Employers Holdings (EIG) Operating Expenses (2009 - 2026)
Employers Holdings' Operating Expenses was $185.5 million in Q2 2026, down 11.4% from $209.3 million a year earlier and down 4.8% from the prior quarter.
Employers Holdings (EIG) Operating Expenses (2009 - 2026) Analysis & Trends
On a trailing twelve-month basis, Employers Holdings' Operating Expenses was $830.9 million through Jun 30, 2026, up 8.6% year-over-year; for FY2025, it came in at $846.7 million, up 15.4% from FY2024.
- Operating Expenses has now increased for four consecutive years, with a five-year compound annual growth rate of 8.5% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $734 million in FY2024 (+4.5%), $702.5 million in FY2023 (+6.8%), $657.7 million in FY2022 (+18.3%) and $556.1 million in FY2021 (-1.3%).
- The Q2 2026 figure marks the lowest quarterly Operating Expenses since Q4 2024.
- Compared with a year earlier, Operating Expenses was higher in six of the last eight quarters, with growth averaging 7.9%.
- The best year-over-year quarter for Operating Expenses over five years was Q3 2025 (growth of 33.7%); the worst was Q2 2026 (a decline of 11.4%).
- Per Business Quant data, EIG's Operating Expenses in the three quarters before Q2 2026 was $194.8 million (Q1 2026), $200.1 million (Q4 2025) and $250.5 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Chubb | 137.65 Bn | 84.23 Bn | 9.13 Bn | 12.19 Bn |
| 2 | Progressive | 129.27 Bn | 105.11 Bn | 9.04 Bn | 19.40 Bn |
| 3 | Marsh & Mclennan Companies | 90.79 Bn | 82.95 Bn | - | 5.65 Bn |
| 4 | Travelers Companies | 83.98 Bn | 60.23 Bn | 6.23 Bn | 9.39 Bn |
| 5 | Manulife Financial | 77.09 Bn | -17.80 Bn | - | -902.21 Mn |
| 6 | Arthur J. Gallagher | 66.40 Bn | 60.80 Bn | - | 3.59 Bn |
| 7 | Metlife | 65.77 Bn | -41.01 Bn | 7.82 Bn | 18.12 Bn |
| 8 | Allstate | 64.29 Bn | 25.56 Bn | 8.73 Bn | 14.45 Bn |
| 9 | Aon | 62.89 Bn | 56.11 Bn | - | 3.33 Bn |
| 10 | Employers Holdings | 938.79 Mn | -475.81 Mn | 97.90 Mn | 185.50 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 185.50 Mn |
| Mar 31, 2026 | 194.80 Mn |
| Dec 31, 2025 | 200.10 Mn |
| Sep 30, 2025 | 250.50 Mn |
| Jun 30, 2025 | 209.30 Mn |
| Mar 31, 2025 | 186.70 Mn |
| Dec 31, 2024 | 182.00 Mn |
| Sep 30, 2024 | 187.30 Mn |
| Jun 30, 2024 | 177.00 Mn |
| Mar 31, 2024 | 187.80 Mn |
| Dec 31, 2023 | 167.60 Mn |
| Sep 30, 2023 | 186.10 Mn |
| Jun 30, 2023 | 171.40 Mn |
| Mar 31, 2023 | 177.50 Mn |
| Dec 31, 2022 | 165.90 Mn |
| Sep 30, 2022 | 180.60 Mn |
| Jun 30, 2022 | 156.70 Mn |
| Mar 31, 2022 | 154.50 Mn |
| Dec 31, 2021 | 131.40 Mn |
| Sep 30, 2021 | 149.70 Mn |
Employers Holdings 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=EIG&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "EIG", "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=EIG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();