Park National (PRK) Professional Fees (2009 - 2026)
Park National's Professional Fees was $8.73 million in Q2 2026, up 18.1% from $7.4 million a year earlier but down 48.1% from the prior quarter.
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Analysis
Park National (PRK) Professional Fees (2009 - 2026) Analysis & Trends
On a trailing twelve-month basis, Park National's Professional Fees was $42.31 million through Jun 30, 2026, up 28.2% year-over-year; for FY2025, it came in at $31.45 million, up 1.0% from FY2024.
- Professional Fees shows a five-year compound annual growth rate of 0.1% (FY2020 to FY2025).
- In earlier years, Professional Fees was $31.15 million in FY2024 (+6.8%), $29.17 million in FY2023 (-5.4%), $30.84 million in FY2022 (+12.3%) and $27.45 million in FY2021 (-12.3%).
- Quarterly Professional Fees has moved between $5.86 million (Q1 2022) and $16.83 million (Q1 2026) over five years.
- Compared with a year earlier, Professional Fees was higher in six of the last eight quarters, with growth averaging 26.9%.
- The best year-over-year quarter for Professional Fees over five years was Q1 2026 (growth of 130.3%); the worst was Q4 2023 (a decline of 28.7%).
- Per Business Quant data, PRK's Professional Fees in the three quarters before Q2 2026 was $16.83 million (Q1 2026), $9.28 million (Q4 2025) and $7.48 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Professional Fees (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 909.02 Bn | 886.77 Bn | - | 3.90 Bn |
| 2 | Banco Santander Chile | 406.67 Bn | -7,110.43 Bn | - | - |
| 3 | Bank Of America | 350.91 Bn | -2,025.20 Bn | - | 606.00 Mn |
| 4 | Hsbc Holdings | 308.71 Bn | -2,966.46 Bn | - | - |
| 5 | Morgan Stanley | 293.66 Bn | -249.15 Bn | - | 700.00 Mn |
| 6 | Royal Bank Of Canada | 283.56 Bn | -546.44 Bn | - | 411.67 Mn |
| 7 | Goldman Sachs | 262.71 Bn | -3,480.74 Bn | - | 424.00 Mn |
| 8 | Wells Fargo & Company | 257.44 Bn | 92.87 Bn | - | 1.17 Bn |
| 9 | Mitsubishi Ufj Financial | 256.82 Bn | -75.42 Bn | 10.89 Bn | - |
| 10 | Park National | 3.24 Bn | -3.51 Bn | - | 9.17 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 9.17 Mn |
| Jun 30, 2026 | 8.73 Mn |
| Mar 31, 2026 | 16.83 Mn |
| Dec 31, 2025 | 9.28 Mn |
| Sep 30, 2025 | 7.48 Mn |
| Jun 30, 2025 | 7.40 Mn |
| Mar 31, 2025 | 7.31 Mn |
| Dec 31, 2024 | 10.47 Mn |
| Sep 30, 2024 | 7.84 Mn |
| Jun 30, 2024 | 6.02 Mn |
| Mar 31, 2024 | 6.82 Mn |
| Dec 31, 2023 | 7.02 Mn |
| Sep 30, 2023 | 7.57 Mn |
| Jun 30, 2023 | 7.37 Mn |
| Mar 31, 2023 | 7.22 Mn |
| Dec 31, 2022 | 9.85 Mn |
| Sep 30, 2022 | 8.36 Mn |
| Jun 30, 2022 | 6.78 Mn |
| Mar 31, 2022 | 5.86 Mn |
| Dec 31, 2021 | 7.84 Mn |
API Access
Park National 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=PRK&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "professional-fees", "ticker": "PRK", "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=PRK&period=max&api_key=YOUR_API_KEY");
const data = await res.json();