Mastercard Beneish M-Score Historical Data
The historical data trend for Mastercard'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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Mastercard Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.26 |
-2.76 |
-2.72 |
-2.41 |
-2.36 |
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Mastercard Quarterly Data
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Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-2.41 |
-2.65 |
-2.66 |
-2.22 |
-2.36 |
Competitive Comparison
For the Credit Services subindustry, Mastercard'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.
Mastercard Beneish M-Score Distribution
For the Credit Services industry and Financial Services sector, Mastercard's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Mastercard's Beneish M-Score falls into.
Mastercard 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 Mastercard 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 * 1.0503 | + | 0.528 * 1.0043 | + | 0.404 * 0.9719 | + | 0.892 * 1.1287 | + | 0.115 * 0.9741 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9227 | + | 4.679 * -0.008693 | - | 0.327 * 1.0001 |
| = | -2.36 |
* 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 $4,060 Mil.
Revenue was 6548 + 6533 + 6269 + 5748 = $25,098 Mil.
Gross Profit was 5020 + 4960 + 4774 + 4322 = $19,076 Mil.
Total Current Assets was $18,961 Mil.
Total Assets was $42,448 Mil.
Property, Plant and Equipment(Net PPE) was $2,061 Mil.
Depreciation, Depletion and Amortization(DDA) was $799 Mil.
Selling, General, & Admin. Expense(SGA) was $3,647 Mil.
Total Current Liabilities was $16,264 Mil.
Long-Term Debt & Capital Lease Obligation was $14,344 Mil.
Net Income was 2791 + 3198 + 2845 + 2361 = $11,195 Mil.
Non Operating Income was -229 + 43 + 148 + -378 = $-416 Mil.
Cash Flow from Operations was 4130 + 3233 + 2698 + 1919 = $11,980 Mil.
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Total Receivables was $3,425 Mil.
Revenue was 5817 + 5756 + 5497 + 5167 = $22,237 Mil.
Gross Profit was 4436 + 4374 + 4178 + 3986 = $16,974 Mil.
Total Current Assets was $16,606 Mil.
Total Assets was $38,724 Mil.
Property, Plant and Equipment(Net PPE) was $2,006 Mil.
Depreciation, Depletion and Amortization(DDA) was $750 Mil.
Selling, General, & Admin. Expense(SGA) was $3,502 Mil.
Total Current Liabilities was $14,171 Mil.
Long-Term Debt & Capital Lease Obligation was $13,749 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) |
| = | (4060 / 25098) | / | (3425 / 22237) |
| = | 0.161766 | / | 0.154023 |
| | = | 1.0503 |
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) |
| = | (16974 / 22237) | / | (19076 / 25098) |
| = | 0.763322 | / | 0.760061 |
| | = | 1.0043 |
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 - (18961 + 2061) / 42448) | / | (1 - (16606 + 2006) / 38724) |
| = | 0.504759 | / | 0.519368 |
| | = | 0.9719 |
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 |
| = | 25098 | / | 22237 |
| | = | 1.1287 |
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)) |
| = | (750 / (750 + 2006)) | / | (799 / (799 + 2061)) |
| = | 0.272134 | / | 0.279371 |
| | = | 0.9741 |
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) |
| = | (3647 / 25098) | / | (3502 / 22237) |
| = | 0.14531 | / | 0.157485 |
| | = | 0.9227 |
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) |
| = | ((14344 + 16264) / 42448) | / | ((13749 + 14171) / 38724) |
| = | 0.72107 | / | 0.721 |
| | = | 1.0001 |
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 |
| = | (11195 - -416 | - | 11980) | / | 42448 |
| | = | -0.008693 |
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.
Mastercard has a M-score of -2.36 suggests that the company is unlikely to be a manipulator.
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