Seer (SEER) Total Non-Current Liabilities (2020 - 2026)
Seer's Total Non-Current Liabilities was $30.94 million in Q2 2026, down 9.5% from $34.18 million a year earlier but up 1.0% from the prior quarter.
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Analysis
Seer (SEER) Total Non-Current Liabilities (2020 - 2026) Analysis & Trends
At the end of FY2025, Total Non-Current Liabilities at Seer came in at $36.77 million, down 5.7% from FY2024.
- Total Non-Current Liabilities has now declined for three consecutive years, though with a five-year compound annual growth rate of 33.1% (FY2020 to FY2025).
- In earlier years, Total Non-Current Liabilities was $38.98 million in FY2024 (-0.5%), $39.19 million in FY2023 (-3.5%), $40.62 million in FY2022 (+13.2%) and $35.88 million in FY2021 (+307.2%).
- Quarterly Total Non-Current Liabilities has moved between $9.96 million (Q3 2021) and $43.93 million (Q2 2022) over five years.
- Compared with a year earlier, Total Non-Current Liabilities has declined for 14 straight quarters, with an average decline of 7.6% over the last eight quarters.
- The best year-over-year quarter for Total Non-Current Liabilities over five years was Q1 2022 (growth of 404.5%); the worst was Q2 2025 (a decline of 18.4%).
- Per Business Quant data, SEER's Total Non-Current Liabilities in the three quarters before Q2 2026 was $30.63 million (Q1 2026), $36.77 million (Q4 2025) and $36.78 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 251.30 Bn | 230.45 Bn | 4.88 Bn | 55.95 Bn |
| 2 | Abbott Laboratories | 174.70 Bn | 145.78 Bn | 7.27 Bn | - |
| 3 | Danaher | 158.94 Bn | 142.76 Bn | 3.61 Bn | 33.25 Bn |
| 4 | Intuitive Surgical | 145.87 Bn | 125.42 Bn | 1.96 Bn | - |
| 5 | Medtronic | 111.49 Bn | 77.36 Bn | 6.34 Bn | 40.46 Bn |
| 6 | Stryker | 106.96 Bn | 93.08 Bn | 4.50 Bn | 21.28 Bn |
| 7 | Boston Scientific | 63.62 Bn | 58.63 Bn | 3.85 Bn | 17.56 Bn |
| 8 | Edwards Lifesciences | 50.80 Bn | 34.92 Bn | 1.35 Bn | 2.57 Bn |
| 9 | Becton Dickinson | 49.59 Bn | 46.74 Bn | 2.32 Bn | 23.92 Bn |
| 10 | Seer | 238.39 Mn | 238.39 Mn | 1.51 Mn | 30.94 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 30.94 Mn |
| Mar 31, 2026 | 30.63 Mn |
| Dec 31, 2025 | 36.77 Mn |
| Sep 30, 2025 | 36.78 Mn |
| Jun 30, 2025 | 34.18 Mn |
| Mar 31, 2025 | 36.22 Mn |
| Dec 31, 2024 | 38.98 Mn |
| Sep 30, 2024 | 38.63 Mn |
| Jun 30, 2024 | 41.87 Mn |
| Mar 31, 2024 | 38.23 Mn |
| Dec 31, 2023 | 39.19 Mn |
| Sep 30, 2023 | 39.02 Mn |
| Jun 30, 2023 | 42.90 Mn |
| Mar 31, 2023 | 39.44 Mn |
| Dec 31, 2022 | 40.62 Mn |
| Sep 30, 2022 | 42.13 Mn |
| Jun 30, 2022 | 43.93 Mn |
| Mar 31, 2022 | 40.29 Mn |
| Dec 31, 2021 | 35.88 Mn |
| Sep 30, 2021 | 9.96 Mn |
API Access
Seer Total Non-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-non-current-liabilities&ticker=SEER&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "ticker": "SEER", "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-non-current-liabilities&ticker=SEER&period=max&api_key=YOUR_API_KEY");
const data = await res.json();