Peoples Bancorp (PEBO) Change in Net Loans (2019 - 2026)
Peoples Bancorp's Change in Net Loans was $56.68 million in Q2 2026, down 68.2% from $177.99 million a year earlier but up 215.5% from the prior quarter.
Peoples Bancorp (PEBO) Change in Net Loans (2019 - 2026) Analysis & Trends
On a trailing twelve-month basis, Peoples Bancorp's Change in Net Loans was $240.08 million through Jun 30, 2026, down 16.5% year-over-year; for FY2025, it was $418.24 million, up 109.9% from FY2024.
- Change in Net Loans shows a five-year compound annual growth rate of -1.2% (FY2020 to FY2025).
- In earlier years, Change in Net Loans was $199.24 million in FY2024 (-44.0%), $356.08 million in FY2023 (+512.4%), $58.14 million in FY2022 and -$113.47 million in FY2021.
- Quarterly Change in Net Loans has moved between -$75.74 million (Q1 2022) and $177.99 million (Q2 2025) over five years.
- Compared with a year earlier, Change in Net Loans has declined for three straight quarters, with an average decline of 9.8% over the last six quarters.
- The best year-over-year quarter for Change in Net Loans over five years was Q3 2023 (growth of 191.0%); the worst was Q1 2026 (a decline of 76.0%).
- Per Business Quant data, PEBO's Change in Net Loans in the three quarters before Q2 2026 was $17.96 million (Q1 2026), $33.78 million (Q4 2025) and $131.67 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change in Net Loans (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 886.05 Bn | 915.53 Bn | - | - |
| 2 | Banco Santander Chile | 409.93 Bn | 529.88 Bn | - | - |
| 3 | Bank Of America | 377.01 Bn | -1,999.06 Bn | - | - |
| 4 | Hsbc Holdings | 329.11 Bn | 329.16 Bn | - | - |
| 5 | Morgan Stanley | 295.54 Bn | -213.55 Bn | - | 12.69 Bn |
| 6 | Royal Bank Of Canada | 273.59 Bn | 124.33 Bn | - | -22.01 Bn |
| 7 | Mitsubishi Ufj Financial | 268.33 Bn | -1,320.16 Bn | 10.89 Bn | - |
| 8 | Goldman Sachs | 261.29 Bn | -3,295.82 Bn | - | 7.29 Bn |
| 9 | Wells Fargo & Company | 243.13 Bn | 245.26 Bn | - | -19.63 Bn |
| 10 | Peoples Bancorp | 1.33 Bn | 576.63 Mn | - | 56.68 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 56.68 Mn |
| Mar 31, 2026 | 17.96 Mn |
| Dec 31, 2025 | 33.78 Mn |
| Sep 30, 2025 | 131.67 Mn |
| Jun 30, 2025 | 177.99 Mn |
| Mar 31, 2025 | 74.80 Mn |
| Dec 31, 2024 | 91.19 Mn |
| Sep 30, 2024 | -56.43 Mn |
| Jun 30, 2024 | 121.15 Mn |
| Mar 31, 2024 | 43.34 Mn |
| Dec 31, 2023 | 70.87 Mn |
| Sep 30, 2023 | 101.03 Mn |
| Jun 30, 2023 | 131.79 Mn |
| Mar 31, 2023 | 52.39 Mn |
| Dec 31, 2022 | 94.30 Mn |
| Sep 30, 2022 | 34.71 Mn |
| Jun 30, 2022 | 4.87 Mn |
| Mar 31, 2022 | -75.74 Mn |
| Dec 31, 2021 | 43.13 Mn |
| Jun 30, 2021 | -124.19 Mn |
Peoples Bancorp Change in Net Loans 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=change-in-net-loans&ticker=PEBO&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-net-loans", "ticker": "PEBO", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=change-in-net-loans&ticker=PEBO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();