i3 Verticals (IIIV) Accumulated Expenses (2017 - 2026)
i3 Verticals (IIIV) posted Accumulated Expenses of $21.03 million for fiscal Q3 2026 (quarter ended Jun 30, 2026), down 4.1% from $21.92 million a year earlier but up 5.0% from the prior quarter.
i3 Verticals (IIIV) Accumulated Expenses (2017 - 2026) Analysis & Trends
At the end of FY2025 (ended Sep 30, 2025), i3 Verticals' Accumulated Expenses came in at $24.53 million, down 72.2% from FY2024.
- Annual Accumulated Expenses shows a five-year compound annual growth rate of 0.4% (FY2020 to FY2025).
- In prior fiscal years, i3 Verticals' Accumulated Expenses was $88.25 million in FY2024 (+162.8%), $33.58 million in FY2023 (-41.9%), $57.83 million in FY2022 (+13.8%) and $50.82 million in FY2021 (+111.2%).
- Quarterly Accumulated Expenses has run from a low of $20.03 million in fiscal Q2 2026 to a high of $93.7 million in fiscal Q1 2022 over five years.
- On a year-over-year basis, Accumulated Expenses has declined in each of the last six quarters, with growth averaging 16.4% over the last eight quarters.
- The strongest year-over-year quarter for Accumulated Expenses in the past five years was fiscal Q1 2022, with growth of 250.3%; the weakest was fiscal Q1 2026, with a decline of 75.0%.
- According to Business Quant data, Accumulated Expenses for the three prior fiscal quarters was $20.03 million (Q2 2026), $20.74 million (Q1 2026) and $24.53 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Palantir Technologies | 386.60 Bn | 351.42 Bn | 1.93 Bn |
| 2 | Oracle | 343.94 Bn | 216.07 Bn | - |
| 3 | Sap Se | 272.35 Bn | 199.75 Bn | 8.64 Bn |
| 4 | Salesforce | 175.46 Bn | 131.33 Bn | 8.70 Bn |
| 5 | Automatic Data Processing | 122.07 Bn | 108.86 Bn | 2.53 Bn |
| 6 | ServiceNow | 105.47 Bn | 84.73 Bn | 2.90 Bn |
| 7 | Intuit | 94.25 Bn | 73.60 Bn | 3.44 Bn |
| 8 | Relx | 73.66 Bn | 72.75 Bn | - |
| 9 | Strategy | 51.78 Bn | 38.91 Bn | 89.63 Mn |
| 10 | i3 Verticals | 370.24 Mn | 256.25 Mn | - |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 21.03 Mn |
| Mar 31, 2026 | 20.03 Mn |
| Dec 31, 2025 | 20.74 Mn |
| Sep 30, 2025 | 24.53 Mn |
| Jun 30, 2025 | 21.92 Mn |
| Mar 31, 2025 | 22.73 Mn |
| Dec 31, 2024 | 83.00 Mn |
| Sep 30, 2024 | 88.25 Mn |
| Jun 30, 2024 | 22.83 Mn |
| Mar 31, 2024 | 26.85 Mn |
| Dec 31, 2023 | 33.08 Mn |
| Sep 30, 2023 | 33.58 Mn |
| Jun 30, 2023 | 46.51 Mn |
| Mar 31, 2023 | 55.41 Mn |
| Dec 31, 2022 | 50.97 Mn |
| Sep 30, 2022 | 57.83 Mn |
| Jun 30, 2022 | 63.88 Mn |
| Mar 31, 2022 | 71.38 Mn |
| Dec 31, 2021 | 93.70 Mn |
| Sep 30, 2021 | 50.82 Mn |
i3 Verticals Accumulated 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=accumulated-expenses&ticker=IIIV&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "IIIV", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=accumulated-expenses&ticker=IIIV&period=max&api_key=YOUR_API_KEY");
const data = await res.json();