Intelligent Protection Management (IPM) Total Liabilities (2010 - 2026)
Intelligent Protection Management's Total Liabilities came in at $12.2 million for Q2 2026, up 22.7% from $9.95 million a year earlier and up 1.1% from the prior quarter.
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Analysis
Intelligent Protection Management (IPM) Total Liabilities (2010 - 2026) Analysis & Trends
At the end of FY2025, Intelligent Protection Management's Total Liabilities was $7.85 million, up 97.7% from FY2024.
- Total Liabilities carries a five-year compound annual growth rate of 15.9% (FY2020 to FY2025).
- Going back by year, Total Liabilities was $3.97 million in FY2024 (+5.9%), $3.75 million in FY2023 (-15.8%), $4.46 million in FY2022 (+16.3%) and $3.83 million in FY2021 (+2.1%).
- The Q2 2026 figure represents the highest quarterly Total Liabilities in data going back to Q4 2010.
- Year-over-year, Total Liabilities has increased for eight consecutive quarters, with growth averaging 79.7% over the last eight quarters.
- The fastest year-over-year change in Total Liabilities over five years came in Q1 2025 (growth of 210.0%), and the weakest in Q1 2024 (a decline of 18.3%).
- Business Quant data shows IPM's Total Liabilities at $12.07 million (Q1 2026), $7.85 million (Q4 2025) and $8.47 million (Q3 2025) in the three quarters before Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Infosys | 51.35 Bn | -77.91 Bn | 1.60 Bn | 6.67 Bn |
| 2 | Cognizant Technology Solutions | 30.16 Bn | 24.12 Bn | 1.91 Bn | 6.60 Bn |
| 3 | Wipro | 22.58 Bn | 17.72 Bn | 745.00 Mn | 5.88 Bn |
| 4 | Cdw | 19.64 Bn | 16.54 Bn | 1.39 Bn | 16.95 Bn |
| 5 | Cgi | 18.54 Bn | 16.34 Bn | - | - |
| 6 | Td Synnex | 17.34 Bn | 11.50 Bn | 1.43 Bn | 32.54 Bn |
| 7 | Arrow Electronics | 9.29 Bn | 8.24 Bn | 1.13 Bn | 31.30 Bn |
| 8 | EPAM Systems | 8.17 Bn | 4.08 Bn | 445.94 Mn | 1.09 Bn |
| 9 | ExlService Holdings | 6.55 Bn | 5.35 Bn | 241.14 Mn | 1.15 Bn |
| 10 | Intelligent Protection Management | 21.07 Mn | -2.75 Mn | 2.67 Mn | 12.20 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 12.20 Mn |
| Mar 31, 2026 | 12.07 Mn |
| Dec 31, 2025 | 7.85 Mn |
| Sep 30, 2025 | 8.47 Mn |
| Jun 30, 2025 | 9.95 Mn |
| Mar 31, 2025 | 10.06 Mn |
| Dec 31, 2024 | 3.97 Mn |
| Sep 30, 2024 | 4.39 Mn |
| Jun 30, 2024 | 3.67 Mn |
| Mar 31, 2024 | 3.25 Mn |
| Dec 31, 2023 | 3.75 Mn |
| Sep 30, 2023 | 3.74 Mn |
| Jun 30, 2023 | 3.91 Mn |
| Mar 31, 2023 | 3.98 Mn |
| Dec 31, 2022 | 4.46 Mn |
| Sep 30, 2022 | 4.42 Mn |
| Jun 30, 2022 | 4.49 Mn |
| Mar 31, 2022 | 3.08 Mn |
| Dec 31, 2021 | 3.83 Mn |
| Sep 30, 2021 | 3.72 Mn |
API Access
Intelligent Protection Management 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=IPM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "IPM", "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=IPM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();