17 Education & Technology (YQ) Total Liabilities (2019 - 2026)
17 Education & Technology (YQ) recorded Total Liabilities of $47.54 million in Q2 2026, up 129.1% from $20.75 million a year earlier and up 36.4% from the prior quarter.
Powered by 
Analysis
17 Education & Technology (YQ) Total Liabilities (2019 - 2026) Analysis & Trends
At the end of FY2025, 17 Education & Technology reported Total Liabilities of $42.29 million, up 98.0% from FY2024.
- Annual Total Liabilities has a five-year compound annual growth rate of -26.9% (FY2020 to FY2025).
- Across earlier years, Total Liabilities came in at $21.36 million in FY2024 (-20.3%), $26.8 million in FY2023 (-16.6%), $32.14 million in FY2022 (-73.9%) and $122.93 million in FY2021 (-39.5%).
- The Q2 2026 figure is the highest quarterly Total Liabilities since Q2 2022.
- On a year-over-year basis, Total Liabilities rose in two of the last six quarters, with growth averaging 25.8%.
- Peak year-over-year performance for Total Liabilities in the last five years was growth of 129.1% in Q2 2026, against a decline of 82.1% in Q3 2022 at the low end.
- Per Business Quant, the preceding three quarters came in at $34.85 million (Q1 2026), $42.85 million (Q4 2025) and $20.73 million (Q3 2025).
Peer Set
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 | 17 Education & Technology | 36.98 Mn | -186.12 Mn | 9.19 Mn | 47.54 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 47.54 Mn |
| Mar 31, 2026 | 34.85 Mn |
| Dec 31, 2025 | 42.85 Mn |
| Sep 30, 2025 | 20.73 Mn |
| Jun 30, 2025 | 20.75 Mn |
| Mar 31, 2025 | 20.60 Mn |
| Dec 31, 2024 | -21.90 Mn |
| Sep 30, 2024 | 21.47 Mn |
| Jun 30, 2024 | 23.62 Mn |
| Mar 31, 2024 | 22.17 Mn |
| Dec 31, 2023 | -39.09 Mn |
| Sep 30, 2023 | 27.08 Mn |
| Jun 30, 2023 | 26.16 Mn |
| Mar 31, 2023 | 29.87 Mn |
| Dec 31, 2022 | -58.65 Mn |
| Sep 30, 2022 | 31.67 Mn |
| Jun 30, 2022 | 55.13 Mn |
| Mar 31, 2022 | 54.37 Mn |
| Dec 31, 2021 | -48.54 Mn |
| Sep 30, 2021 | 176.46 Mn |
API Access
17 Education & 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=YQ&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "YQ", "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=YQ&period=max&api_key=YOUR_API_KEY");
const data = await res.json();