Arlo Technologies (ARLO) Total Non-Current Liabilities (2017 - 2026)
Arlo Technologies (ARLO) recorded Total Non-Current Liabilities of $200.17 million in Q2 2026, up 0.6% from $198.89 million a year earlier and up 6.5% from the prior quarter.
Arlo Technologies (ARLO) Total Non-Current Liabilities (2017 - 2026) Analysis & Trends
At the end of FY2025, Arlo Technologies reported Total Non-Current Liabilities of $179.08 million, down 8.2% from FY2024.
- Annual Total Non-Current Liabilities has a five-year compound annual growth rate of -8.5% (FY2020 to FY2025).
- Across earlier years, Total Non-Current Liabilities came in at $195.12 million in FY2024 (+9.3%), $178.47 million in FY2023 (-1.7%), $181.56 million in FY2022 (-21.9%) and $232.4 million in FY2021 (-16.7%).
- Quarterly Total Non-Current Liabilities has ranged from $167.59 million in Q1 2023 to $232.4 million in Q4 2021 over the past five years.
- On a year-over-year basis, Total Non-Current Liabilities rose in six of the last eight quarters, with growth averaging 1.6%.
- Peak year-over-year performance for Total Non-Current Liabilities in the last five years was growth of 11.3% in Q1 2024, against a decline of 21.9% in Q4 2022 at the low end.
- Per Business Quant, the preceding three quarters came in at $187.93 million (Q1 2026), $179.08 million (Q4 2025) and $219.44 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 327.39 Bn | 312.46 Bn | 2.30 Bn | 19.68 Bn |
| 2 | CrowdStrike Holdings | 274.44 Bn | 254.87 Bn | 1.10 Bn | 6.57 Bn |
| 3 | Fortinet | 135.72 Bn | 121.65 Bn | 1.64 Bn | 9.17 Bn |
| 4 | Snowflake | 118.93 Bn | 106.25 Bn | 1.04 Bn | 6.45 Bn |
| 5 | Datadog | 100.80 Bn | 82.44 Bn | 881.34 Mn | 3.16 Bn |
| 6 | Zscaler | 42.42 Bn | 28.54 Bn | - | 5.20 Bn |
| 7 | Okta | 37.78 Bn | 27.88 Bn | 641.00 Mn | 2.11 Bn |
| 8 | Axon Enterprise | 34.60 Bn | 29.12 Bn | 546.45 Mn | 3.62 Bn |
| 9 | MongoDB | 31.40 Bn | 21.87 Bn | 569.77 Mn | 770.18 Mn |
| 10 | Arlo Technologies | 1.40 Bn | 917.19 Mn | 75.22 Mn | 200.17 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 28, 2026 | 200.17 Mn |
| Mar 29, 2026 | 187.93 Mn |
| Dec 31, 2025 | 179.08 Mn |
| Sep 28, 2025 | 219.44 Mn |
| Jun 29, 2025 | 198.89 Mn |
| Mar 30, 2025 | 190.81 Mn |
| Dec 31, 2024 | 195.12 Mn |
| Sep 29, 2024 | 211.75 Mn |
| Jun 30, 2024 | 193.01 Mn |
| Mar 31, 2024 | 186.51 Mn |
| Dec 31, 2023 | 178.47 Mn |
| Oct 1, 2023 | 204.13 Mn |
| Jul 2, 2023 | 184.22 Mn |
| Apr 2, 2023 | 167.59 Mn |
| Dec 31, 2022 | 181.56 Mn |
| Oct 2, 2022 | 231.35 Mn |
| Jul 3, 2022 | 195.28 Mn |
| Apr 3, 2022 | 197.73 Mn |
| Dec 31, 2021 | 232.40 Mn |
| Oct 3, 2021 | 219.51 Mn |
Arlo Technologies 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=ARLO&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "ticker": "ARLO", "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=ARLO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();