George Risk Industries (RSKIA) Operating Expenses (2015 - 2026)
George Risk Industries' Operating Expenses came in at $1.32 million for fiscal Q1 2027 (quarter ended Jul 31, 2026), up 8.7% from $1.22 million a year earlier but down 1.3% from the prior quarter.
George Risk Industries (RSKIA) Operating Expenses (2015 - 2026) Analysis & Trends
Over the trailing twelve months to Jul 31, 2026, George Risk Industries reported Operating Expenses of $5.09 million, up 8.0% year-over-year; for FY2026 (ended Apr 30, 2026), it came in at $4.98 million, up 6.7% from FY2025.
- Operating Expenses has increased in each of the last three fiscal years, with a five-year compound annual growth rate of 4.4% (FY2021 to FY2026).
- Going back by fiscal year, Operating Expenses was $4.67 million in FY2025 (+2.6%), $4.55 million in FY2024 (+5.5%), $4.31 million in FY2023 (-1.2%) and $4.37 million in FY2022 (+8.6%).
- The five-year range for quarterly Operating Expenses is $1.02 million (fiscal Q3 2023) to $1.34 million (fiscal Q4 2026).
- Year-over-year, Operating Expenses has increased for three consecutive quarters, with growth averaging 4.9% over the last eight quarters.
- The fastest year-over-year change in Operating Expenses over five years came in fiscal Q4 2026 (growth of 14.6%), and the weakest in fiscal Q4 2023 (a decline of 4.2%).
- Business Quant data shows RSKIA's Operating Expenses at $1.34 million (Q4 2026), $1.25 million (Q3 2026) and $1.18 million (Q2 2026) in the three fiscal quarters before Q1 2027.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Accenture | 122.50 Bn | 82.91 Bn | 6.13 Bn | 15.54 Bn |
| 2 | Cintas | 78.05 Bn | 77.24 Bn | 1.48 Bn | 792.12 Mn |
| 3 | Iron Mountain | 33.02 Bn | 32.53 Bn | 1.07 Bn | 1.66 Bn |
| 4 | APi | 16.68 Bn | 13.72 Bn | 703.00 Mn | 528.00 Mn |
| 5 | Rollins | 14.49 Bn | 14.04 Bn | 569.95 Mn | 877.22 Mn |
| 6 | Aramark | 14.11 Bn | 12.13 Bn | 430.34 Mn | 4.84 Bn |
| 7 | UL Solutions | 13.27 Bn | 12.05 Bn | 417.00 Mn | 267.00 Mn |
| 8 | Gartner | 11.78 Bn | 5.47 Bn | 1.19 Bn | 1.30 Bn |
| 9 | Rentokil Initial | 9.98 Bn | 3.32 Bn | - | - |
| 10 | George Risk Industries | 107.01 Mn | -81.27 Mn | 3.23 Mn | 1.32 Mn |
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | 1.32 Mn |
| Apr 30, 2026 | 1.34 Mn |
| Jan 31, 2026 | 1.25 Mn |
| Oct 31, 2025 | 1.18 Mn |
| Jul 31, 2025 | 1.22 Mn |
| Apr 30, 2025 | 1.17 Mn |
| Jan 31, 2025 | 1.10 Mn |
| Oct 31, 2024 | 1.23 Mn |
| Jul 31, 2024 | 1.17 Mn |
| Apr 30, 2024 | 1.20 Mn |
| Jan 31, 2024 | 1.14 Mn |
| Oct 31, 2023 | 1.14 Mn |
| Jul 31, 2023 | 1.08 Mn |
| Apr 30, 2023 | 1.07 Mn |
| Jan 31, 2023 | 1.02 Mn |
| Oct 31, 2022 | 1.13 Mn |
| Jul 31, 2022 | 1.09 Mn |
| Apr 30, 2022 | 1.12 Mn |
| Jan 31, 2022 | 1.05 Mn |
| Oct 31, 2021 | 1.09 Mn |
George Risk Industries 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=operating-expenses&ticker=RSKIA&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "RSKIA", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=RSKIA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();