Kyndryl Holdings Beneish M-Score Historical Data
The historical data trend for Kyndryl 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.
Kyndryl Holdings Beneish M-Score Chart
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Kyndryl Holdings Annual Data
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Trend |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Mar23 |
| Beneish M-Score |
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- |
- |
- |
-2.63 |
-3.67 |
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Kyndryl Holdings Quarterly Data
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Dec18 |
Dec19 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-3.52 |
-3.67 |
-3.44 |
-2.97 |
-3.03 |
Competitive Comparison of Kyndryl Holdings's Beneish M-Score
For the Information Technology Services subindustry, Kyndryl 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.
Kyndryl Holdings's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, Kyndryl Holdings's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Kyndryl Holdings's Beneish M-Score falls into.
Kyndryl 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 Kyndryl 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 * 1.126 | + | 0.528 * 0.8542 | + | 0.404 * 0.8612 | + | 0.892 * 0.9567 | + | 0.115 * 1.0106 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.053 | + | 4.679 * -0.097548 | - | 0.327 * 1.0788 |
| = | -3.03 |
* 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 $1,658 Mil.
Revenue was 3936 + 4073 + 4193 + 4255 = $16,457 Mil.
Gross Profit was 752 + 651 + 744 + 643 = $2,790 Mil.
Total Current Assets was $4,851 Mil.
Total Assets was $10,969 Mil.
Property, Plant and Equipment(Net PPE) was $3,721 Mil.
Depreciation, Depletion and Amortization(DDA) was $1,285 Mil.
Selling, General, & Admin. Expense(SGA) was $2,842 Mil.
Total Current Liabilities was $5,152 Mil.
Long-Term Debt & Capital Lease Obligation was $3,329 Mil.
Net Income was -12 + -142 + -141 + -737 = $-1,032 Mil.
Non Operating Income was 37 + -95 + -105 + -120 = $-283 Mil.
Cash Flow from Operations was 436 + 46 + -173 + 12 = $321 Mil.
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Total Receivables was $1,539 Mil.
Revenue was 4303 + 4179 + 4288 + 4431 = $17,201 Mil.
Gross Profit was 707 + 566 + 611 + 607 = $2,491 Mil.
Total Current Assets was $4,967 Mil.
Total Assets was $11,851 Mil.
Property, Plant and Equipment(Net PPE) was $3,877 Mil.
Depreciation, Depletion and Amortization(DDA) was $1,358 Mil.
Selling, General, & Admin. Expense(SGA) was $2,821 Mil.
Total Current Liabilities was $4,607 Mil.
Long-Term Debt & Capital Lease Obligation was $3,887 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) |
| = | (1658 / 16457) | / | (1539 / 17201) |
| = | 0.100747 | / | 0.089472 |
| | = | 1.126 |
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) |
| = | (2491 / 17201) | / | (2790 / 16457) |
| = | 0.144817 | / | 0.169533 |
| | = | 0.8542 |
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 - (4851 + 3721) / 10969) | / | (1 - (4967 + 3877) / 11851) |
| = | 0.218525 | / | 0.253734 |
| | = | 0.8612 |
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 |
| = | 16457 | / | 17201 |
| | = | 0.9567 |
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)) |
| = | (1358 / (1358 + 3877)) | / | (1285 / (1285 + 3721)) |
| = | 0.259408 | / | 0.256692 |
| | = | 1.0106 |
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) |
| = | (2842 / 16457) | / | (2821 / 17201) |
| = | 0.172692 | / | 0.164002 |
| | = | 1.053 |
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) |
| = | ((3329 + 5152) / 10969) | / | ((3887 + 4607) / 11851) |
| = | 0.773179 | / | 0.716733 |
| | = | 1.0788 |
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 |
| = | (-1032 - -283 | - | 321) | / | 10969 |
| | = | -0.097548 |
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.
Kyndryl Holdings has a M-score of -3.03 suggests that the company is unlikely to be a manipulator.
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