Seer (SEER) Total Liabilities (2020 - 2026)
Seer (SEER) reported Total Liabilities of $30.96 million for Q2 2026, down 9.5% from $34.2 million a year earlier but up 1.0% from the prior quarter.
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Analysis
Seer (SEER) Total Liabilities (2020 - 2026) Analysis & Trends
At the end of FY2025, Seer posted Total Liabilities of $36.78 million, down 5.8% from FY2024.
- Total Liabilities has declined for three consecutive years, though with a five-year compound annual growth rate of 28.0% (FY2020 to FY2025).
- By year, Total Liabilities came in at $39.03 million in FY2024 (-0.9%), $39.37 million in FY2023 (-3.8%), $40.94 million in FY2022 (+13.0%) and $36.22 million in FY2021 (+238.2%).
- Five-year quarterly Total Liabilities spans a low of $12.64 million in Q3 2021 and a high of $44.26 million in Q2 2022.
- Year over year, Total Liabilities has now declined in each of the last 14 quarters, with an average decline of 7.7% over the last eight quarters.
- The high point for year-over-year Total Liabilities in five years was Q1 2022 (growth of 311.7%); the low point was Q2 2025 (a decline of 18.4%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $30.65 million (Q1 2026), $36.78 million (Q4 2025) and $36.79 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 250.84 Bn | 229.99 Bn | 4.88 Bn | 60.49 Bn |
| 2 | Abbott Laboratories | 174.73 Bn | 145.82 Bn | 7.27 Bn | 57.45 Bn |
| 3 | Danaher | 159.85 Bn | 143.67 Bn | 3.61 Bn | 39.78 Bn |
| 4 | Intuitive Surgical | 146.79 Bn | 126.35 Bn | 1.96 Bn | 2.58 Bn |
| 5 | Medtronic | 114.54 Bn | 80.41 Bn | 6.34 Bn | 42.46 Bn |
| 6 | Stryker | 105.67 Bn | 91.79 Bn | 4.50 Bn | 23.94 Bn |
| 7 | Boston Scientific | 63.93 Bn | 58.94 Bn | 3.85 Bn | 20.04 Bn |
| 8 | Becton Dickinson | 50.12 Bn | 47.27 Bn | 2.32 Bn | 26.32 Bn |
| 9 | Edwards Lifesciences | 50.06 Bn | 34.17 Bn | 1.35 Bn | 3.14 Bn |
| 10 | Seer | 225.08 Mn | 225.08 Mn | 1.51 Mn | 30.96 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 30.96 Mn |
| Mar 31, 2026 | 30.65 Mn |
| Dec 31, 2025 | 36.78 Mn |
| Sep 30, 2025 | 36.79 Mn |
| Jun 30, 2025 | 34.20 Mn |
| Mar 31, 2025 | 36.26 Mn |
| Dec 31, 2024 | 39.03 Mn |
| Sep 30, 2024 | 38.70 Mn |
| Jun 30, 2024 | 41.91 Mn |
| Mar 31, 2024 | 38.41 Mn |
| Dec 31, 2023 | 39.37 Mn |
| Sep 30, 2023 | 39.17 Mn |
| Jun 30, 2023 | 43.08 Mn |
| Mar 31, 2023 | 39.80 Mn |
| Dec 31, 2022 | 40.94 Mn |
| Sep 30, 2022 | 42.44 Mn |
| Jun 30, 2022 | 44.26 Mn |
| Mar 31, 2022 | 40.63 Mn |
| Dec 31, 2021 | 36.22 Mn |
| Sep 30, 2021 | 12.64 Mn |
API Access
Seer 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=SEER&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-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-liabilities&ticker=SEER&period=max&api_key=YOUR_API_KEY");
const data = await res.json();