Ameris Bancorp (ABCB) Operating Expenses (2010 - 2026)
Ameris Bancorp's Operating Expenses came in at $158.75 million for Q3 2026, up 2.7% from $154.57 million a year earlier but down 34.6% from the prior quarter.
Ameris Bancorp (ABCB) Operating Expenses (2010 - 2026) Analysis & Trends
Over the trailing twelve months to Sep 30, 2026, Ameris Bancorp reported Operating Expenses of $701.63 million, up 14.5% year-over-year; for FY2025, it was $603.95 million, down 0.6% from FY2024.
- Operating Expenses carries a five-year compound annual growth rate of 0.2% (FY2020 to FY2025).
- Going back by year, Operating Expenses was $607.79 million in FY2024 (+5.1%), $578.28 million in FY2023 (+3.1%), $560.66 million in FY2022 (+0.1%) and $560.12 million in FY2021 (-6.4%).
- The five-year range for quarterly Operating Expenses is $135.06 million (Q4 2022) to $242.71 million (Q2 2026).
- Year-over-year, Operating Expenses has increased for three consecutive quarters, with growth averaging 7.8% over the last eight quarters.
- The fastest year-over-year change in Operating Expenses over five years came in Q2 2026 (growth of 56.3%), and the weakest in Q4 2021 (a decline of 8.4%).
- Business Quant data shows ABCB's Operating Expenses at $242.71 million (Q2 2026), $157.08 million (Q1 2026) and $143.09 million (Q4 2025) in the three quarters before Q3 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 939.97 Bn | 939.97 Bn | - | 27.32 Bn |
| 2 | Bank Of America | 367.49 Bn | -2,008.62 Bn | - | 19.72 Bn |
| 3 | Hsbc Holdings | 309.85 Bn | -1,793.74 Bn | - | 8.82 Bn |
| 4 | Morgan Stanley | 296.54 Bn | -212.55 Bn | - | 13.90 Bn |
| 5 | Royal Bank Of Canada | 293.26 Bn | -536.78 Bn | - | 7.02 Bn |
| 6 | Goldman Sachs | 275.62 Bn | -3,281.49 Bn | - | 11.67 Bn |
| 7 | Wells Fargo & Company | 261.02 Bn | 261.02 Bn | - | 13.74 Bn |
| 8 | Mitsubishi Ufj Financial | 249.37 Bn | -92.02 Bn | 10.89 Bn | 17.50 Bn |
| 9 | American Express | 223.63 Bn | 23.11 Bn | - | 14.55 Bn |
| 10 | Ameris Bancorp | 5.64 Bn | 5.64 Bn | - | 242.71 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 242.71 Mn |
| Mar 31, 2026 | 157.08 Mn |
| Dec 31, 2025 | 143.09 Mn |
| Sep 30, 2025 | 154.57 Mn |
| Jun 30, 2025 | 155.26 Mn |
| Mar 31, 2025 | 151.03 Mn |
| Dec 31, 2024 | 151.95 Mn |
| Sep 30, 2024 | 151.78 Mn |
| Jun 30, 2024 | 155.36 Mn |
| Mar 31, 2024 | 148.71 Mn |
| Dec 31, 2023 | 149.01 Mn |
| Sep 30, 2023 | 141.45 Mn |
| Jun 30, 2023 | 148.40 Mn |
| Mar 31, 2023 | 139.42 Mn |
| Dec 31, 2022 | 135.06 Mn |
| Sep 30, 2022 | 139.58 Mn |
| Jun 30, 2022 | 142.20 Mn |
| Mar 31, 2022 | 143.82 Mn |
| Dec 31, 2021 | 138.37 Mn |
| Sep 30, 2021 | 137.20 Mn |
Ameris Bancorp 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=ABCB&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "ABCB", "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=ABCB&period=max&api_key=YOUR_API_KEY");
const data = await res.json();