Visa Beneish M-Score Historical Data
The historical data trend for Visa'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.
Visa Beneish M-Score Chart
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Visa Annual Data
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Trend |
Sep15 |
Sep16 |
Sep17 |
Sep18 |
Sep19 |
Sep20 |
Sep21 |
Sep22 |
Sep23 |
Sep24 |
| Beneish M-Score |
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-2.86 |
-2.42 |
-2.61 |
-2.53 |
-2.06 |
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Visa Quarterly Data
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Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
| Beneish M-Score |
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-2.53 |
-2.46 |
-2.27 |
-2.58 |
-2.06 |
Competitive Comparison of Visa's Beneish M-Score
For the Credit Services subindustry, Visa'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.
Visa's Beneish M-Score Distribution in the Credit Services Industry
For the Credit Services industry and Financial Services sector, Visa's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Visa's Beneish M-Score falls into.
Visa 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 Visa 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 * 1.4251 | + | 0.528 * 0.9937 | + | 0.404 * 1.0132 | + | 0.892 * 1.1002 | + | 0.115 * 1.0143 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.072 | + | 4.679 * -0.007481 | - | 0.327 * 1.0409 |
| = | -2.06 |
* 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 (Sep24) TTM: | Last Year (Sep23) TTM: |
Total Receivables was $7,015 Mil.
Revenue was 9617 + 8900 + 8775 + 8634 = $35,926 Mil.
Gross Profit was 7800 + 7127 + 6983 + 6974 = $28,884 Mil.
Total Current Assets was $34,033 Mil.
Total Assets was $94,511 Mil.
Property, Plant and Equipment(Net PPE) was $3,824 Mil.
Depreciation, Depletion and Amortization(DDA) was $1,034 Mil.
Selling, General, & Admin. Expense(SGA) was $3,793 Mil.
Total Current Liabilities was $26,517 Mil.
Long-Term Debt & Capital Lease Obligation was $20,836 Mil.
Net Income was 5318 + 4872 + 4663 + 4890 = $19,743 Mil.
Non Operating Income was 189 + 234 + -189 + 266 = $500 Mil.
Cash Flow from Operations was 6664 + 5134 + 4538 + 3614 = $19,950 Mil.
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Total Receivables was $4,474 Mil.
Revenue was 8609 + 8123 + 7985 + 7936 = $32,653 Mil.
Gross Profit was 6914 + 6460 + 6291 + 6421 = $26,086 Mil.
Total Current Assets was $33,532 Mil.
Total Assets was $90,499 Mil.
Property, Plant and Equipment(Net PPE) was $3,425 Mil.
Depreciation, Depletion and Amortization(DDA) was $943 Mil.
Selling, General, & Admin. Expense(SGA) was $3,216 Mil.
Total Current Liabilities was $23,098 Mil.
Long-Term Debt & Capital Lease Obligation was $20,463 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) |
| = | (7015 / 35926) | / | (4474 / 32653) |
| = | 0.195262 | / | 0.137017 |
| | = | 1.4251 |
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) |
| = | (26086 / 32653) | / | (28884 / 35926) |
| = | 0.798885 | / | 0.803986 |
| | = | 0.9937 |
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 - (34033 + 3824) / 94511) | / | (1 - (33532 + 3425) / 90499) |
| = | 0.599443 | / | 0.591631 |
| | = | 1.0132 |
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 |
| = | 35926 | / | 32653 |
| | = | 1.1002 |
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)) |
| = | (943 / (943 + 3425)) | / | (1034 / (1034 + 3824)) |
| = | 0.215888 | / | 0.212845 |
| | = | 1.0143 |
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) |
| = | (3793 / 35926) | / | (3216 / 32653) |
| = | 0.105578 | / | 0.09849 |
| | = | 1.072 |
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) |
| = | ((20836 + 26517) / 94511) | / | ((20463 + 23098) / 90499) |
| = | 0.501032 | / | 0.481342 |
| | = | 1.0409 |
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 |
| = | (19743 - 500 | - | 19950) | / | 94511 |
| | = | -0.007481 |
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.
Visa has a M-score of -2.06 suggests that the company is unlikely to be a manipulator.
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