White Mountains Insurance (WTM) Operating Expenses (2009 - 2026)
White Mountains Insurance (WTM) reported Operating Expenses of $588.6 million for Q2 2026, up 14.8% from $512.7 million a year earlier and up 8.3% from the prior quarter.
Powered by 
Analysis
White Mountains Insurance (WTM) Operating Expenses (2009 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, White Mountains Insurance's Operating Expenses came in at $2.52 billion, up 20.2% year-over-year; for FY2025, it came in at $2.41 billion, up 25.1% from FY2024.
- Operating Expenses has increased for five consecutive years, with a five-year compound annual growth rate of 59.2% (FY2020 to FY2025).
- By year, Operating Expenses came in at $1.92 billion in FY2024 (+20.1%), $1.6 billion in FY2023 (+22.5%), $1.31 billion in FY2022 (+47.2%) and $888 million in FY2021 (+277.6%).
- Five-year quarterly Operating Expenses spans a low of $230 million in Q4 2021 and a high of $702.8 million in Q4 2025.
- Year over year, Operating Expenses has now increased in each of the last 17 quarters, with growth averaging 20.2% over the last eight quarters.
- The high point for year-over-year Operating Expenses in five years was Q3 2021 (growth of 93.9%); the low point was Q1 2022 (a decline of 13.2%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $543.3 million (Q1 2026), $702.8 million (Q4 2025) and $685.4 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Chubb | 138.09 Bn | 84.67 Bn | 9.13 Bn | 12.19 Bn |
| 2 | Progressive | 127.57 Bn | 103.40 Bn | 9.04 Bn | 19.40 Bn |
| 3 | Marsh & Mclennan Companies | 89.82 Bn | 81.98 Bn | - | 5.65 Bn |
| 4 | Travelers Companies | 80.92 Bn | 57.17 Bn | 6.23 Bn | 9.39 Bn |
| 5 | Manulife Financial | 75.09 Bn | -19.79 Bn | - | -902.21 Mn |
| 6 | Arthur J. Gallagher | 64.98 Bn | 59.38 Bn | - | 3.59 Bn |
| 7 | Metlife | 64.10 Bn | -42.68 Bn | 7.82 Bn | 18.12 Bn |
| 8 | Allstate | 63.22 Bn | 24.49 Bn | 8.73 Bn | 14.45 Bn |
| 9 | Aon | 61.77 Bn | 54.99 Bn | - | 3.33 Bn |
| 10 | White Mountains Insurance | 5.28 Bn | -6.13 Bn | 764.50 Mn | 588.60 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 588.60 Mn |
| Mar 31, 2026 | 543.30 Mn |
| Dec 31, 2025 | 702.80 Mn |
| Sep 30, 2025 | 685.40 Mn |
| Jun 30, 2025 | 512.70 Mn |
| Mar 31, 2025 | 505.40 Mn |
| Dec 31, 2024 | 478.70 Mn |
| Sep 30, 2024 | 599.60 Mn |
| Jun 30, 2024 | 430.10 Mn |
| Mar 31, 2024 | 414.70 Mn |
| Dec 31, 2023 | 409.00 Mn |
| Sep 30, 2023 | 498.50 Mn |
| Jun 30, 2023 | 361.00 Mn |
| Mar 31, 2023 | 332.80 Mn |
| Dec 31, 2022 | 308.60 Mn |
| Sep 30, 2022 | 414.20 Mn |
| Jun 30, 2022 | 309.30 Mn |
| Mar 31, 2022 | 275.20 Mn |
| Dec 31, 2021 | 230.00 Mn |
| Sep 30, 2021 | 268.20 Mn |
API Access
White Mountains Insurance 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=WTM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "WTM", "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=WTM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();