Vaso (VASO) Total Liabilities (2011 - 2026)
Vaso's Total Liabilities was $56.7 million in Q2 2026, up 1.1% from $56.08 million a year earlier and up 4.3% from the prior quarter.
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Analysis
Vaso (VASO) Total Liabilities (2011 - 2026) Analysis & Trends
At the end of FY2025, Total Liabilities at Vaso came in at $58.92 million, up 6.7% from FY2024.
- Total Liabilities shows a five-year compound annual growth rate of 5.4% (FY2020 to FY2025).
- In earlier years, Total Liabilities was $55.24 million in FY2024 (+12.9%), $48.91 million in FY2023 (-1.3%), $49.58 million in FY2022 (+20.1%) and $41.28 million in FY2021 (-8.9%).
- Quarterly Total Liabilities has moved between $37.15 million (Q3 2021) and $58.92 million (Q4 2025) over five years.
- Compared with a year earlier, Total Liabilities has increased for eight straight quarters, with growth averaging 10.7% over the last eight quarters.
- The best year-over-year quarter for Total Liabilities over five years was Q2 2025 (growth of 23.7%); the worst was Q3 2021 (a decline of 13.9%).
- Per Business Quant data, VASO's Total Liabilities in the three quarters before Q2 2026 was $54.38 million (Q1 2026), $58.92 million (Q4 2025) and $56.24 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 251.93 Bn | 230.96 Bn | 4.88 Bn | 60.49 Bn |
| 2 | Abbott Laboratories | 181.29 Bn | 151.72 Bn | 7.27 Bn | 57.45 Bn |
| 3 | Danaher | 158.18 Bn | 141.99 Bn | 3.61 Bn | 39.78 Bn |
| 4 | Intuitive Surgical | 153.47 Bn | 132.89 Bn | 1.96 Bn | 2.58 Bn |
| 5 | Medtronic | 118.97 Bn | 84.22 Bn | 6.34 Bn | 42.46 Bn |
| 6 | Stryker | 114.72 Bn | 100.84 Bn | 4.50 Bn | 23.94 Bn |
| 7 | Boston Scientific | 66.18 Bn | 60.95 Bn | 3.85 Bn | 20.04 Bn |
| 8 | Becton Dickinson | 52.49 Bn | 49.64 Bn | 2.32 Bn | 26.32 Bn |
| 9 | Edwards Lifesciences | 50.32 Bn | 34.33 Bn | 1.35 Bn | 3.14 Bn |
| 10 | Vaso | 49.30 Mn | -79.90 Mn | 8.89 Mn | 56.70 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 56.70 Mn |
| Mar 31, 2026 | 54.38 Mn |
| Dec 31, 2025 | 58.92 Mn |
| Sep 30, 2025 | 56.24 Mn |
| Jun 30, 2025 | 56.08 Mn |
| Mar 31, 2025 | 51.26 Mn |
| Dec 31, 2024 | 55.24 Mn |
| Sep 30, 2024 | 48.29 Mn |
| Jun 30, 2024 | 45.34 Mn |
| Mar 31, 2024 | 43.87 Mn |
| Dec 31, 2023 | 48.91 Mn |
| Sep 30, 2023 | 47.43 Mn |
| Jun 30, 2023 | 49.15 Mn |
| Mar 31, 2023 | 46.95 Mn |
| Dec 31, 2022 | 49.58 Mn |
| Sep 30, 2022 | 44.73 Mn |
| Jun 30, 2022 | 41.67 Mn |
| Mar 31, 2022 | 41.00 Mn |
| Dec 31, 2021 | 41.28 Mn |
| Sep 30, 2021 | 37.15 Mn |
API Access
Vaso 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=VASO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-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-liabilities&ticker=VASO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();