Lakeland Financial (LKFN) Operating Expenses (2010 - 2026)
Lakeland Financial (LKFN) reported Operating Expenses of $36.12 million for Q3 2026, up 3.3% from $34.97 million a year earlier and up 4.8% from the prior quarter.
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Analysis
Lakeland Financial (LKFN) Operating Expenses (2010 - 2026) Analysis & Trends
Over the twelve months ended Sep 30, 2026, Lakeland Financial's Operating Expenses came in at $139.17 million, up 8.0% year-over-year; for FY2025, it was $131.61 million, up 5.2% from FY2024.
- Operating Expenses has a five-year compound annual growth rate of 7.6% (FY2020 to FY2025).
- By year, Operating Expenses came in at $125.08 million in FY2024 (-4.3%), $130.71 million in FY2023 (+18.6%), $110.21 million in FY2022 (+5.7%) and $104.29 million in FY2021 (+14.3%).
- The Q3 2026 figure ranks as the highest quarterly Operating Expenses since Q2 2023.
- Year over year, Operating Expenses has now increased in each of the last five quarters, with growth averaging 6.3% over the last eight quarters.
- The high point for year-over-year Operating Expenses in five years was Q2 2023 (growth of 53.1%); the low point was Q2 2024 (a decline of 22.0%).
- Per Business Quant data, the three quarters before Q3 2026 came in at $34.46 million (Q2 2026), $35.15 million (Q1 2026) and $33.45 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 896.53 Bn | 896.53 Bn | - | 27.30 Bn |
| 2 | Bank Of America | 354.20 Bn | -2,021.91 Bn | - | 19.72 Bn |
| 3 | Hsbc Holdings | 303.54 Bn | -1,800.05 Bn | - | 8.82 Bn |
| 4 | Royal Bank Of Canada | 283.29 Bn | -546.75 Bn | - | 7.02 Bn |
| 5 | Morgan Stanley | 281.19 Bn | -262.84 Bn | - | 13.71 Bn |
| 6 | Goldman Sachs | 256.26 Bn | -3,487.19 Bn | - | 11.31 Bn |
| 7 | Wells Fargo & Company | 253.33 Bn | 253.33 Bn | - | 13.74 Bn |
| 8 | Mitsubishi Ufj Financial | 238.77 Bn | -102.62 Bn | 10.89 Bn | 17.50 Bn |
| 9 | American Express | 216.03 Bn | 15.51 Bn | - | 14.55 Bn |
| 10 | Lakeland Financial | 1.53 Bn | 928.64 Mn | - | 36.12 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 36.12 Mn |
| Jun 30, 2026 | 34.46 Mn |
| Mar 31, 2026 | 35.15 Mn |
| Dec 31, 2025 | 33.45 Mn |
| Sep 30, 2025 | 34.97 Mn |
| Jun 30, 2025 | 30.43 Mn |
| Mar 31, 2025 | 32.76 Mn |
| Dec 31, 2024 | 30.65 Mn |
| Sep 30, 2024 | 30.39 Mn |
| Jun 30, 2024 | 33.33 Mn |
| Mar 31, 2024 | 30.71 Mn |
| Dec 31, 2023 | 29.45 Mn |
| Sep 30, 2023 | 29.10 Mn |
| Jun 30, 2023 | 42.73 Mn |
| Mar 31, 2023 | 29.43 Mn |
| Dec 31, 2022 | 27.43 Mn |
| Sep 30, 2022 | 27.89 Mn |
| Jun 30, 2022 | 27.91 Mn |
| Mar 31, 2022 | 26.97 Mn |
| Dec 31, 2021 | 24.93 Mn |
API Access
Lakeland 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=LKFN&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "LKFN", "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=LKFN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();