Green Dot Beneish M-Score Historical Data
The historical data trend for Green Dot'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.
Green Dot Beneish M-Score Chart
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Green Dot Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.56 |
-2.39 |
-2.06 |
-2.80 |
-2.01 |
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Green Dot 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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-2.80 |
-2.67 |
-2.63 |
-2.55 |
-2.01 |
Competitive Comparison of Green Dot's Beneish M-Score
For the Credit Services subindustry, Green Dot'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.
Green Dot's Beneish M-Score Distribution in the Credit Services Industry
For the Credit Services industry and Financial Services sector, Green Dot's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Green Dot's Beneish M-Score falls into.
Green Dot 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 Green Dot 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 * 1.4461 | + | 0.528 * 1.2082 | + | 0.404 * 0.9437 | + | 0.892 * 1.0357 | + | 0.115 * 1.0438 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9212 | + | 4.679 * -0.017809 | - | 0.327 * 0.9828 |
| = | -2.01 |
* 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 $68 Mil.
Revenue was 366.043 + 353.029 + 365.876 + 416.38 = $1,501 Mil.
Gross Profit was 140.87 + 131.247 + 147.527 + 200.901 = $621 Mil.
Total Current Assets was $1,638 Mil.
Total Assets was $4,817 Mil.
Property, Plant and Equipment(Net PPE) was $185 Mil.
Depreciation, Depletion and Amortization(DDA) was $83 Mil.
Selling, General, & Admin. Expense(SGA) was $601 Mil.
Total Current Liabilities was $3,953 Mil.
Long-Term Debt & Capital Lease Obligation was $3 Mil.
Net Income was -23.603 + -6.265 + 0.578 + 36.012 = $7 Mil.
Non Operating Income was 1.04 + -0.802 + -2.224 + -3.024 = $-5 Mil.
Cash Flow from Operations was -34.929 + 4.682 + 27.234 + 100.532 = $98 Mil.
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Total Receivables was $46 Mil.
Revenue was 342.432 + 343.748 + 362.769 + 400.617 = $1,450 Mil.
Gross Profit was 152.405 + 156.592 + 192.741 + 222.174 = $724 Mil.
Total Current Assets was $1,466 Mil.
Total Assets was $4,789 Mil.
Property, Plant and Equipment(Net PPE) was $169 Mil.
Depreciation, Depletion and Amortization(DDA) was $81 Mil.
Selling, General, & Admin. Expense(SGA) was $630 Mil.
Total Current Liabilities was $3,962 Mil.
Long-Term Debt & Capital Lease Obligation was $40 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) |
| = | (68.167 / 1501.328) | / | (45.513 / 1449.566) |
| = | 0.045404 | / | 0.031398 |
| | = | 1.4461 |
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) |
| = | (723.912 / 1449.566) | / | (620.545 / 1501.328) |
| = | 0.499399 | / | 0.413331 |
| | = | 1.2082 |
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 - (1637.91 + 184.718) / 4817.122) | / | (1 - (1465.832 + 168.538) / 4789.176) |
| = | 0.621635 | / | 0.658737 |
| | = | 0.9437 |
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 |
| = | 1501.328 | / | 1449.566 |
| | = | 1.0357 |
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)) |
| = | (80.61 / (80.61 + 168.538)) | / | (82.971 / (82.971 + 184.718)) |
| = | 0.323543 | / | 0.309953 |
| | = | 1.0438 |
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) |
| = | (600.902 / 1501.328) | / | (629.792 / 1449.566) |
| = | 0.400247 | / | 0.434469 |
| | = | 0.9212 |
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) |
| = | ((2.687 + 3953.19) / 4817.122) | / | ((40.247 + 3961.671) / 4789.176) |
| = | 0.821212 | / | 0.835617 |
| | = | 0.9828 |
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 |
| = | (6.722 - -5.01 | - | 97.519) | / | 4817.122 |
| | = | -0.017809 |
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.
Green Dot has a M-score of -2.01 suggests that the company is unlikely to be a manipulator.
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