Fiserv Beneish M-Score Historical Data
The historical data trend for Fiserv'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.
Fiserv Beneish M-Score Chart
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Fiserv Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-1.43 |
-2.71 |
-2.57 |
-2.49 |
-2.69 |
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Fiserv Quarterly Data
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Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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-2.56 |
-3.35 |
-2.69 |
-2.69 |
-2.68 |
Competitive Comparison of Fiserv's Beneish M-Score
For the Information Technology Services subindustry, Fiserv'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.
Fiserv's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, Fiserv's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Fiserv's Beneish M-Score falls into.
Fiserv 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 Fiserv 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 * 1.0208 | + | 0.528 * 0.9215 | + | 0.404 * 0.8124 | + | 0.892 * 1.0325 | + | 0.115 * 1.0582 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0053 | + | 4.679 * -0.018115 | - | 0.327 * 1.1914 |
| = | -2.69 |
* 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 (Mar24) TTM: | Last Year (Mar23) TTM: |
Total Receivables was €3,288 Mil.
Revenue was 4492.36 + 4508.889 + 4566.001 + 4389.788 = €17,957 Mil.
Gross Profit was 2647.76 + 2819.775 + 2791.323 + 2609.321 = €10,868 Mil.
Total Current Assets was €34,126 Mil.
Total Assets was €85,282 Mil.
Property, Plant and Equipment(Net PPE) was €2,048 Mil.
Depreciation, Depletion and Amortization(DDA) was €2,874 Mil.
Selling, General, & Admin. Expense(SGA) was €6,164 Mil.
Total Current Liabilities was €32,309 Mil.
Long-Term Debt & Capital Lease Obligation was €21,854 Mil.
Net Income was 676.2 + 797.79 + 892.024 + 630.409 = €2,996 Mil.
Non Operating Income was -6.44 + -58.688 + 132.117 + -23.998 = €43 Mil.
Cash Flow from Operations was 764.52 + 1462.615 + 1460.783 + 810.394 = €4,498 Mil.
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Total Receivables was €3,120 Mil.
Revenue was 4246.898 + 4371.664 + 4563.18 + 4209.7 = €17,391 Mil.
Gross Profit was 2374.228 + 2502.544 + 2547.22 + 2276.076 = €9,700 Mil.
Total Current Assets was €18,950 Mil.
Total Assets was €71,496 Mil.
Property, Plant and Equipment(Net PPE) was €1,870 Mil.
Depreciation, Depletion and Amortization(DDA) was €3,024 Mil.
Selling, General, & Admin. Expense(SGA) was €5,938 Mil.
Total Current Liabilities was €17,618 Mil.
Long-Term Debt & Capital Lease Obligation was €20,495 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) |
| = | (3288.08 / 17957.038) | / | (3119.56 / 17391.442) |
| = | 0.183108 | / | 0.179373 |
| | = | 1.0208 |
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) |
| = | (9700.068 / 17391.442) | / | (10868.179 / 17957.038) |
| = | 0.557749 | / | 0.605232 |
| | = | 0.9215 |
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 - (34126.48 + 2047.92) / 85282.16) | / | (1 - (18949.926 + 1869.868) / 71495.832) |
| = | 0.575827 | / | 0.708797 |
| | = | 0.8124 |
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 |
| = | 17957.038 | / | 17391.442 |
| | = | 1.0325 |
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)) |
| = | (3024.228 / (3024.228 + 1869.868)) | / | (2874.372 / (2874.372 + 2047.92)) |
| = | 0.617934 | / | 0.58395 |
| | = | 1.0582 |
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) |
| = | (6163.78 / 17957.038) | / | (5938.178 / 17391.442) |
| = | 0.343251 | / | 0.341443 |
| | = | 1.0053 |
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) |
| = | ((21853.68 + 32308.56) / 85282.16) | / | ((20494.762 + 17618.042) / 71495.832) |
| = | 0.635095 | / | 0.533077 |
| | = | 1.1914 |
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 |
| = | (2996.423 - 42.991 | - | 4498.312) | / | 85282.16 |
| | = | -0.018115 |
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.
Fiserv has a M-score of -2.69 suggests that the company is unlikely to be a manipulator.
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