George Risk Industries (RSKIA) Assets (2015 - 2026)
George Risk Industries (RSKIA) posted Assets of $74.18 million for fiscal Q1 2027 (quarter ended Jul 31, 2026), up 8.7% from $68.21 million a year earlier and up 3.9% from the prior quarter.
George Risk Industries (RSKIA) Assets (2015 - 2026) Analysis & Trends
At the end of FY2026 (ended Apr 30, 2026), George Risk Industries' Assets came in at $71.37 million, up 12.7% from FY2025.
- Annual Assets has increased for four consecutive fiscal years, with a five-year compound annual growth rate of 5.7% (FY2021 to FY2026).
- In prior fiscal years, George Risk Industries' Assets was $63.34 million in FY2025 (+4.2%), $60.78 million in FY2024 (+8.6%), $55.95 million in FY2023 (+3.6%) and $54.03 million in FY2022 (-0.2%).
- The fiscal Q1 2027 figure stands as the highest quarterly Assets in data going back to fiscal Q4 2015.
- On a year-over-year basis, Assets has increased in each of the last 14 quarters, with growth averaging 8.4% over the last eight quarters.
- The strongest year-over-year quarter for Assets in the past five years was fiscal Q2 2022, with growth of 20.1%; the weakest was fiscal Q2 2023, with a decline of 6.0%.
- According to Business Quant data, Assets for the three prior fiscal quarters was $71.37 million (Q4 2026), $68.36 million (Q3 2026) and $66.18 million (Q2 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Assets (Qtr) |
|---|---|---|---|---|---|
| 1 | Accenture | 122.50 Bn | 82.91 Bn | 6.13 Bn | 68.81 Bn |
| 2 | Cintas | 78.05 Bn | 77.24 Bn | 1.48 Bn | 10.53 Bn |
| 3 | Iron Mountain | 33.02 Bn | 32.53 Bn | 1.07 Bn | 21.96 Bn |
| 4 | APi | 16.68 Bn | 13.72 Bn | 703.00 Mn | 9.95 Bn |
| 5 | Rollins | 14.49 Bn | 14.04 Bn | 569.95 Mn | 3.35 Bn |
| 6 | Aramark | 14.11 Bn | 12.13 Bn | 430.34 Mn | 13.97 Bn |
| 7 | UL Solutions | 13.27 Bn | 12.05 Bn | 417.00 Mn | 3.12 Bn |
| 8 | Gartner | 11.78 Bn | 5.47 Bn | 1.19 Bn | 7.19 Bn |
| 9 | Rentokil Initial | 9.98 Bn | 3.32 Bn | - | 22.00 Mn |
| 10 | George Risk Industries | 107.01 Mn | -81.27 Mn | 3.23 Mn | 74.18 Mn |
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | 74.18 Mn |
| Apr 30, 2026 | 71.37 Mn |
| Jan 31, 2026 | 68.36 Mn |
| Oct 31, 2025 | 66.18 Mn |
| Jul 31, 2025 | 68.21 Mn |
| Apr 30, 2025 | 63.34 Mn |
| Jan 31, 2025 | 63.72 Mn |
| Oct 31, 2024 | 62.79 Mn |
| Jul 31, 2024 | 64.76 Mn |
| Apr 30, 2024 | 60.78 Mn |
| Jan 31, 2024 | 59.07 Mn |
| Oct 31, 2023 | 54.25 Mn |
| Jul 31, 2023 | 58.50 Mn |
| Apr 30, 2023 | 55.95 Mn |
| Jan 31, 2023 | 54.92 Mn |
| Oct 31, 2022 | 52.11 Mn |
| Jul 31, 2022 | 55.52 Mn |
| Apr 30, 2022 | 54.03 Mn |
| Jan 31, 2022 | 55.10 Mn |
| Oct 31, 2021 | 55.44 Mn |
George Risk Industries Assets 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=assets&ticker=RSKIA&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "assets", "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=assets&ticker=RSKIA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();