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.
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Visa Annual Data
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Trend |
Sep14 |
Sep15 |
Sep16 |
Sep17 |
Sep18 |
Sep19 |
Sep20 |
Sep21 |
Sep22 |
Sep23 |
| Beneish M-Score |
Array
(
[0] => -
[1] => -
[2] => -
[3] => -
[4] => -
[5] => -2.01
[6] => -2.86
[7] => -2.42
[8] => -2.61
[9] => -2.53
)
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|
|
|
-2.01 |
-2.86 |
-2.42 |
-2.61 |
-2.53 |
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Visa 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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|
|
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|
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|
|
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|
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|
|
-2.55 |
-2.55 |
-2.43 |
-2.53 |
-2.46 |
Competitive Comparison
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 Beneish M-Score Distribution
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 * 1.074 | + | 0.528 * 1.0059 | + | 0.404 * 0.9498 | + | 0.892 * 1.1048 | + | 0.115 * 0.9934 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9168 | + | 4.679 * -0.027908 | - | 0.327 * 1.0161 |
| = | -2.46 |
* 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 $5,031 Mil.
Revenue was 8634 + 8609 + 8123 + 7985 = $33,351 Mil.
Gross Profit was 6974 + 6914 + 6460 + 6291 = $26,639 Mil.
Total Current Assets was $32,732 Mil.
Total Assets was $91,409 Mil.
Property, Plant and Equipment(Net PPE) was $3,472 Mil.
Depreciation, Depletion and Amortization(DDA) was $963 Mil.
Selling, General, & Admin. Expense(SGA) was $3,217 Mil.
Total Current Liabilities was $22,634 Mil.
Long-Term Debt & Capital Lease Obligation was $20,703 Mil.
Net Income was 4890 + 4681 + 4156 + 4257 = $17,984 Mil.
Non Operating Income was 266 + 140 + -153 + 84 = $337 Mil.
Cash Flow from Operations was 3614 + 6927 + 5797 + 3860 = $20,198 Mil.
|
Total Receivables was $4,240 Mil.
Revenue was 7936 + 7787 + 7275 + 7189 = $30,187 Mil.
Gross Profit was 6421 + 6246 + 5814 + 5773 = $24,254 Mil.
Total Current Assets was $27,859 Mil.
Total Assets was $85,387 Mil.
Property, Plant and Equipment(Net PPE) was $3,236 Mil.
Depreciation, Depletion and Amortization(DDA) was $890 Mil.
Selling, General, & Admin. Expense(SGA) was $3,176 Mil.
Total Current Liabilities was $19,353 Mil.
Long-Term Debt & Capital Lease Obligation was $20,487 Mil.
|
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) |
| = | (5031 / 33351) | / | (4240 / 30187) |
| = | 0.15085 | / | 0.140458 |
| | = | 1.074 |
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) |
| = | (24254 / 30187) | / | (26639 / 33351) |
| = | 0.803458 | / | 0.798747 |
| | = | 1.0059 |
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 - (32732 + 3472) / 91409) | / | (1 - (27859 + 3236) / 85387) |
| = | 0.603934 | / | 0.635834 |
| | = | 0.9498 |
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 |
| = | 33351 | / | 30187 |
| | = | 1.1048 |
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)) |
| = | (890 / (890 + 3236)) | / | (963 / (963 + 3472)) |
| = | 0.215705 | / | 0.217136 |
| | = | 0.9934 |
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) |
| = | (3217 / 33351) | / | (3176 / 30187) |
| = | 0.096459 | / | 0.105211 |
| | = | 0.9168 |
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) |
| = | ((20703 + 22634) / 91409) | / | ((20487 + 19353) / 85387) |
| = | 0.4741 | / | 0.466582 |
| | = | 1.0161 |
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 |
| = | (17984 - 337 | - | 20198) | / | 91409 |
| | = | -0.027908 |
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 -2.46 suggests that the company is unlikely to be a manipulator.
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