Vaso (VASO) Total Current Liabilities (2011 - 2026)
Vaso's Total Current Liabilities was $32.86 million in Q2 2026, down 0.5% from $33.02 million a year earlier but up 7.5% from the prior quarter.
Vaso (VASO) Total Current Liabilities (2011 - 2026) Analysis & Trends
At the end of FY2025, Total Current Liabilities at Vaso came in at $36.85 million, up 6.1% from FY2024.
- Total Current Liabilities shows a five-year compound annual growth rate of 3.1% (FY2020 to FY2025).
- In earlier years, Total Current Liabilities was $34.72 million in FY2024 (+15.6%), $30.04 million in FY2023 (-4.7%), $31.51 million in FY2022 (+1.6%) and $31 million in FY2021 (-2.2%).
- Quarterly Total Current Liabilities has moved between $26.22 million (Q1 2023) and $36.85 million (Q4 2025) over five years.
- Compared with a year earlier, Total Current Liabilities was higher in six of the last eight quarters, with growth averaging 7.6%.
- The best year-over-year quarter for Total Current Liabilities over five years was Q2 2025 (growth of 23.0%); the worst was Q1 2023 (a decline of 12.5%).
- Per Business Quant data, VASO's Total Current Liabilities in the three quarters before Q2 2026 was $30.56 million (Q1 2026), $36.85 million (Q4 2025) and $31.6 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 251.93 Bn | 230.96 Bn | 4.88 Bn | 15.07 Bn |
| 2 | Abbott Laboratories | 181.29 Bn | 151.72 Bn | 7.27 Bn | 17.81 Bn |
| 3 | Danaher | 158.18 Bn | 141.99 Bn | 3.61 Bn | 8.11 Bn |
| 4 | Intuitive Surgical | 153.47 Bn | 132.89 Bn | 1.96 Bn | 1.92 Bn |
| 5 | Medtronic | 118.97 Bn | 84.22 Bn | 6.34 Bn | 11.80 Bn |
| 6 | Stryker | 114.72 Bn | 100.84 Bn | 4.50 Bn | 6.68 Bn |
| 7 | Boston Scientific | 66.18 Bn | 60.95 Bn | 3.85 Bn | 6.43 Bn |
| 8 | Becton Dickinson | 52.49 Bn | 49.64 Bn | 2.32 Bn | 9.40 Bn |
| 9 | Edwards Lifesciences | 50.32 Bn | 34.33 Bn | 1.35 Bn | 1.51 Bn |
| 10 | Vaso | 49.30 Mn | -79.90 Mn | 8.89 Mn | 32.86 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 32.86 Mn |
| Mar 31, 2026 | 30.56 Mn |
| Dec 31, 2025 | 36.85 Mn |
| Sep 30, 2025 | 31.60 Mn |
| Jun 30, 2025 | 33.02 Mn |
| Mar 31, 2025 | 30.25 Mn |
| Dec 31, 2024 | 34.72 Mn |
| Sep 30, 2024 | 30.17 Mn |
| Jun 30, 2024 | 26.84 Mn |
| Mar 31, 2024 | 27.28 Mn |
| Dec 31, 2023 | 30.04 Mn |
| Sep 30, 2023 | 30.30 Mn |
| Jun 30, 2023 | 29.08 Mn |
| Mar 31, 2023 | 26.22 Mn |
| Dec 31, 2022 | 31.51 Mn |
| Sep 30, 2022 | 32.62 Mn |
| Jun 30, 2022 | 30.58 Mn |
| Mar 31, 2022 | 29.97 Mn |
| Dec 31, 2021 | 31.00 Mn |
| Sep 30, 2021 | 28.74 Mn |
Vaso Total Current 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-current-liabilities&ticker=VASO&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-current-liabilities", "ticker": "VASO", "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-current-liabilities&ticker=VASO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();