George Risk Industries (RSKIA) Inventory (2015 - 2026)
George Risk Industries' Inventory was $13.06 million in fiscal Q1 2027 (quarter ended Jul 31, 2026), up 23.3% from $10.59 million a year earlier and up 10.4% from the prior quarter.
George Risk Industries (RSKIA) Inventory (2015 - 2026) Analysis & Trends
At the end of FY2026 (ended Apr 30, 2026), Inventory at George Risk Industries came in at $11.82 million, up 10.1% from FY2025.
- Inventory shows a five-year compound annual growth rate of 16.0% (FY2021 to FY2026).
- In earlier fiscal years, Inventory was $10.74 million in FY2025 (-7.1%), $11.56 million in FY2024 (+1.0%), $11.44 million in FY2023 (+44.1%) and $7.94 million in FY2022 (+41.2%).
- The fiscal Q1 2027 figure marks the highest quarterly Inventory in data going back to fiscal Q4 2015.
- Compared with a year earlier, Inventory has increased for four straight quarters, with growth averaging 0.6% over the last eight quarters.
- The best year-over-year quarter for Inventory over five years was fiscal Q3 2023 (growth of 50.2%); the worst was fiscal Q2 2025 (a decline of 12.1%).
- Per Business Quant data, RSKIA's Inventory in the three fiscal quarters before Q1 2027 was $11.82 million (Q4 2026), $11.6 million (Q3 2026) and $11.09 million (Q2 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Inventory (Qtr) |
|---|---|---|---|---|---|
| 1 | Accenture | 172.92 Bn | 132.01 Bn | 5.98 Bn | - |
| 2 | Cintas | 90.00 Bn | 89.09 Bn | 1.55 Bn | 433.29 Mn |
| 3 | Iron Mountain | 32.99 Bn | 32.50 Bn | 1.06 Bn | - |
| 4 | Rollins | 18.37 Bn | 17.91 Bn | 582.90 Mn | 42.22 Mn |
| 5 | APi | 18.18 Bn | 15.39 Bn | 770.00 Mn | 182.00 Mn |
| 6 | UL Solutions | 16.47 Bn | 14.51 Bn | 423.00 Mn | - |
| 7 | Aramark | 14.29 Bn | 12.30 Bn | 430.34 Mn | 433.62 Mn |
| 8 | Rentokil Initial | 11.99 Bn | 5.51 Bn | - | 314.00 Mn |
| 9 | Gartner | 11.92 Bn | 5.41 Bn | 1.07 Bn | - |
| 10 | George Risk Industries | 99.58 Mn | -88.70 Mn | 3.23 Mn | 13.06 Mn |
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | 13.06 Mn |
| Apr 30, 2026 | 11.82 Mn |
| Jan 31, 2026 | 11.60 Mn |
| Oct 31, 2025 | 11.09 Mn |
| Jul 31, 2025 | 10.59 Mn |
| Apr 30, 2025 | 10.74 Mn |
| Jan 31, 2025 | 11.37 Mn |
| Oct 31, 2024 | 11.08 Mn |
| Jul 31, 2024 | 11.24 Mn |
| Apr 30, 2024 | 11.56 Mn |
| Jan 31, 2024 | 12.09 Mn |
| Oct 31, 2023 | 12.61 Mn |
| Jul 31, 2023 | 11.96 Mn |
| Apr 30, 2023 | 11.44 Mn |
| Jan 31, 2023 | 10.30 Mn |
| Oct 31, 2022 | 9.64 Mn |
| Jul 31, 2022 | 8.84 Mn |
| Apr 30, 2022 | 7.94 Mn |
| Jan 31, 2022 | 6.86 Mn |
| Oct 31, 2021 | 7.08 Mn |
George Risk Industries Inventory 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=inventory&ticker=RSKIA&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "inventory", "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=inventory&ticker=RSKIA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();