HBT Financial (HBT) Operating Expenses (2018 - 2026)
HBT Financial (HBT) reported Operating Expenses of $42.66 million for Q3 2026, up 31.2% from $32.51 million a year earlier and up 0.5% from the prior quarter.
HBT Financial (HBT) Operating Expenses (2018 - 2026) Analysis & Trends
Over the twelve months ended Sep 30, 2026, HBT Financial's Operating Expenses came in at $170.61 million, up 34.1% year-over-year; for FY2025, it came in at $129.42 million, up 4.4% from FY2024.
- Operating Expenses has a five-year compound annual growth rate of 7.1% (FY2020 to FY2025).
- By year, Operating Expenses came in at $124.01 million in FY2024 (-5.3%), $130.96 million in FY2023 (+24.6%), $105.11 million in FY2022 (+15.2%) and $91.25 million in FY2021 (-0.8%).
- Five-year quarterly Operating Expenses spans a low of $23.84 million in Q2 2022 and a high of $52.44 million in Q1 2026.
- Year over year, Operating Expenses has now increased in each of the last nine quarters, with growth averaging 18.5% over the last eight quarters.
- The high point for year-over-year Operating Expenses in five years was Q1 2026 (growth of 64.2%); the low point was Q1 2024 (a decline of 13.0%).
- Per Business Quant data, the three quarters before Q3 2026 came in at $42.45 million (Q2 2026), $52.44 million (Q1 2026) and $33.06 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 909.02 Bn | 886.77 Bn | - | 27.30 Bn |
| 2 | Banco Santander Chile | 406.67 Bn | -7,110.43 Bn | - | - |
| 3 | Bank Of America | 350.91 Bn | -2,025.20 Bn | - | 19.72 Bn |
| 4 | Hsbc Holdings | 308.71 Bn | -2,966.46 Bn | - | 8.82 Bn |
| 5 | Morgan Stanley | 293.66 Bn | -249.15 Bn | - | 13.71 Bn |
| 6 | Royal Bank Of Canada | 283.56 Bn | -546.44 Bn | - | 7.02 Bn |
| 7 | Goldman Sachs | 262.71 Bn | -3,480.74 Bn | - | 11.31 Bn |
| 8 | Wells Fargo & Company | 257.44 Bn | 92.87 Bn | - | 13.74 Bn |
| 9 | Mitsubishi Ufj Financial | 256.82 Bn | -75.42 Bn | 10.89 Bn | 17.50 Bn |
| 10 | HBT Financial | 1.36 Bn | 682.67 Mn | - | 42.66 Mn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 42.66 Mn |
| Jun 30, 2026 | 42.45 Mn |
| Mar 31, 2026 | 52.44 Mn |
| Dec 31, 2025 | 33.06 Mn |
| Sep 30, 2025 | 32.51 Mn |
| Jun 30, 2025 | 31.91 Mn |
| Mar 31, 2025 | 31.94 Mn |
| Dec 31, 2024 | 30.91 Mn |
| Sep 30, 2024 | 31.32 Mn |
| Jun 30, 2024 | 30.51 Mn |
| Mar 31, 2024 | 31.27 Mn |
| Dec 31, 2023 | 30.39 Mn |
| Sep 30, 2023 | 30.67 Mn |
| Jun 30, 2023 | 33.97 Mn |
| Mar 31, 2023 | 35.93 Mn |
| Dec 31, 2022 | 33.11 Mn |
| Sep 30, 2022 | 24.00 Mn |
| Jun 30, 2022 | 23.84 Mn |
| Mar 31, 2022 | 24.16 Mn |
| Dec 31, 2021 | 24.38 Mn |
HBT 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=HBT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "HBT", "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=HBT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();