Intelligent Protection Management (IPM) Other Operating Expenses (2010 - 2026)
Intelligent Protection Management's Other Operating Expenses came in at $1.15 million for Q2 2026, up 37.1% from $839,397 a year earlier and up 30.8% from the prior quarter.
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Analysis
Intelligent Protection Management (IPM) Other Operating Expenses (2010 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Intelligent Protection Management reported Other Operating Expenses of $4.4 million, up 223.6% year-over-year; for FY2025, it was $3.97 million.
- Other Operating Expenses carries a five-year compound annual growth rate of -7.5% (FY2020 to FY2025).
- Going back by year, Other Operating Expenses was $277,244 in FY2024 (-8.2%), $302,171 in FY2023 (-96.0%), $7.51 million in FY2022 (+2.5%) and $7.33 million in FY2021 (+25.2%).
- The five-year range for quarterly Other Operating Expenses is -$3.99 million (Q4 2023) to $2.23 million (Q3 2021).
- Year-over-year, Other Operating Expenses increased in five of the last six quarters, with growth averaging 137.6%.
- The fastest year-over-year change in Other Operating Expenses over five years came in Q3 2025 (growth of 441.9%), and the weakest in Q1 2024 (a decline of 82.3%).
- Business Quant data shows IPM's Other Operating Expenses at $879,638 (Q1 2026), $1.02 million (Q4 2025) and $1.35 million (Q3 2025) in the three quarters before Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Infosys | 51.35 Bn | -77.91 Bn | 1.60 Bn |
| 2 | Cognizant Technology Solutions | 30.16 Bn | 24.12 Bn | 1.91 Bn |
| 3 | Wipro | 22.58 Bn | 17.72 Bn | 745.00 Mn |
| 4 | Cdw | 19.64 Bn | 16.54 Bn | 1.39 Bn |
| 5 | Cgi | 18.54 Bn | 16.34 Bn | - |
| 6 | Td Synnex | 17.34 Bn | 11.50 Bn | 1.43 Bn |
| 7 | Arrow Electronics | 9.29 Bn | 8.24 Bn | 1.13 Bn |
| 8 | EPAM Systems | 8.17 Bn | 4.08 Bn | 445.94 Mn |
| 9 | ExlService Holdings | 6.55 Bn | 5.35 Bn | 241.14 Mn |
| 10 | Intelligent Protection Management | 21.07 Mn | -2.75 Mn | 2.67 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 382,861.00 |
| Mar 31, 2026 | 101,609.00 |
| Dec 31, 2025 | 210,599.00 |
| Sep 30, 2025 | 507,181.00 |
| Jun 30, 2025 | 4.25 Mn |
| Mar 31, 2025 | 167,629.00 |
| Dec 31, 2024 | 3.20 Mn |
| Sep 30, 2024 | -697,995.00 |
| Jun 30, 2024 | 315,889.00 |
| Mar 31, 2024 | 59,311.00 |
| Dec 31, 2023 | -2.71 Mn |
| Sep 30, 2023 | 1.04 Mn |
| Jun 30, 2023 | 343,045.00 |
| Mar 31, 2023 | 1.06 Mn |
| Dec 31, 2022 | 1.04 Mn |
| Sep 30, 2022 | 1.15 Mn |
| Jun 30, 2022 | -38,772.00 |
| Mar 31, 2022 | -7,886.00 |
| Dec 31, 2021 | 1.04 Mn |
| Jun 30, 2021 | 1.07 Mn |
API Access
Intelligent Protection Management Other Operating Expenses 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=other-operating-expenses&ticker=IPM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-operating-expenses", "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=other-operating-expenses&ticker=IPM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();