445911) |
| = | 0.209223 | / | 0.21825 |
| | = | 0.9586 |
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) |
| = | (117678 / 445911) | / | (127970 / 480306) |
| = | 0.263905 | / | 0.266434 |
| | = | 0.9905 |
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 - (272834 + 113915) / 471400) | / | (1 - (244099 + 120993) / 435469) |
| = | 0.179574 | / | 0.161612 |
| | = | 1.1111 |
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 |
| = | 480306 | / | 445911 |
| | = | 1.0771 |
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)) |
| = | (20629 / (20629 + 120993)) | / | (21433 / (21433 + 113915)) |
| = | 0.145662 | / | 0.158355 |
| | = | 0.9198 |
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) |
| = | (70939 / 480306) | / | (66490 / 445911) |
| = | 0.147695 | / | 0.14911 |
| | = | 0.9905 |
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) |
| = | ((52940 + 105535) / 471400) | / | ((45197 + 108367) / 435469) |
| = | 0.336179 | / | 0.35264 |
| | = | 0.9533 |
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 |
| = | (40461 - 0 | - | 67900) | / | 471400 |
| | = | -0.058207 |
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.
SCSK has a M-score of -2.67 suggests that the company is unlikely to be a manipulator.
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