Digital Brands (DBGI) Total Non-Current Liabilities (2020 - 2026)
Digital Brands (DBGI) reported Total Non-Current Liabilities of $46.11 million for Q2 2026, up 124.8% from $20.51 million a year earlier and up 5.8% from the prior quarter.
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Analysis
Digital Brands (DBGI) Total Non-Current Liabilities (2020 - 2026) Analysis & Trends
At the end of FY2025, Digital Brands posted Total Non-Current Liabilities of $35.69 million, up 69.9% from FY2024.
- Total Non-Current Liabilities has a five-year compound annual growth rate of 10.1% (FY2020 to FY2025).
- By year, Total Non-Current Liabilities came in at $21.01 million in FY2024 (-11.1%), $23.63 million in FY2023 (-18.8%), $29.09 million in FY2022 (-7.6%) and $31.48 million in FY2021 (+42.4%).
- The Q2 2026 figure ranks as the highest quarterly Total Non-Current Liabilities in data going back to Q4 2020.
- Year over year, Total Non-Current Liabilities has now increased in each of the last four quarters, with growth averaging 34.7% over the last eight quarters.
- The high point for year-over-year Total Non-Current Liabilities in five years was Q2 2026 (growth of 124.8%); the low point was Q2 2023 (a decline of 28.5%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $43.58 million (Q1 2026), $35.69 million (Q4 2025) and $25 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Nike | 55.58 Bn | 21.79 Bn | 4.80 Bn | - |
| 2 | Tapestry | 23.76 Bn | 19.72 Bn | 1.56 Bn | 5.46 Bn |
| 3 | Ralph Lauren | 22.75 Bn | 14.84 Bn | 1.44 Bn | 4.63 Bn |
| 4 | Deckers Outdoor | 12.32 Bn | 5.19 Bn | - | 384.05 Mn |
| 5 | Lululemon Athletica | 10.95 Bn | 5.21 Bn | 1.46 Bn | 3.63 Bn |
| 6 | Levi Strauss | 8.08 Bn | 4.66 Bn | 1.07 Bn | 4.29 Bn |
| 7 | V F | 6.77 Bn | 3.39 Bn | 917.04 Mn | 7.07 Bn |
| 8 | Gildan Activewear | 6.50 Bn | 5.42 Bn | 459.76 Mn | 4.37 Bn |
| 9 | Birkenstock Holding | 6.10 Bn | 4.42 Bn | 493.89 Mn | 2.70 Bn |
| 10 | Digital Brands | 1.30 Mn | -13.85 Mn | 324,265.00 | 46.11 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 46.11 Mn |
| Mar 31, 2026 | 43.58 Mn |
| Dec 31, 2025 | 35.69 Mn |
| Sep 30, 2025 | 25.00 Mn |
| Jun 30, 2025 | 20.51 Mn |
| Mar 31, 2025 | 38.06 Mn |
| Dec 31, 2024 | 21.01 Mn |
| Sep 30, 2024 | 23.17 Mn |
| Jun 30, 2024 | 22.12 Mn |
| Mar 31, 2024 | 21.77 Mn |
| Dec 31, 2023 | 23.63 Mn |
| Sep 30, 2023 | 22.32 Mn |
| Jun 30, 2023 | 22.88 Mn |
| Mar 31, 2023 | 28.72 Mn |
| Dec 31, 2022 | 29.01 Mn |
| Sep 30, 2022 | 27.11 Mn |
| Jun 30, 2022 | 30.83 Mn |
| Mar 31, 2022 | 33.46 Mn |
| Dec 31, 2021 | 31.48 Mn |
| Sep 30, 2021 | 26.12 Mn |
API Access
Digital Brands 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=DBGI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "ticker": "DBGI", "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=DBGI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();