Willis Towers Watson (WTW) Operating Expenses (2009 - 2026)
Willis Towers Watson's (WTW) quarterly Operating Expenses came in at $2.1 billion in Q2 2026, up 11.04% on a YoY basis from $1.9 billion in Q2 2025, and up 7.03% quarter-over-quarter from $2.0 billion in Q1 2026.
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Willis Towers Watson (WTW) Operating Expenses (2009 - 2026) Analysis & Trends
Willis Towers Watson (WTW) has reported Operating Expenses for 18 consecutive years, with $2.1 billion the latest figure, recorded in Q2 2026.
- For the quarter ending Q2 2026, Operating Expenses rose 11.04% year-over-year to $2.1 billion; the trailing twelve-month figure through Jun 2026 stood at $7.9 billion (down 11.46% YoY), and the FY2025 full-year result was $7.5 billion, down 19.66% from the prior year.
- Operating Expenses rose to $2.1 billion in Q2 2026 per WTW's latest filing, from $2.0 billion in the prior quarter.
- Across five years, Operating Expenses topped out at $3.1 billion in Q3 2024 and bottomed at $1.8 billion in Q1 2025.
- Historically, Operating Expenses has averaged $2.0 billion across 5 years, with a median of $2.0 billion in 2022.
- The sharpest annual moves came in 2022 and 2025: Operating Expenses soared 113.66% in 2022, then plunged 38.79% in 2025.
- Over 5 years, Operating Expenses stood at $2.0 billion in 2022, then advanced by 6.01% to $2.1 billion in 2023, then dropped by 0.05% to $2.1 billion in 2024, then declined by 10.03% to $1.9 billion in 2025, then grew by 9.48% to $2.1 billion in 2026.
- According to Business Quant data, Operating Expenses over the past three periods registered $2.1 billion, $2.0 billion, and $1.9 billion for Q2 2026, Q1 2026, and Q4 2025 respectively.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Marsh & Mclennan Companies | 83.52 Bn | 71.57 Bn | 6.04 Bn | 5.51 Bn |
| 2 | Aon | 62.69 Bn | 61.45 Bn | - | 3.33 Bn |
| 3 | Arthur J. Gallagher | 61.32 Bn | 59.96 Bn | - | 3.59 Bn |
| 4 | Willis Towers Watson | 28.79 Bn | 27.21 Bn | 2.09 Bn | 2.10 Bn |
| 5 | Brown & Brown | 21.46 Bn | 20.56 Bn | 1.41 Bn | 1.29 Bn |
| 6 | XChange TEC.INC | 12.72 Bn | 12.72 Bn | - | - |
| 7 | Erie Indemnity | 11.04 Bn | 10.70 Bn | - | 885.67 Mn |
| 8 | Ryan Specialty Holdings | 10.28 Bn | 10.64 Bn | - | 736.33 Mn |
| 9 | Hagerty | 4.78 Bn | 4.92 Bn | 244.11 Mn | 352.59 Mn |
| 10 | Baldwin Insurance | 4.45 Bn | 4.80 Bn | - | 501.28 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 2.10 Bn |
| Mar 31, 2026 | 1.96 Bn |
| Dec 31, 2025 | 1.92 Bn |
| Sep 30, 2025 | 1.87 Bn |
| Jun 30, 2025 | 1.89 Bn |
| Mar 31, 2025 | 1.79 Bn |
| Dec 31, 2024 | 2.13 Bn |
| Sep 30, 2024 | 3.06 Bn |
| Jun 30, 2024 | 2.05 Bn |
| Mar 31, 2024 | 2.06 Bn |
| Dec 31, 2023 | 2.14 Bn |
| Sep 30, 2023 | 2.01 Bn |
| Jun 30, 2023 | 2.02 Bn |
| Mar 31, 2023 | 1.96 Bn |
| Dec 31, 2022 | 2.01 Bn |
| Sep 30, 2022 | 1.80 Bn |
| Jun 30, 2022 | 1.89 Bn |
| Mar 31, 2022 | 1.98 Bn |
| Dec 31, 2021 | 2.02 Bn |
| Sep 30, 2021 | 842.00 Mn |
API Access
Willis Towers Watson 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=WTW&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "WTW", "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=WTW&period=max&api_key=YOUR_API_KEY");
const data = await res.json();