Fabric.AI (FABC) Total Non-Current Liabilities (2012 - 2026)
Fabric.AI's Total Non-Current Liabilities came in at $18.99 million for Q2 2026, up 144.6% from $7.76 million a year earlier and up 129.2% from the prior quarter.
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Analysis
Fabric.AI (FABC) Total Non-Current Liabilities (2012 - 2026) Analysis & Trends
At the end of FY2025, Fabric.AI's Total Non-Current Liabilities was $7.68 million, down 46.7% from FY2024.
- Total Non-Current Liabilities carries a five-year compound annual growth rate of 26.0% (FY2020 to FY2025).
- Going back by year, Total Non-Current Liabilities was $14.4 million in FY2024 (-43.3%), $25.41 million in FY2023 (+789.4%), $2.86 million in FY2022 (-36.8%) and $4.52 million in FY2021 (+86.8%).
- The Q2 2026 figure represents the highest quarterly Total Non-Current Liabilities since Q3 2024.
- Year-over-year, Total Non-Current Liabilities increased in two of the last eight quarters, with an average decline of 13.2%.
- The fastest year-over-year change in Total Non-Current Liabilities over five years came in Q4 2023 (growth of 789.4%), and the weakest in Q2 2025 (a decline of 69.4%).
- Business Quant data shows FABC's Total Non-Current Liabilities at $8.29 million (Q1 2026), $7.68 million (Q4 2025) and $7.3 million (Q3 2025) in the three quarters before Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Robinhood Markets | 104.48 Bn | 85.58 Bn | - | 46.75 Bn |
| 2 | Bank of New York Mellon | 99.71 Bn | 39.09 Bn | - | 468.26 Bn |
| 3 | Cme | 94.57 Bn | 94.57 Bn | - | 167.36 Bn |
| 4 | Intercontinental Exchange | 85.38 Bn | 79.19 Bn | - | 24.02 Bn |
| 5 | Nasdaq | 51.62 Bn | 49.05 Bn | 1.50 Bn | 15.10 Bn |
| 6 | State Street | 48.84 Bn | 48.84 Bn | - | - |
| 7 | Interactive Brokers | 38.83 Bn | 32.29 Bn | - | 224.85 Bn |
| 8 | Northern Trust | 31.65 Bn | 31.65 Bn | - | 161.36 Bn |
| 9 | Cboe Global Markets | 27.38 Bn | 19.03 Bn | 731.60 Mn | 4.94 Bn |
| 10 | Fabric.AI | 9.48 Mn | -39.39 Mn | - | 18.99 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 18.99 Mn |
| Mar 31, 2026 | 8.29 Mn |
| Dec 31, 2025 | 7.68 Mn |
| Sep 30, 2025 | 7.30 Mn |
| Jun 30, 2025 | 7.76 Mn |
| Mar 31, 2025 | 11.87 Mn |
| Dec 31, 2024 | 14.40 Mn |
| Sep 30, 2024 | 20.10 Mn |
| Jun 30, 2024 | 25.39 Mn |
| Mar 31, 2024 | 28.61 Mn |
| Dec 31, 2023 | 25.41 Mn |
| Sep 30, 2023 | 12.42 Mn |
| Dec 31, 2022 | 2.86 Mn |
| Sep 30, 2022 | 3.50 Mn |
| Jun 30, 2022 | 2.62 Mn |
| Mar 31, 2022 | 3.42 Mn |
| Dec 31, 2021 | 4.52 Mn |
| Sep 30, 2021 | 6.57 Mn |
| Jun 30, 2021 | 5.01 Mn |
| Mar 31, 2021 | 3.03 Mn |
API Access
Fabric.AI 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=FABC&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "ticker": "FABC", "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=FABC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();