Stewart Information Services (STC) Retained Earnings (2010 - 2026)
Stewart Information Services (STC) posted Retained Earnings of $1.17 billion for Q2 2026, up 6.5% from $1.1 billion a year earlier and up 1.8% from the prior quarter.
Stewart Information Services (STC) Retained Earnings (2010 - 2026) Analysis & Trends
At the end of FY2025, Stewart Information Services' Retained Earnings came in at $1.15 billion, up 5.1% from FY2024.
- Annual Retained Earnings shows a five-year compound annual growth rate of 10.7% (FY2020 to FY2025).
- In prior years, Stewart Information Services' Retained Earnings was $1.09 billion in FY2024 (+1.7%), $1.07 billion in FY2023 (-1.9%), $1.09 billion in FY2022 (+12.0%) and $974.8 million in FY2021 (+41.5%).
- The Q2 2026 figure stands as the highest quarterly Retained Earnings in data going back to Q4 2010.
- On a year-over-year basis, Retained Earnings has increased in each of the last eight quarters, with growth averaging 3.6% over the last eight quarters.
- The strongest year-over-year quarter for Retained Earnings in the past five years was Q4 2021, with growth of 41.5%; the weakest was Q4 2023, with a decline of 1.9%.
- According to Business Quant data, Retained Earnings for the three prior quarters was $1.15 billion (Q1 2026), $1.15 billion (Q4 2025) and $1.13 billion (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Retained Earnings (Qtr) |
|---|---|---|---|---|---|
| 1 | Berkshire Hathaway | 1,083.69 Bn | -333.79 Bn | 55.86 Bn | 798.96 Bn |
| 2 | Chubb | 127.81 Bn | 79.86 Bn | 9.13 Bn | 71.68 Bn |
| 3 | Progressive | 121.79 Bn | 97.63 Bn | 9.04 Bn | 32.26 Bn |
| 4 | Marsh & Mclennan Companies | 80.80 Bn | 72.54 Bn | - | 29.30 Bn |
| 5 | Travelers Companies | 75.76 Bn | 52.01 Bn | 6.23 Bn | 58.35 Bn |
| 6 | Manulife Financial | 74.06 Bn | 75.27 Bn | - | - |
| 7 | Metlife | 61.12 Bn | -45.36 Bn | 7.82 Bn | 45.38 Bn |
| 8 | Arthur J. Gallagher | 58.82 Bn | 53.25 Bn | - | 6.59 Bn |
| 9 | Allstate | 57.81 Bn | 19.06 Bn | 8.73 Bn | 67.50 Bn |
| 10 | Stewart Information Services | 1.75 Bn | 533.81 Mn | 877.17 Mn | 1.17 Bn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.17 Bn |
| Mar 31, 2026 | 1.15 Bn |
| Dec 31, 2025 | 1.15 Bn |
| Sep 30, 2025 | 1.13 Bn |
| Jun 30, 2025 | 1.10 Bn |
| Mar 31, 2025 | 1.08 Bn |
| Dec 31, 2024 | 1.09 Bn |
| Sep 30, 2024 | 1.08 Bn |
| Jun 30, 2024 | 1.06 Bn |
| Mar 31, 2024 | 1.06 Bn |
| Dec 31, 2023 | 1.07 Bn |
| Sep 30, 2023 | 1.08 Bn |
| Jun 30, 2023 | 1.07 Bn |
| Mar 31, 2023 | 1.07 Bn |
| Dec 31, 2022 | 1.09 Bn |
| Sep 30, 2022 | 1.09 Bn |
| Jun 30, 2022 | 1.07 Bn |
| Mar 31, 2022 | 1.02 Bn |
| Dec 31, 2021 | 974.80 Mn |
| Sep 30, 2021 | 899.53 Mn |
Stewart Information Services 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=STC&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "retained-earnings", "ticker": "STC", "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=STC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();