Credit Acceptance Beneish M-Score Historical Data
The historical data trend for Credit Acceptance'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.
Credit Acceptance Beneish M-Score Chart
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Credit Acceptance Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.47 |
-2.78 |
-2.58 |
-2.91 |
-2.96 |
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Credit Acceptance 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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-2.91 |
-2.93 |
-2.96 |
-2.91 |
-2.96 |
Competitive Comparison of Credit Acceptance's Beneish M-Score
For the Credit Services subindustry, Credit Acceptance'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.
Credit Acceptance's Beneish M-Score Distribution in the Credit Services Industry
For the Credit Services industry and Financial Services sector, Credit Acceptance's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Credit Acceptance's Beneish M-Score falls into.
Credit Acceptance 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 Credit Acceptance 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 * 1.0701 | + | 0.528 * 1.1009 | + | 0.404 * 0.9152 | + | 0.892 * 1.0313 | + | 0.115 * 0.9137 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0558 | + | 4.679 * -0.120575 | - | 0.327 * 1.0219 |
| = | -2.96 |
* 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 $6,960 Mil.
Revenue was 485.4 + 473.2 + 472.6 + 449.7 = $1,881 Mil.
Gross Profit was 323.9 + 319.5 + 319.9 + 300.2 = $1,264 Mil.
Total Current Assets was $7,437 Mil.
Total Assets was $7,610 Mil.
Property, Plant and Equipment(Net PPE) was $47 Mil.
Depreciation, Depletion and Amortization(DDA) was $27 Mil.
Selling, General, & Admin. Expense(SGA) was $179 Mil.
Total Current Liabilities was $400 Mil.
Long-Term Debt & Capital Lease Obligation was $5,068 Mil.
Net Income was 93.6 + 70.8 + 22.2 + 99.5 = $286 Mil.
Non Operating Income was -1 + 0.5 + 0.4 + 0 = $-0 Mil.
Cash Flow from Operations was 311.2 + 313.4 + 282.7 + 296.5 = $1,204 Mil.
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Total Receivables was $6,306 Mil.
Revenue was 454.8 + 457.8 + 455.8 + 455.4 = $1,824 Mil.
Gross Profit was 327.7 + 336.2 + 339.3 + 345.6 = $1,349 Mil.
Total Current Assets was $6,728 Mil.
Total Assets was $6,905 Mil.
Property, Plant and Equipment(Net PPE) was $51 Mil.
Depreciation, Depletion and Amortization(DDA) was $26 Mil.
Selling, General, & Admin. Expense(SGA) was $164 Mil.
Total Current Liabilities was $263 Mil.
Long-Term Debt & Capital Lease Obligation was $4,591 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) |
| = | (6959.6 / 1880.9) | / | (6306.4 / 1823.8) |
| = | 3.700144 | / | 3.457835 |
| | = | 1.0701 |
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) |
| = | (1348.8 / 1823.8) | / | (1263.5 / 1880.9) |
| = | 0.739555 | / | 0.671753 |
| | = | 1.1009 |
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 - (7437.3 + 46.5) / 7610.2) | / | (1 - (6728 + 51.4) / 6904.7) |
| = | 0.016609 | / | 0.018147 |
| | = | 0.9152 |
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 |
| = | 1880.9 | / | 1823.8 |
| | = | 1.0313 |
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)) |
| = | (25.6 / (25.6 + 51.4)) | / | (26.6 / (26.6 + 46.5)) |
| = | 0.332468 | / | 0.363885 |
| | = | 0.9137 |
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) |
| = | (178.9 / 1880.9) | / | (164.3 / 1823.8) |
| = | 0.095114 | / | 0.090087 |
| | = | 1.0558 |
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) |
| = | ((5067.5 + 399.8) / 7610.2) | / | ((4590.7 + 263.3) / 6904.7) |
| = | 0.718417 | / | 0.702999 |
| | = | 1.0219 |
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 |
| = | (286.1 - -0.1 | - | 1203.8) | / | 7610.2 |
| | = | -0.120575 |
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.
Credit Acceptance has a M-score of -2.96 suggests that the company is unlikely to be a manipulator.
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