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Allowance For Credit Losses | 9 Months Ended
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Sep. 30, 2025
Financing Receivable, Allowance for Credit Loss, Writeoff, after Recovery [Abstract] |
Allowance for Credit Losses [Text Block] | Allowance for Credit Losses The ACL is an estimate of the expected credit losses on financial assets measured at amortized cost, which is measured using relevant information about past events, including historical credit loss experience on financial assets with similar risk characteristics, current conditions, and reasonable and supportable forecasts that affect the collectability of the remaining cash flows over the contractual term of the financial assets. A provision for credit losses is charged to operations based on management’s periodic evaluation of these and other pertinent factors. Quantitative Considerations The ACL is primarily calculated utilizing a DCF model. Key inputs and assumptions used in this model are discussed below: •Forecast model - For each portfolio segment, a LDA was performed in order to identify appropriate loss drivers and create a regression model for use in forecasting cash flows. The LDA analysis utilized Park's own FFIEC Call Report data for the commercial, financial and agricultural and residential real estate portfolio segments. Peer data was incorporated into the analysis for the commercial real estate, construction real estate, and consumer portfolio segments. Park updated the LDA in the fourth quarter of 2024. During the COVID-19 pandemic, macroeconomic indicators showed significant deterioration, however, Park, along with most financial institutions, observed little to no meaningful increase in default activity. This can be attributed to external intervention in the form of deferral programs and government stimulus which is unlikely to reoccur in future downturns. For these reasons, management has excluded data from 2020-2022 in the LDA by using indicator variables during this time period. •Probability of default – PD is the probability that an asset will be in default within a given time frame. Park has defined default to be when a charge-off has occurred, a loan is placed on nonaccrual, or a loan is greater than 90 days past due. Whenever possible, Park utilizes its own loan-level PDs for the reasonable and supportable forecast period. When loan-level data is not available reflecting the forecasted economic conditions, the LDA is utilized to estimate PDs. In all cases, the LDA is then utilized to determine the long-term historical average, which is reached over the reversion period. •Loss given default – LGD is the percentage of the asset not expected to be collected due to default. Whenever possible, Park utilizes its own loan-level LGDs for the reasonable and supportable forecast period. When it is not possible to use Park's own LGDs, the LGD is derived using a method referred to as Frye Jacobs. In all cases, the Frye Jacobs method is utilized to calculate LGDs during the reversion period and long-term historical average. •Prepayments and curtailments – Prepayments and curtailments are calculated based on Park’s own data utilizing a three-year average. This analysis is updated annually in the fourth quarter and was last updated in the fourth quarter of 2024. •Forecast and reversion – Park has established a one-year reasonable and supportable forecast period with a one-year straight line reversion to the long-term historical average. •Economic forecast - Park utilizes a third party to provide economic forecasts under various scenarios, which are weighted in order to reflect model risk in the current economic environment. The scenario weighting is evaluated by management on a quarterly basis. ◦As of September 30, 2024, the "most likely" scenario forecasted Ohio unemployment between 4.64% and 4.70% during the next four quarters. In determining the appropriate weighting of scenarios at September 30, 2024, management considered the range of forecasted unemployment as well as a number of economic indicators. The low and volatile levels of consumer confidence, increased unemployment rates, the impact of elevated inflation for several years, the interest rate environment, financial system stress, and geopolitical conflict (including the conflicts between Russia and Ukraine and between Israel and Hamas) and stress in the commercial real estate sector, continued to cause uncertainty as to the overall economic environment. Considering these factors, management determined it was appropriate to maintain the existing weighting, and weigh the "most likely" scenario 50% and the "moderate recession" scenario 50% at September 30, 2024. ◦As of December 31, 2024, the "most likely" scenario forecasted Ohio unemployment between 4.48% and 4.60% during the next four quarters. In determining the appropriate weighting of scenarios at December 31, 2024, management considered the range of forecasted unemployment as well as a number of economic indicators. While some economic indications are showing improvement and stabilization, volatile levels of consumer confidence, higher unemployment rates, the impact of elevated inflation for several years with no immediate indications of sustained decline, the interest rate environment, financial system stress, and geopolitical conflict (including the conflicts between Russia and Ukraine and between Israel and Hamas) and stress in the commercial real estate sector, continued to cause uncertainty as to the overall economic environment. Considering these factors, management determined it was appropriate to maintain the existing weighting, and weigh the "most likely" scenario 50% and the "moderate recession" scenario 50% at December 31, 2024. ◦As of March 31, 2025, the "most likely" scenario forecasted Ohio unemployment between 4.51% and 4.85% during the next four quarters. In determining the appropriate weighting of scenarios at March 31, 2025, management considered the range of forecasted unemployment as well as a number of economic indicators. While some economic indications are showing stabilization, lower levels of consumer confidence, higher unemployment rates, the impact of elevated inflation for several years with no immediate signs of sustained decline, the interest rate environment, financial system stress, geopolitical conflict, uncertainty regarding fiscal policy of the new political administration, including tariffs, and stress in the commercial real estate sector cause uncertainty to the overall economic environmen t. Considering these factors, management determined it was appropriate to maintain the existing weighting, and weigh the "most likely" scenario 50% and the "moderate recession" scenario 50% at March 31, 2025. ◦As of June 30, 2025, the "most likely" scenario forecasted Ohio unemployment between 5.02% and 5.35% during the next four quarters. In determining the appropriate weighting of scenarios at June 30, 2025, management considered the range of forecasted unemployment as well as a number of economic indicators. While some economic indications are showing stabilization or slight improvement, volatile and low levels of consumer confidence, higher unemployment rates, the impact of elevated inflation for several years with the impact of tariffs being unknown, the interest rate environment, financial system stress, geopolitical conflict (including conflict related to tariffs), uncertainty regarding fiscal policy of the new political administration, including tariffs, and stress in the commercial real estate sector cause uncertainty to the overall economic environmen t. Considering these factors, management determined it was appropriate to maintain the existing weighting, and weigh the "most likely" scenario 50% and the "moderate recession" scenario 50% at June 30, 2025. ◦As of September 30, 2025, the "most likely" scenario forecasted Ohio unemployment between 5.05% and 5.49% during the next four quarters. In determining the appropriate weighting of scenarios at September 30, 2025, management considered the range of forecasted unemployment as well as a number of economic indicators. While some economic indications are showing stabilization or slight improvement, volatile and low levels of consumer confidence, higher unemployment rates, the impact of elevated inflation for several years with the impact of tariffs being unknown, the interest rate environment, geopolitical conflict (including conflict related to tariffs), uncertainty regarding fiscal policy of the current political administration, including tariffs, and continued stress in the commercial real estate sector cause uncertainty to the overall economic environmen t. Considering these factors, management determined it was appropriate to maintain the existing weighting, and weigh the "most likely" scenario 50% and the "moderate recession" scenario 50% at September 30, 2025. Qualitative Considerations Park reviews various internal and external factors to consider the need for any qualitative adjustments to the quantitative model. Factors considered include the following: •The nature and volume of Park’s financial assets; the existence, growth, and effect of any concentrations of credit and the volume and severity of past due financial assets, the volume of nonaccrual assets, and the volume and severity of adversely classified or graded assets. Specifically, management considers: ◦Trends (e.g., growth, reduction) in specific categories of the loan portfolio, as well as adjustments to the types of loans offered by Park. ◦Level of and trend in loan delinquencies, troubled loans, commercial watch list loans and nonperforming loans. ◦Level of and trend in new nonaccrual loans. ◦Level of and trend in loan charge-offs and recoveries. •Park's lending policies and procedures, including changes in lending strategies, underwriting standards and practices for collections, charge-offs, and recoveries. •The quality of Park’s credit review function. •The experience, ability, and depth of Park’s lending, investment, collection, and other relevant management and staff. •The effect of other external factors such as the regulatory, legal and technological environments; competition; geopolitical conflict; and events such as natural disasters or pandemics. •Actual and expected changes in international, national, regional, and local economic and business conditions and developments in the markets in which Park operates that affect the collectability of financial assets. •Where the U.S. economy is within a given credit cycle. •The extent that there is government assistance (stimulus). Qualitative adjustments amounted to $2.2 million and $1.2 million at September 30, 2025 and December 31, 2024, respectively. Qualitative adjustments included a $760,000 and $757,000 reserve at September 30, 2025 and December 31, 2024, respectively, related to Hurricane Helene which impacted borrowers in Park's Carolina region. This reserve considers the overall population of loans to borrowers in this area. While Helene impacted this region in October 2024, many borrowers are still navigating the insurance claim process and local businesses are waiting to see the full economic impact on tourist season. Management will continue to evaluate potential losses as a result of Hurricane Helene as additional information becomes available. Qualitative adjustments also included a $1.1 million reserve at September 30, 2025 related to several special purpose mortgage loan programs to assist borrowers in attaining home ownership. As of September 30, 2025, the total loans in these special purpose mortgage loan programs totaled $225.0 million. Delinquency rates within these special purpose mortgage loan programs have become higher than those of Park's traditional 30-year mortgage portfolio loans. These special purpose mortgage loan programs require very little, if any, down payment, and the loan-to-value on these loans are generally at 90% or above. For these reasons, management expects that the PD and LGD related to loans within these programs will be higher than that of Park's standard 30-year portfolio loans and established a qualitative factor related to the increased risk of loss on mortgage loans within these programs. Management will continue to evaluate this portfolio as additional information becomes available. ACL Activity The activity in the ACL for the three-month and nine-month periods ended September 30, 2025 and September 30, 2024 is summarized in the following tables:
| Three Months Ended September 30, 2025
(In thousands) | Commercial, financial and agricultural |  | Commercial real estate |  | Construction real estate |  | Residential real estate |  | Consumer |  | Leases |  | Total
ACL: |  |  |  |  |  |  |  |  |  |  |  |  |
Beginning balance | $ | 11,103 |  |  | $ | 20,499 |  |  | $ | 7,765 |  |  | $ | 24,510 |  |  | $ | 25,716 |  |  | $ | 192 |  |  | $ | 89,785 |
Charge-offs | 475 |  |  | — |  |  | — |  |  | 27 |  |  | 3,424 |  |  | — |  |  | 3,926 |
Recoveries | 195 |  |  | 52 |  |  | 4 |  |  | 14 |  |  | 1,604 |  |  | — |  |  | 1,869 |
Net charge-offs/(recoveries) | $ | 280 |  |  | $ | (52) |  |  | $ | (4) |  |  | $ | 13 |  |  | $ | 1,820 |  |  | $ | — |  |  | $ | 2,057 |
Provision for (recovery of) credit losses | 2,536 |  |  | (36) |  |  | (650) |  |  | 537 |  |  | 1,579 |  |  | 64 |  |  | 4,030 |
Ending balance | $ | 13,359 |  |  | $ | 20,515 |  |  | $ | 7,119 |  |  | $ | 25,034 |  |  | $ | 25,475 |  |  | $ | 256 |  |  | $ | 91,758 |
| Three Months Ended September 30, 2024
(In thousands) | Commercial, financial and agricultural |  | Commercial real estate |  | Construction real estate |  | Residential real estate |  | Consumer |  | Leases |  | Total
ACL: |  |  |  |  |  |  |  |  |  |  |  |  |
Beginning balance | $ | 16,663 |  |  | $ | 16,855 |  |  | $ | 5,867 |  |  | $ | 19,450 |  |  | $ | 27,579 |  |  | $ | 161 |  |  | $ | 86,575 |
Charge-offs | 3,151 |  |  | 40 |  |  | — |  |  | — |  |  | 3,363 |  |  | — |  |  | 6,554 |
Recoveries | 79 |  |  | 223 |  |  | 25 |  |  | 40 |  |  | 1,534 |  |  | — |  |  | 1,901 |
Net charge-offs/(recoveries) | $ | 3,072 |  |  | $ | (183) |  |  | $ | (25) |  |  | $ | (40) |  |  | $ | 1,829 |  |  | $ | — |  |  | $ | 4,653 |
Provision for credit losses | 284 |  |  | 1,818 |  |  | 194 |  |  | 768 |  |  | 2,247 |  |  | 4 |  |  | 5,315 |
Ending balance | $ | 13,875 |  |  | $ | 18,856 |  |  | $ | 6,086 |  |  | $ | 20,258 |  |  | $ | 27,997 |  |  | $ | 165 |  |  | $ | 87,237 |
| Nine Months Ended September 30, 2025
(In thousands) | Commercial, financial and agricultural |  | Commercial real estate |  | Construction real estate |  | Residential real estate |  | Consumer |  | Leases |  | Total
ACL: |  |  |  |  |  |  |  |  |  |  |  |  |
Beginning balance | $ | 12,683 |  |  | $ | 19,571 |  |  | $ | 7,125 |  |  | $ | 22,355 |  |  | $ | 26,081 |  |  | $ | 151 |  |  | $ | 87,966 |
Charge-offs | 1,048 |  |  | 68 |  |  | — |  |  | 152 |  |  | 10,222 |  |  | — |  |  | $ | 11,490 |
Recoveries | 719 |  |  | 850 |  |  | 1,115 |  |  | 114 |  |  | 4,845 |  |  | — |  |  | $ | 7,643 |
Net charge-offs/(recoveries) | $ | 329 |  |  | $ | (782) |  |  | $ | (1,115) |  |  | $ | 38 |  |  | $ | 5,377 |  |  | $ | — |  |  | $ | 3,847 |
Provision for (recovery of) credit losses | 1,005 |  |  | 162 |  |  | (1,121) |  |  | 2,717 |  |  | 4,771 |  |  | 105 |  |  | $ | 7,639 |
Ending balance | $ | 13,359 |  |  | $ | 20,515 |  |  | $ | 7,119 |  |  | $ | 25,034 |  |  | $ | 25,475 |  |  | $ | 256 |  |  | $ | 91,758 |
| Nine Months Ended September 30, 2024
(In thousands) | Commercial, financial and agricultural |  | Commercial real estate |  | Construction real estate |  | Residential real estate |  | Consumer |  | Leases |  | Total
ACL: |  |  |  |  |  |  |  |  |  |  |  |  |
Beginning balance | $ | 15,496 |  |  | $ | 16,374 |  |  | $ | 5,227 |  |  | $ | 18,818 |  |  | $ | 27,713 |  |  | $ | 117 |  |  | $ | 83,745 |
Charge-offs | 3,657 |  |  | 40 |  |  | — |  |  | 31 |  |  | 9,163 |  |  | — |  |  | 12,891 |
Recoveries | 340 |  |  | 250 |  |  | 1,058 |  |  | 307 |  |  | 3,820 |  |  | — |  |  | 5,775 |
Net charge-offs/(recoveries) | $ | 3,317 |  |  | $ | (210) |  |  | $ | (1,058) |  |  | $ | (276) |  |  | $ | 5,343 |  |  | $ | — |  |  | $ | 7,116 |
Provision for (recovery of) credit losses | 1,696 |  |  | 2,272 |  |  | (199) |  |  | 1,164 |  |  | 5,627 |  |  | 48 |  |  | 10,608 |
Ending balance | $ | 13,875 |  |  | $ | 18,856 |  |  | $ | 6,086 |  |  | $ | 20,258 |  |  | $ | 27,997 |  |  | $ | 165 |  |  | $ | 87,237 |

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