Franklin Financial Services (FRAF) Operating Expenses (2010 - 2026)
Franklin Financial Services' Operating Expenses was $14.61 million in Q2 2026, up 1.5% from $14.39 million a year earlier but down 4.8% from the prior quarter.
Franklin Financial Services (FRAF) Operating Expenses (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, Franklin Financial Services' Operating Expenses was $60.65 million through Jun 30, 2026, up 6.0% year-over-year; for FY2025, it came in at $59.66 million, up 6.7% from FY2024.
- Operating Expenses has now increased for seven consecutive years, with a five-year compound annual growth rate of 8.7% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $55.9 million in FY2024 (+11.8%), $50.01 million in FY2023 (+2.7%), $48.69 million in FY2022 (+12.6%) and $43.25 million in FY2021 (+9.9%).
- Quarterly Operating Expenses has moved between $10.99 million (Q3 2021) and $15.54 million (Q4 2025) over five years.
- Compared with a year earlier, Operating Expenses has increased for ten straight quarters, with growth averaging 7.2% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q2 2022 (growth of 19.0%); the worst was Q4 2023 (a decline of 0.4%).
- Per Business Quant data, FRAF's Operating Expenses in the three quarters before Q2 2026 was $15.35 million (Q1 2026), $15.54 million (Q4 2025) and $15.15 million (Q3 2025).
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 | Franklin Financial Services | 281.98 Mn | -439.69 Mn | - | 14.61 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 14.61 Mn |
| Mar 31, 2026 | 15.35 Mn |
| Dec 31, 2025 | 15.54 Mn |
| Sep 30, 2025 | 15.15 Mn |
| Jun 30, 2025 | 14.39 Mn |
| Mar 31, 2025 | 14.58 Mn |
| Dec 31, 2024 | 14.33 Mn |
| Sep 30, 2024 | 13.92 Mn |
| Jun 30, 2024 | 14.34 Mn |
| Mar 31, 2024 | 13.28 Mn |
| Dec 31, 2023 | 13.15 Mn |
| Sep 30, 2023 | 12.20 Mn |
| Jun 30, 2023 | 12.65 Mn |
| Mar 31, 2023 | 12.02 Mn |
| Dec 31, 2022 | 13.20 Mn |
| Sep 30, 2022 | 12.20 Mn |
| Jun 30, 2022 | 12.03 Mn |
| Mar 31, 2022 | 11.27 Mn |
| Dec 31, 2021 | 11.98 Mn |
| Sep 30, 2021 | 10.99 Mn |
Franklin Financial Services 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=FRAF&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "FRAF", "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=FRAF&period=max&api_key=YOUR_API_KEY");
const data = await res.json();