Coursera (COUR) Total Liabilities (2020 - 2026)
Coursera's Total Liabilities was $780.8 million in Q2 2026, up 121.3% from $352.9 million a year earlier and up 111.8% from the prior quarter.
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Analysis
Coursera (COUR) Total Liabilities (2020 - 2026) Analysis & Trends
At the end of FY2025, Total Liabilities at Coursera came in at $364.3 million, up 9.4% from FY2024.
- Total Liabilities has now increased for four consecutive years, though with a five-year compound annual growth rate of -10.6% (FY2020 to FY2025).
- In earlier years, Total Liabilities was $332.9 million in FY2024 (+9.4%), $304.33 million in FY2023 (+20.3%), $253.02 million in FY2022 (+16.4%) and $217.4 million in FY2021 (-66.0%).
- The Q2 2026 figure marks the highest quarterly Total Liabilities in data going back to Q4 2020.
- Compared with a year earlier, Total Liabilities has increased for 17 straight quarters, with growth averaging 23.4% over the last eight quarters.
- The best year-over-year quarter for Total Liabilities over five years was Q2 2026 (growth of 121.3%); the worst was Q4 2021 (a decline of 66.0%).
- Per Business Quant data, COUR's Total Liabilities in the three quarters before Q2 2026 was $368.7 million (Q1 2026), $364.3 million (Q4 2025) and $355.8 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 | Coursera | 1.27 Bn | -2.09 Bn | 173.40 Mn | 780.80 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 780.80 Mn |
| Mar 31, 2026 | 368.70 Mn |
| Dec 31, 2025 | 364.30 Mn |
| Sep 30, 2025 | 355.80 Mn |
| Jun 30, 2025 | 352.90 Mn |
| Mar 31, 2025 | 340.70 Mn |
| Dec 31, 2024 | 332.90 Mn |
| Sep 30, 2024 | 320.86 Mn |
| Jun 30, 2024 | 319.16 Mn |
| Mar 31, 2024 | 307.20 Mn |
| Dec 31, 2023 | 304.33 Mn |
| Sep 30, 2023 | 300.94 Mn |
| Jun 30, 2023 | 292.23 Mn |
| Mar 31, 2023 | 283.04 Mn |
| Dec 31, 2022 | 253.02 Mn |
| Sep 30, 2022 | 247.28 Mn |
| Jun 30, 2022 | 236.60 Mn |
| Mar 31, 2022 | 218.18 Mn |
| Dec 31, 2021 | 217.40 Mn |
| Sep 30, 2021 | 198.87 Mn |
API Access
Coursera 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=COUR&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "COUR", "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=COUR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();