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.
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 Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Infosys | 42.66 Bn | 42.72 Bn | 1.60 Bn | 6.69 Bn |
| 2 | Cognizant Technology Solutions | 25.65 Bn | 18.82 Bn | 1.83 Bn | 6.36 Bn |
| 3 | Td Synnex | 20.51 Bn | 14.54 Bn | 1.34 Bn | 29.56 Bn |
| 4 | Cdw | 16.33 Bn | 14.32 Bn | 1.32 Bn | 14.81 Bn |
| 5 | Cgi | 15.07 Bn | 12.85 Bn | - | - |
| 6 | Arrow Electronics | 11.72 Bn | 10.75 Bn | 1.13 Bn | 31.30 Bn |
| 7 | Avnet | 8.33 Bn | 7.51 Bn | 865.03 Mn | 10.40 Bn |
| 8 | Ingram Micro Holding | 6.23 Bn | 1.84 Bn | 958.68 Mn | 17.25 Bn |
| 9 | EPAM Systems | 5.55 Bn | 1.19 Bn | 429.57 Mn | 1.05 Bn |
| 10 | Intelligent Protection Management | 23.33 Mn | -487,682.59 | 2.67 Mn | 12.20 Mn |
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 |
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_KEY
import 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();