Willis Towers Watson (WTW) Other Operating Expenses (2009 - 2026)
Willis Towers Watson (WTW) posted Other Operating Expenses of $380 million for Q2 2026, up 13.1% from $336 million a year earlier but down 1.3% from the prior quarter.
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Analysis
Willis Towers Watson (WTW) Other Operating Expenses (2009 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Other Operating Expenses at Willis Towers Watson was $1.47 billion, down 10.1% year-over-year; for FY2025, it came in at $1.41 billion, down 23.2% from FY2024.
- Annual Other Operating Expenses shows a five-year compound annual growth rate of -3.7% (FY2020 to FY2025).
- In prior years, Willis Towers Watson's Other Operating Expenses was $1.83 billion in FY2024 (+1.0%), $1.82 billion in FY2023 (+7.1%), $1.7 billion in FY2022 (+1.3%) and $1.67 billion in FY2021 (-1.4%).
- Quarterly Other Operating Expenses has run from a low of $336 million in Q2 2025 to a high of $533 million in Q4 2023 over five years.
- On a year-over-year basis, Other Operating Expenses increased in three of the last eight quarters, with an average decline of 8.7%.
- The strongest year-over-year quarter for Other Operating Expenses in the past five years was Q4 2023, with growth of 23.4%; the weakest was Q4 2025, with a decline of 31.5%.
- According to Business Quant data, Other Operating Expenses for the three prior quarters was $385 million (Q1 2026), $355 million (Q4 2025) and $352 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Chubb | 137.65 Bn | 84.23 Bn | 9.13 Bn |
| 2 | Progressive | 129.27 Bn | 105.11 Bn | 9.04 Bn |
| 3 | Marsh & Mclennan Companies | 90.79 Bn | 82.95 Bn | - |
| 4 | Travelers Companies | 83.98 Bn | 60.23 Bn | 6.23 Bn |
| 5 | Manulife Financial | 77.09 Bn | -17.80 Bn | - |
| 6 | Arthur J. Gallagher | 66.40 Bn | 60.80 Bn | - |
| 7 | Metlife | 65.77 Bn | -41.01 Bn | 7.82 Bn |
| 8 | Allstate | 64.29 Bn | 25.56 Bn | 8.73 Bn |
| 9 | Aon | 62.89 Bn | 56.11 Bn | - |
| 10 | Willis Towers Watson | 29.88 Bn | 21.29 Bn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 380.00 Mn |
| Mar 31, 2026 | 385.00 Mn |
| Dec 31, 2025 | 355.00 Mn |
| Sep 30, 2025 | 352.00 Mn |
| Jun 30, 2025 | 336.00 Mn |
| Mar 31, 2025 | 365.00 Mn |
| Dec 31, 2024 | 518.00 Mn |
| Sep 30, 2024 | 419.00 Mn |
| Jun 30, 2024 | 439.00 Mn |
| Mar 31, 2024 | 457.00 Mn |
| Dec 31, 2023 | 533.00 Mn |
| Sep 30, 2023 | 396.00 Mn |
| Jun 30, 2023 | 433.00 Mn |
| Mar 31, 2023 | 453.00 Mn |
| Dec 31, 2022 | 432.00 Mn |
| Sep 30, 2022 | 384.00 Mn |
| Jun 30, 2022 | 393.00 Mn |
| Mar 31, 2022 | 486.00 Mn |
| Dec 31, 2021 | 504.00 Mn |
| Sep 30, 2021 | 385.00 Mn |
API Access
Willis Towers Watson Other 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=other-operating-expenses&ticker=WTW&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-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=other-operating-expenses&ticker=WTW&period=max&api_key=YOUR_API_KEY");
const data = await res.json();