Berkley W R (WRB) Operating Expenses (2009 - 2026)
Berkley W R (WRB) posted Operating Expenses of $3.14 billion for Q2 2026, down 0.3% from $3.15 billion a year earlier but up 2.2% from the prior quarter.
Berkley W R (WRB) Operating Expenses (2009 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Berkley W R was $12.48 billion, up 3.8% year-over-year; for FY2025, it was $12.43 billion, up 9.3% from FY2024.
- Annual Operating Expenses has increased for seven consecutive years, with a five-year compound annual growth rate of 10.9% (FY2020 to FY2025).
- In prior years, Berkley W R's Operating Expenses was $11.37 billion in FY2024 (+9.5%), $10.39 billion in FY2023 (+10.0%), $9.45 billion in FY2022 (+15.6%) and $8.17 billion in FY2021 (+10.5%).
- Quarterly Operating Expenses has run from a low of $2.09 billion in Q3 2021 to a high of $3.15 billion in Q4 2025 over five years.
- On a year-over-year basis, Operating Expenses increased in seven of the last eight quarters, with growth averaging 7.4%.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q1 2022, with growth of 17.3%; the weakest was Q2 2026, with a decline of 0.3%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $3.07 billion (Q1 2026), $3.15 billion (Q4 2025) and $3.12 billion (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Berkshire Hathaway | 1,248.67 Bn | -185.49 Bn | 56.71 Bn | 91.43 Bn |
| 2 | Chubb | 141.22 Bn | 92.15 Bn | 8.67 Bn | 12.79 Bn |
| 3 | Progressive | 134.26 Bn | 109.78 Bn | 8.29 Bn | 19.96 Bn |
| 4 | Marsh & Mclennan Companies | 98.32 Bn | 90.72 Bn | - | 5.65 Bn |
| 5 | Travelers Companies | 82.09 Bn | 59.57 Bn | 5.93 Bn | 10.04 Bn |
| 6 | Manulife Financial | 75.36 Bn | -19.02 Bn | - | 899.35 Mn |
| 7 | Arthur J. Gallagher | 72.54 Bn | 67.17 Bn | 3.33 Bn | 3.46 Bn |
| 8 | Aon | 71.33 Bn | 50.56 Bn | - | 3.29 Bn |
| 9 | Allstate | 65.04 Bn | 22.10 Bn | -9.85 Bn | 14.73 Bn |
| 10 | Berkley W R | 28.55 Bn | 13.22 Bn | 1.74 Bn | 3.16 Bn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 3.16 Bn |
| Jun 30, 2026 | 3.14 Bn |
| Mar 31, 2026 | 3.07 Bn |
| Dec 31, 2025 | 3.15 Bn |
| Sep 30, 2025 | 3.12 Bn |
| Jun 30, 2025 | 3.15 Bn |
| Mar 31, 2025 | 3.01 Bn |
| Dec 31, 2024 | 2.94 Bn |
| Sep 30, 2024 | 2.93 Bn |
| Jun 30, 2024 | 2.83 Bn |
| Mar 31, 2024 | 2.68 Bn |
| Dec 31, 2023 | 2.72 Bn |
| Sep 30, 2023 | 2.61 Bn |
| Jun 30, 2023 | 2.54 Bn |
| Mar 31, 2023 | 2.52 Bn |
| Dec 31, 2022 | 2.54 Bn |
| Sep 30, 2022 | 2.44 Bn |
| Jun 30, 2022 | 2.29 Bn |
| Mar 31, 2022 | 2.18 Bn |
| Dec 31, 2021 | 2.22 Bn |
Berkley W R 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=WRB&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "WRB", "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=WRB&period=max&api_key=YOUR_API_KEY");
const data = await res.json();