Muncy Columbia Financial (CCFN) Professional Fees (2010 - 2026)
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Analysis
Muncy Columbia Financial (CCFN) Professional Fees (2010 - 2026) Analysis & Trends
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Professional Fees (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 881.30 Bn | 881.30 Bn | - | 3.86 Bn |
| 2 | Bank Of America | 354.90 Bn | -2,021.17 Bn | - | 573.00 Mn |
| 3 | Hsbc Holdings | 311.39 Bn | -1,517.77 Bn | - | - |
| 4 | Morgan Stanley | 282.15 Bn | -226.95 Bn | - | 680.00 Mn |
| 5 | Royal Bank Of Canada | 281.68 Bn | -548.32 Bn | - | 411.67 Mn |
| 6 | Goldman Sachs | 255.22 Bn | -3,301.89 Bn | - | 372.00 Mn |
| 7 | Mitsubishi Ufj Financial | 249.82 Bn | -82.42 Bn | 10.89 Bn | - |
| 8 | Wells Fargo & Company | 249.49 Bn | 251.62 Bn | - | 1.11 Bn |
| 9 | Toronto Dominion Bank | 210.53 Bn | -465.35 Bn | - | 684.93 Mn |
| 10 | Muncy Columbia Financial | 320.86 Mn | 146.42 Mn | - | 445,000.00 |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 445,000.00 |
| Mar 31, 2026 | 644,000.00 |
| Dec 31, 2025 | 586,000.00 |
| Sep 30, 2025 | 491,000.00 |
| Jun 30, 2025 | 414,000.00 |
| Mar 31, 2025 | 448,000.00 |
| Dec 31, 2024 | 387,000.00 |
| Sep 30, 2024 | 359,000.00 |
| Jun 30, 2024 | 319,000.00 |
| Mar 31, 2024 | 457,000.00 |
| Dec 31, 2023 | 442,000.00 |
| Sep 30, 2023 | 316,000.00 |
| Jun 30, 2023 | 264,000.00 |
| Mar 31, 2023 | 311,000.00 |
| Dec 31, 2022 | 476,000.00 |
| Sep 30, 2022 | 274,000.00 |
| Jun 30, 2022 | 342,000.00 |
| Dec 31, 2013 | 183,000.00 |
| Sep 30, 2013 | 148,000.00 |
| Jun 30, 2013 | 160,000.00 |
API Access
Muncy Columbia Financial Professional Fees 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=professional-fees&ticker=CCFN&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "professional-fees", "ticker": "CCFN", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=professional-fees&ticker=CCFN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();