Pitney Bowes (PBI) Change in Accured Expenses (2009 - 2021)
Pitney Bowes (PBI) posted Change in Accured Expenses of $27.75 million for Q3 2021, down 28.1% from $38.61 million a year earlier.
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Analysis
Pitney Bowes (PBI) Change in Accured Expenses (2009 - 2021) Analysis & Trends
For the trailing twelve months through Sep 30, 2021, Change in Accured Expenses at Pitney Bowes was $53.13 million, up 53.4% year-over-year; for FY2020, it came in at $94.85 million, up 329.6% from FY2019.
- In prior years, Pitney Bowes' Change in Accured Expenses was $22.08 million in FY2019, -$4.37 million in FY2018, -$18.65 million in FY2017 and -$97.78 million in FY2016.
- Quarterly Change in Accured Expenses has run from a low of -$104.56 million in Q1 2020 to a high of $81.41 million in Q4 2020 over five years.
- On a year-over-year basis, Change in Accured Expenses increased in 1 of the last four quarters, with growth averaging 38.6%.
- According to Business Quant data, Change in Accured Expenses for the three prior quarters was -$2.02 million (Q2 2021), -$54.02 million (Q1 2021) and $81.41 million (Q4 2020).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Accenture | 132.79 Bn | 93.20 Bn | 6.13 Bn | 967.46 Mn |
| 2 | Cintas | 77.24 Bn | 76.43 Bn | 1.48 Bn | 60.14 Mn |
| 3 | Iron Mountain | 33.76 Bn | 33.28 Bn | 1.07 Bn | 183.83 Mn |
| 4 | APi | 17.50 Bn | 14.54 Bn | 703.00 Mn | - |
| 5 | Aramark | 14.64 Bn | 12.66 Bn | 430.34 Mn | -6.96 Mn |
| 6 | Rollins | 14.51 Bn | 14.06 Bn | 569.95 Mn | 81.49 Mn |
| 7 | UL Solutions | 13.33 Bn | 12.11 Bn | 417.00 Mn | 83.00 Mn |
| 8 | Gartner | 11.67 Bn | 5.36 Bn | 1.19 Bn | 53.59 Mn |
| 9 | Rentokil Initial | 10.08 Bn | 3.42 Bn | - | - |
| 10 | Pitney Bowes | 2.30 Bn | 1.07 Bn | 254.70 Mn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2021 | 27.75 Mn |
| Jun 30, 2021 | -2.02 Mn |
| Mar 31, 2021 | -54.02 Mn |
| Dec 31, 2020 | 81.41 Mn |
| Sep 30, 2020 | 38.61 Mn |
| Jun 30, 2020 | 79.39 Mn |
| Mar 31, 2020 | -104.56 Mn |
| Dec 31, 2019 | 21.19 Mn |
| Sep 30, 2019 | 54.78 Mn |
| Jun 30, 2019 | -38.90 Mn |
| Mar 31, 2019 | -14.99 Mn |
| Dec 31, 2018 | 76.54 Mn |
| Sep 30, 2018 | -26.29 Mn |
| Jun 30, 2018 | 20.19 Mn |
| Mar 31, 2018 | -74.81 Mn |
| Dec 31, 2017 | 20.14 Mn |
| Sep 30, 2017 | 30.36 Mn |
| Jun 30, 2017 | -36.32 Mn |
| Mar 31, 2017 | -32.83 Mn |
| Dec 31, 2016 | 22.04 Mn |
API Access
Pitney Bowes Change in Accured Expenses API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=change-in-accured-expenses&ticker=PBI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "PBI", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=change-in-accured-expenses&ticker=PBI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();