George Risk Industries (RSKIA) Retained Earnings (2015 - 2026)
George Risk Industries' Retained Earnings was $67.76 million in fiscal Q1 2027 (quarter ended Jul 31, 2026), up 7.8% from $62.87 million a year earlier and up 3.3% from the prior quarter.
George Risk Industries (RSKIA) Retained Earnings (2015 - 2026) Analysis & Trends
At the end of FY2026 (ended Apr 30, 2026), Retained Earnings at George Risk Industries came in at $65.57 million, up 11.0% from FY2025.
- Retained Earnings has now increased for 11 consecutive fiscal years, with a five-year compound annual growth rate of 5.7% (FY2021 to FY2026).
- In earlier fiscal years, Retained Earnings was $59.07 million in FY2025 (+3.9%), $56.84 million in FY2024 (+8.3%), $52.48 million in FY2023 (+3.2%) and $50.84 million in FY2022 (+2.2%).
- The fiscal Q1 2027 figure marks the highest quarterly Retained Earnings in data going back to fiscal Q4 2015.
- Compared with a year earlier, Retained Earnings has increased for 15 straight quarters, with growth averaging 7.3% over the last eight quarters.
- The best year-over-year quarter for Retained Earnings over five years was fiscal Q2 2022 (growth of 19.9%); the worst was fiscal Q2 2023 (a decline of 2.6%).
- Per Business Quant data, RSKIA's Retained Earnings in the three fiscal quarters before Q1 2027 was $65.57 million (Q4 2026), $62.8 million (Q3 2026) and $60.32 million (Q2 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Retained Earnings (Qtr) |
|---|---|---|---|---|---|
| 1 | Accenture | 122.50 Bn | 82.91 Bn | 6.13 Bn | 24.03 Bn |
| 2 | Cintas | 78.05 Bn | 77.24 Bn | 1.48 Bn | 13.07 Bn |
| 3 | Iron Mountain | 33.02 Bn | 32.53 Bn | 1.07 Bn | 5.69 Bn |
| 4 | APi | 16.68 Bn | 13.72 Bn | 703.00 Mn | 673.00 Mn |
| 5 | Rollins | 14.49 Bn | 14.04 Bn | 569.95 Mn | 794.96 Mn |
| 6 | Aramark | 14.11 Bn | 12.13 Bn | 430.34 Mn | 652.31 Mn |
| 7 | UL Solutions | 13.27 Bn | 12.05 Bn | 417.00 Mn | 750.00 Mn |
| 8 | Gartner | 11.78 Bn | 5.47 Bn | 1.19 Bn | 7.22 Bn |
| 9 | Rentokil Initial | 9.98 Bn | 3.32 Bn | - | - |
| 10 | George Risk Industries | 107.01 Mn | -81.27 Mn | 3.23 Mn | 67.76 Mn |
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | 67.76 Mn |
| Apr 30, 2026 | 65.57 Mn |
| Jan 31, 2026 | 62.80 Mn |
| Oct 31, 2025 | 60.32 Mn |
| Jul 31, 2025 | 62.87 Mn |
| Apr 30, 2025 | 59.07 Mn |
| Jan 31, 2025 | 58.47 Mn |
| Oct 31, 2024 | 56.86 Mn |
| Jul 31, 2024 | 59.54 Mn |
| Apr 30, 2024 | 56.84 Mn |
| Jan 31, 2024 | 54.84 Mn |
| Oct 31, 2023 | 51.60 Mn |
| Jul 31, 2023 | 54.86 Mn |
| Apr 30, 2023 | 52.48 Mn |
| Jan 31, 2023 | 51.39 Mn |
| Oct 31, 2022 | 49.38 Mn |
| Jul 31, 2022 | 51.73 Mn |
| Apr 30, 2022 | 50.84 Mn |
| Jan 31, 2022 | 50.87 Mn |
| Oct 31, 2021 | 50.71 Mn |
George Risk Industries Retained Earnings 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=retained-earnings&ticker=RSKIA&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "retained-earnings", "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=retained-earnings&ticker=RSKIA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();