Pitney Bowes Beneish M-Score Historical Data
The historical data trend for Pitney Bowes'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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Pitney Bowes Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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|
|
|
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-2.37 |
-2.59 |
-2.72 |
-2.63 |
-2.65 |
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Pitney Bowes 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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-2.63 |
-2.64 |
-2.59 |
-2.70 |
-2.65 |
Competitive Comparison
For the Integrated Freight & Logistics subindustry, Pitney Bowes'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.
Pitney Bowes Beneish M-Score Distribution
For the Transportation industry and Industrials sector, Pitney Bowes's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Pitney Bowes's Beneish M-Score falls into.
Pitney Bowes 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 Pitney Bowes 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 * 1.0702 | + | 0.528 * 0.9631 | + | 0.404 * 0.9403 | + | 0.892 * 0.9232 | + | 0.115 * 0.9868 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0754 | + | 4.679 * -0.017707 | - | 0.327 * 1.091 |
| = | -2.65 |
* 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 $906 Mil.
Revenue was 871.578 + 783.751 + 776.481 + 834.538 = $3,266 Mil.
Gross Profit was 288.598 + 260.564 + 258.619 + 277.557 = $1,085 Mil.
Total Current Assets was $1,692 Mil.
Total Assets was $4,272 Mil.
Property, Plant and Equipment(Net PPE) was $717 Mil.
Depreciation, Depletion and Amortization(DDA) was $160 Mil.
Selling, General, & Admin. Expense(SGA) was $897 Mil.
Total Current Liabilities was $1,730 Mil.
Long-Term Debt & Capital Lease Obligation was $2,365 Mil.
Net Income was -223.836 + -12.519 + -141.535 + -7.737 = $-386 Mil.
Non Operating Income was -237.438 + -13.895 + -139.063 + 0.947 = $-389 Mil.
Cash Flow from Operations was 93.921 + 25.305 + -0.044 + -39.714 = $79 Mil.
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Total Receivables was $917 Mil.
Revenue was 908.691 + 830.914 + 871.495 + 926.942 = $3,538 Mil.
Gross Profit was 288.174 + 264.187 + 273.924 + 305.996 = $1,132 Mil.
Total Current Assets was $1,798 Mil.
Total Assets was $4,741 Mil.
Property, Plant and Equipment(Net PPE) was $744 Mil.
Depreciation, Depletion and Amortization(DDA) was $164 Mil.
Selling, General, & Admin. Expense(SGA) was $904 Mil.
Total Current Liabilities was $1,728 Mil.
Long-Term Debt & Capital Lease Obligation was $2,438 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) |
| = | (906.336 / 3266.348) | / | (917.319 / 3538.042) |
| = | 0.277477 | / | 0.259273 |
| | = | 1.0702 |
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) |
| = | (1132.281 / 3538.042) | / | (1085.338 / 3266.348) |
| = | 0.32003 | / | 0.332279 |
| | = | 0.9631 |
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 - (1691.917 + 717.169) / 4272.185) | / | (1 - (1798.016 + 744.288) / 4741.355) |
| = | 0.4361 | / | 0.463802 |
| | = | 0.9403 |
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 |
| = | 3266.348 | / | 3538.042 |
| | = | 0.9232 |
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)) |
| = | (163.816 / (163.816 + 744.288)) | / | (160.43 / (160.43 + 717.169)) |
| = | 0.180393 | / | 0.182806 |
| | = | 0.9868 |
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) |
| = | (897.26 / 3266.348) | / | (903.768 / 3538.042) |
| = | 0.274698 | / | 0.255443 |
| | = | 1.0754 |
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) |
| = | ((2365.082 + 1730.409) / 4272.185) | / | ((2438.198 + 1727.803) / 4741.355) |
| = | 0.958641 | / | 0.878652 |
| | = | 1.091 |
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 |
| = | (-385.627 - -389.449 | - | 79.468) | / | 4272.185 |
| | = | -0.017707 |
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.
Pitney Bowes has a M-score of -2.65 suggests that the company is unlikely to be a manipulator.
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