Innodata (INOD) Total Liabilities (2010 - 2026)
Innodata (INOD) posted Total Liabilities of $197.06 million for Q2 2026, up 328.6% from $45.98 million a year earlier and up 139.6% from the prior quarter.
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Analysis
Innodata (INOD) Total Liabilities (2010 - 2026) Analysis & Trends
At the end of FY2025, Innodata's Total Liabilities came in at $61.45 million, up 22.7% from FY2024.
- Annual Total Liabilities has increased for three consecutive years, with a five-year compound annual growth rate of 17.3% (FY2020 to FY2025).
- In prior years, Innodata's Total Liabilities was $50.06 million in FY2024 (+45.4%), $34.44 million in FY2023 (+17.7%), $29.27 million in FY2022 (-0.1%) and $29.29 million in FY2021 (+6.1%).
- The Q2 2026 figure stands as the highest quarterly Total Liabilities in data going back to Q4 2010.
- On a year-over-year basis, Total Liabilities has increased in each of the last 14 quarters, with growth averaging 72.1% over the last eight quarters.
- The strongest year-over-year quarter for Total Liabilities in the past five years was Q2 2026, with growth of 328.6%; the weakest was Q2 2022, with a decline of 2.1%.
- According to Business Quant data, Total Liabilities for the three prior quarters was $82.23 million (Q1 2026), $61.45 million (Q4 2025) and $55.59 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Infosys | 52.03 Bn | 38.53 Bn | 1.60 Bn | 21.56 Bn |
| 2 | Cognizant Technology Solutions | 31.75 Bn | 24.91 Bn | 1.83 Bn | 6.36 Bn |
| 3 | Wipro | 21.48 Bn | 16.18 Bn | 738.00 Mn | 5.71 Bn |
| 4 | Cdw | 19.70 Bn | 17.69 Bn | 1.32 Bn | 14.81 Bn |
| 5 | Td Synnex | 19.65 Bn | 13.81 Bn | 1.43 Bn | 32.54 Bn |
| 6 | Cgi | 17.59 Bn | 15.39 Bn | - | - |
| 7 | Arrow Electronics | 11.05 Bn | 10.00 Bn | 1.13 Bn | 31.30 Bn |
| 8 | Avnet | 7.49 Bn | 6.67 Bn | 865.03 Mn | 10.40 Bn |
| 9 | EPAM Systems | 6.82 Bn | 2.46 Bn | 429.57 Mn | 1.05 Bn |
| 10 | Innodata | 1.84 Bn | 1.31 Bn | 42.46 Mn | 197.06 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 197.06 Mn |
| Mar 31, 2026 | 82.23 Mn |
| Dec 31, 2025 | 61.45 Mn |
| Sep 30, 2025 | 55.59 Mn |
| Jun 30, 2025 | 45.98 Mn |
| Mar 31, 2025 | 49.81 Mn |
| Dec 31, 2024 | 50.06 Mn |
| Sep 30, 2024 | 41.16 Mn |
| Jun 30, 2024 | 37.70 Mn |
| Mar 31, 2024 | 36.72 Mn |
| Dec 31, 2023 | 34.44 Mn |
| Sep 30, 2023 | 33.57 Mn |
| Jun 30, 2023 | 30.95 Mn |
| Mar 31, 2023 | 30.72 Mn |
| Dec 31, 2022 | 29.27 Mn |
| Sep 30, 2022 | 30.03 Mn |
| Jun 30, 2022 | 28.90 Mn |
| Mar 31, 2022 | 30.16 Mn |
| Dec 31, 2021 | 29.29 Mn |
| Sep 30, 2021 | 28.11 Mn |
API Access
Innodata 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=INOD&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "INOD", "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=INOD&period=max&api_key=YOUR_API_KEY");
const data = await res.json();