Orrstown Financial Services (ORRF) Interest Expenses (2010 - 2026)
Orrstown Financial Services (ORRF) posted Interest Expenses of $25.87 million for Q2 2026, up 2.2% from $25.32 million a year earlier and up 2.0% from the prior quarter.
Orrstown Financial Services (ORRF) Interest Expenses (2010 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Interest Expenses at Orrstown Financial Services was $103.09 million, down 8.6% year-over-year; for FY2025, it came in at $103.94 million, up 11.0% from FY2024.
- Annual Interest Expenses has increased for four consecutive years, with a five-year compound annual growth rate of 45.3% (FY2020 to FY2025).
- In prior years, Orrstown Financial Services' Interest Expenses was $93.68 million in FY2024 (+108.2%), $44.99 million in FY2023 (+398.6%), $9.02 million in FY2022 (+34.3%) and $6.72 million in FY2021 (-58.1%).
- Quarterly Interest Expenses has run from a low of $1.22 million in Q1 2022 to a high of $31.29 million in Q3 2024 over five years.
- On a year-over-year basis, Interest Expenses increased in five of the last eight quarters, with growth averaging 43.2%.
- The strongest year-over-year quarter for Interest Expenses in the past five years was Q2 2023, with growth of 754.4%; the weakest was Q3 2021, with a decline of 53.8%.
- According to Business Quant data, Interest Expenses for the three prior quarters was $25.36 million (Q1 2026), $25.73 million (Q4 2025) and $26.13 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Int Expense (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 890.60 Bn | 920.07 Bn | - | 25.11 Bn |
| 2 | Banco Santander Chile | 421.74 Bn | 541.68 Bn | - | -538.61 Bn |
| 3 | Bank Of America | 385.85 Bn | -1,990.22 Bn | - | 17.84 Bn |
| 4 | Hsbc Holdings | 345.94 Bn | 345.99 Bn | - | - |
| 5 | Morgan Stanley | 303.15 Bn | -205.95 Bn | - | 13.12 Bn |
| 6 | Royal Bank Of Canada | 279.82 Bn | 130.57 Bn | - | 12.80 Bn |
| 7 | Mitsubishi Ufj Financial | 274.62 Bn | -1,313.87 Bn | 10.89 Bn | 9.12 Bn |
| 8 | Goldman Sachs | 267.07 Bn | -3,290.04 Bn | - | 18.09 Bn |
| 9 | Wells Fargo & Company | 243.79 Bn | 245.93 Bn | - | 10.97 Bn |
| 10 | Orrstown Financial Services | 803.90 Mn | 803.90 Mn | - | 25.87 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 25.87 Mn |
| Mar 31, 2026 | 25.36 Mn |
| Dec 31, 2025 | 25.73 Mn |
| Sep 30, 2025 | 26.13 Mn |
| Jun 30, 2025 | 25.32 Mn |
| Mar 31, 2025 | 26.76 Mn |
| Dec 31, 2024 | 29.44 Mn |
| Sep 30, 2024 | 31.29 Mn |
| Jun 30, 2024 | 17.18 Mn |
| Mar 31, 2024 | 15.77 Mn |
| Dec 31, 2023 | 14.01 Mn |
| Sep 30, 2023 | 12.47 Mn |
| Jun 30, 2023 | 10.53 Mn |
| Mar 31, 2023 | 7.98 Mn |
| Dec 31, 2022 | 4.61 Mn |
| Sep 30, 2022 | 1.96 Mn |
| Jun 30, 2022 | 1.23 Mn |
| Mar 31, 2022 | 1.22 Mn |
| Dec 31, 2021 | 1.32 Mn |
| Sep 30, 2021 | 1.57 Mn |
Orrstown Financial Services Interest 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=interest-expenses&ticker=ORRF&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "interest-expenses", "ticker": "ORRF", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=interest-expenses&ticker=ORRF&period=max&api_key=YOUR_API_KEY");
const data = await res.json();