Par Technology (PAR) Total Liabilities (2010 - 2026)
Par Technology (PAR) posted Total Liabilities of $556.1 million for Q2 2026, up 4.4% from $532.6 million a year earlier but down 1.5% from the prior quarter.
Par Technology (PAR) Total Liabilities (2010 - 2026) Analysis & Trends
At the end of FY2025, Par Technology's Total Liabilities came in at $543.99 million, up 6.9% from FY2024.
- Annual Total Liabilities shows a five-year compound annual growth rate of 28.5% (FY2020 to FY2025).
- In prior years, Par Technology's Total Liabilities was $509.02 million in FY2024 (+8.4%), $469.54 million in FY2023 (-2.1%), $479.66 million in FY2022 (+25.0%) and $383.8 million in FY2021 (+147.1%).
- Quarterly Total Liabilities has run from a low of $381.71 million in Q3 2021 to a high of $606.57 million in Q3 2024 over five years.
- On a year-over-year basis, Total Liabilities has increased in each of the last three quarters, with growth averaging 8.3% over the last eight quarters.
- The strongest year-over-year quarter for Total Liabilities in the past five years was Q1 2022, with growth of 186.2%; the weakest was Q3 2025, with a decline of 11.1%.
- According to Business Quant data, Total Liabilities for the three prior quarters was $564.72 million (Q1 2026), $543.99 million (Q4 2025) and $539.33 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Bryn | 945.00 Bn | 945.00 Bn | - | 206,169.00 |
| 2 | Veeva Systems | 45.35 Bn | 17.59 Bn | 695.95 Mn | 1.63 Bn |
| 3 | Samsara | 22.20 Bn | 18.97 Bn | 392.58 Mn | 1.17 Bn |
| 4 | Toast | 17.53 Bn | 10.20 Bn | 516.00 Mn | 1.14 Bn |
| 5 | Ptc | 15.47 Bn | 14.28 Bn | 490.47 Mn | 3.04 Bn |
| 6 | Trimble | 13.41 Bn | 12.48 Bn | 674.90 Mn | 3.43 Bn |
| 7 | Duolingo | 12.56 Bn | 7.73 Bn | 216.74 Mn | 664.21 Mn |
| 8 | Manhattan Associates | 11.77 Bn | 10.77 Bn | 168.33 Mn | 541.14 Mn |
| 9 | Costar | 10.95 Bn | 4.91 Bn | 728.00 Mn | 2.19 Bn |
| 10 | Par Technology | 564.19 Mn | 235.29 Mn | 56.58 Mn | 556.10 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 556.10 Mn |
| Mar 31, 2026 | 564.72 Mn |
| Dec 31, 2025 | 543.99 Mn |
| Sep 30, 2025 | 539.33 Mn |
| Jun 30, 2025 | 532.60 Mn |
| Mar 31, 2025 | 529.55 Mn |
| Dec 31, 2024 | 509.02 Mn |
| Sep 30, 2024 | 606.57 Mn |
| Jun 30, 2024 | 468.36 Mn |
| Mar 31, 2024 | 482.51 Mn |
| Dec 31, 2023 | 469.54 Mn |
| Sep 30, 2023 | 476.47 Mn |
| Jun 30, 2023 | 474.27 Mn |
| Mar 31, 2023 | 472.42 Mn |
| Dec 31, 2022 | 479.66 Mn |
| Sep 30, 2022 | 481.66 Mn |
| Jun 30, 2022 | 463.61 Mn |
| Mar 31, 2022 | 460.23 Mn |
| Dec 31, 2021 | 383.80 Mn |
| Sep 30, 2021 | 381.71 Mn |
Par Technology Total Liabilities 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=total-liabilities&ticker=PAR&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "PAR", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=total-liabilities&ticker=PAR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();