Axos Financial (AX) Operating Expenses (2010 - 2026)
Axos Financial (AX) posted Operating Expenses of $205.95 million for fiscal Q4 2026 (quarter ended Jun 30, 2026), up 36.7% from $150.65 million a year earlier and up 10.8% from the prior quarter.
Axos Financial (AX) Operating Expenses (2010 - 2026) Analysis & Trends
For FY2026 (ended Jun 30, 2026), Axos Financial's Operating Expenses came in at $732.72 million, up 24.3% from FY2025.
- Annual Operating Expenses has increased for 16 consecutive fiscal years, with a five-year compound annual growth rate of 18.4% (FY2021 to FY2026).
- In prior fiscal years, Axos Financial's Operating Expenses was $589.7 million in FY2025 (+14.3%), $516.11 million in FY2024 (+15.3%), $447.62 million in FY2023 (+25.4%) and $356.81 million in FY2022 (+13.5%).
- The fiscal Q4 2026 figure stands as the highest quarterly Operating Expenses in data going back to fiscal Q1 2011.
- On a year-over-year basis, Operating Expenses has increased in each of the last 25 quarters, with growth averaging 19.4% over the last eight quarters.
- Across the past five years, year-over-year growth in Operating Expenses ran from 3.8% in fiscal Q1 2024 to 37.5% in fiscal Q1 2023.
- According to Business Quant data, Operating Expenses for the three prior fiscal quarters was $185.95 million (Q3 2026), $184.57 million (Q2 2026) and $156.25 million (Q1 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 895.36 Bn | 924.83 Bn | - | 27.32 Bn |
| 2 | Banco Santander Chile | 425.01 Bn | 544.95 Bn | - | -3,218.32 Bn |
| 3 | Bank Of America | 389.22 Bn | -1,986.85 Bn | - | 18.63 Bn |
| 4 | Hsbc Holdings | 347.56 Bn | 347.61 Bn | - | - |
| 5 | Morgan Stanley | 304.44 Bn | -204.66 Bn | - | 13.90 Bn |
| 6 | Royal Bank Of Canada | 281.54 Bn | 132.29 Bn | - | 7.02 Bn |
| 7 | Mitsubishi Ufj Financial | 277.23 Bn | -1,311.26 Bn | 10.89 Bn | 17.50 Bn |
| 8 | Goldman Sachs | 267.12 Bn | -3,289.99 Bn | - | 11.67 Bn |
| 9 | Wells Fargo & Company | 244.76 Bn | 246.90 Bn | - | 13.66 Bn |
| 10 | Axos Financial | 4.97 Bn | -1.91 Bn | - | 205.95 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 205.95 Mn |
| Mar 31, 2026 | 185.95 Mn |
| Dec 31, 2025 | 184.57 Mn |
| Sep 30, 2025 | 156.25 Mn |
| Jun 30, 2025 | 150.65 Mn |
| Mar 31, 2025 | 146.26 Mn |
| Dec 31, 2024 | 145.32 Mn |
| Sep 30, 2024 | 147.47 Mn |
| Jun 30, 2024 | 140.54 Mn |
| Mar 31, 2024 | 133.23 Mn |
| Dec 31, 2023 | 121.84 Mn |
| Sep 30, 2023 | 120.51 Mn |
| Jun 30, 2023 | 112.46 Mn |
| Mar 31, 2023 | 111.04 Mn |
| Dec 31, 2022 | 108.03 Mn |
| Sep 30, 2022 | 116.09 Mn |
| Jun 30, 2022 | 99.54 Mn |
| Mar 31, 2022 | 86.82 Mn |
| Dec 31, 2021 | 86.02 Mn |
| Sep 30, 2021 | 84.43 Mn |
Axos Financial 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=AX&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "AX", "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=AX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();