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Allowance For Credit Losses | 6 Months Ended
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Jun. 30, 2023
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. During the first quarter of 2023, Park adopted ASU 2022-02. This standard was adopted using a modified retrospective transition method on January 1, 2023, resulting in a $383,000 increase to the ACL. A cumulative effect adjustment resulting in a $303,000 decrease to retained earnings was also recorded as a result of the adoption of ASU 2022-02. 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 the residential real estate portfolio segments. Peer data was incorporated into the analysis for the commercial real estate, the construction real estate, and the consumer portfolio segments. Park updated the LDA in the fourth quarter of 2022 with data through September 30, 2022. After considering the impact of the inclusion of periods impacted by COVID, as well as analysis of the ongoing applicability of the selected peer group, management decided it was appropriate to continue to utilize the LDA analysis from the fourth quarter of 2019 as the correlation of the LDA was higher. •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, a forecast model is utilized to estimate PDs. •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. •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 2022. •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. ◦A s of December 31, 2022, the "most likely" scenario forecasted Ohio unemployment between 4.14% and 4.36% during the next four quarters. In determining the appropriate weighting of scenarios at December 31, 2022, management considered the range of forecasted unemployment as well as a number of economic indicators. The continued high level of inflation, historically low consumer confidence, rising interest rates, geopolitical conflict (including the conflict between Russia and Ukraine), and workforce and supply chain challenges 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, 20 22. ◦A s of March 31, 2023, the "most likely" scenario forecasted Ohio unemployment between 4.15% and 4.51% during the next four quarters. In determining the appropriate weighting of scenarios at March 31, 2023, management considered the range of forecasted unemployment as well as a number of economic indicators. The continued high level of inflation, historically low consumer confidence, rising interest rates, financial system stress related to recent bank failures, geopolitical conflict, and workforce challenges 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 March 31, 2023. ◦A s of June 30, 2023, the "most likely" scenario forecasted Ohio unemployment between 4.01% and 4.62% during the next four quarters. In determining the appropriate weighting of scenarios at June 30, 2023, management considered the range of forecasted unemployment as well as a number of economic indicators. The continued elevated levels of inflation, volatile levels of consumer confidence, the likelihood of interest rates increasing, financial system stress and geopolitical conflict 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 June 30, 2023. 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 collectibility of financial assets. •Where the U.S. economy is within a given credit cycle. •The extent that there is government assistance (stimulus). As of June 30, 2023 and December 31, 2022, Park had $3.1 million and $4.2 million, respectively, of PPP loans which were included in the commercial, financial and agricultural portfolio segment. These loans are guaranteed by the SBA and thus have not been reserved for using the same methodology as the rest of Park’s loan portfolio. A 10 basis point reserve at each of June 30, 2023 and December 31, 2022 was calculated for these loans to reflect minimal credit risk. ACL Activity The activity in the ACL for the three-month and the six-month periods ended June 30, 2023 and June 30, 2022 is summarized in the following tables:
| Three Months Ended June 30, 2023
(In thousands) | Commercial, financial and agricultural |  | Commercial real estate |  | Construction real estate |  | Residential real estate |  | Consumer |  | Leases |  | Total
ACL: |  |  |  |  |  |  |  |  |  |  |  |  |
Beginning balance | $ | 16,572 |  |  | $ | 17,946 |  |  | $ | 5,362 |  |  | $ | 17,889 |  |  | $ | 28,053 |  |  | $ | 124 |  |  | $ | 85,946 |
Charge-offs | 188 |  |  | 530 |  |  | — |  |  | 14 |  |  | 1,953 |  |  | — |  |  | 2,685 |
Recoveries | 84 |  |  | — |  |  | 12 |  |  | 114 |  |  | 1,243 |  |  | — |  |  | 1,453 |
Net charge-offs/(recoveries) | $ | 104 |  |  | $ | 530 |  |  | $ | (12) |  |  | $ | (100) |  |  | $ | 710 |  |  | $ | — |  |  | $ | 1,232 |
(Recovery of) provision for credit losses | (190) |  |  | 1,725 |  |  | (488) |  |  | 430 |  |  | 1,027 |  |  | (12) |  |  | 2,492 |
Ending balance | $ | 16,278 |  |  | $ | 19,141 |  |  | $ | 4,886 |  |  | $ | 18,419 |  |  | $ | 28,370 |  |  | $ | 112 |  |  | $ | 87,206 |
| Three Months Ended June 30, 2022
(In thousands) | Commercial, financial and agricultural |  | Commercial real estate |  | Construction real estate |  | Residential real estate |  | Consumer |  | Leases |  | Total
ACL: |  |  |  |  |  |  |  |  |  |  |  |  |
Beginning balance | $ | 13,288 |  |  | $ | 23,731 |  |  | $ | 4,230 |  |  | $ | 11,584 |  |  | $ | 25,797 |  |  | $ | 231 |  |  | $ | 78,861 |
Charge-offs | 723 |  |  | 598 |  |  | 33 |  |  | 46 |  |  | 1,002 |  |  | — |  |  | 2,402 |
Recoveries | 316 |  |  | 540 |  |  | 29 |  |  | 54 |  |  | 1,058 |  |  | 1 |  |  | 1,998 |
Net charge-offs/(recoveries) | $ | 407 |  |  | $ | 58 |  |  | $ | 4 |  |  | $ | (8) |  |  | $ | (56) |  |  | $ | (1) |  |  | $ | 404 |
(Recovery of) provision for credit losses | (134) |  |  | (1,334) |  |  | 165 |  |  | 2,027 |  |  | 2,296 |  |  | (29) |  |  | 2,991 |
Ending balance | $ | 12,747 |  |  | $ | 22,339 |  |  | $ | 4,391 |  |  | $ | 13,619 |  |  | $ | 28,149 |  |  | $ | 203 |  |  | $ | 81,448 |
| Six Months Ended June 30, 2023
(In thousands) | Commercial, financial and agricultural |  | Commercial real estate |  | Construction real estate |  | Residential real estate |  | Consumer |  | Leases |  | Total
ACL: |  |  |  |  |  |  |  |  |  |  |  |  |
Beginning balance | $ | 16,987 |  |  | $ | 17,829 |  |  | $ | 5,550 |  |  | $ | 16,831 |  |  | $ | 28,021 |  |  | $ | 161 |  |  | $ | 85,379 |
Impact of Adoption of ASU 2022-02 | 222 |  |  | 181 |  |  | — |  |  | (20) |  |  | — |  |  | — |  |  | 383 |
Charge-offs | 537 |  |  | 530 |  |  | — |  |  | 43 |  |  | 3,810 |  |  | — |  |  | 4,920 |
Recoveries | 130 |  |  | 232 |  |  | 508 |  |  | 471 |  |  | 2,348 |  |  | — |  |  | 3,689 |
Net charge-offs/(recoveries) | $ | 407 |  |  | $ | 298 |  |  | $ | (508) |  |  | $ | (428) |  |  | $ | 1,462 |  |  | $ | — |  |  | $ | 1,231 |
(Recovery of) provision for credit losses | (524) |  |  | 1,429 |  |  | (1,172) |  |  | 1,180 |  |  | 1,811 |  |  | (49) |  |  | 2,675 |
Ending balance | $ | 16,278 |  |  | $ | 19,141 |  |  | $ | 4,886 |  |  | $ | 18,419 |  |  | $ | 28,370 |  |  | $ | 112 |  |  | $ | 87,206 |
| Six Months Ended June 30, 2022
(In thousands) | Commercial, financial and agricultural |  | Commercial real estate |  | Construction real estate |  | Residential real estate |  | Consumer |  | Leases |  | Total
ACL: |  |  |  |  |  |  |  |  |  |  |  |  |
Beginning balance | $ | 14,025 |  |  | $ | 25,466 |  |  | $ | 5,758 |  |  | $ | 11,424 |  |  | $ | 26,286 |  |  | $ | 238 |  |  | $ | 83,197 |
Charge-offs | 913 |  |  | 598 |  |  | 33 |  |  | 81 |  |  | 2,118 |  |  | 6 |  |  | 3,749 |
Recoveries | 434 |  |  | 588 |  |  | 530 |  |  | 86 |  |  | 1,975 |  |  | 1 |  |  | 3,614 |
Net charge-offs/(recoveries) | $ | 479 |  |  | $ | 10 |  |  | $ | (497) |  |  | $ | (5) |  |  | $ | 143 |  |  | $ | 5 |  |  | $ | 135 |
(Recovery of) provision for credit losses | (799) |  |  | (3,117) |  |  | (1,864) |  |  | 2,190 |  |  | 2,006 |  |  | (30) |  |  | (1,614) |
Ending balance | $ | 12,747 |  |  | $ | 22,339 |  |  | $ | 4,391 |  |  | $ | 13,619 |  |  | $ | 28,149 |  |  | $ | 203 |  |  | $ | 81,448 |
ACL Summary Loans collectively evaluated for impairment in the following tables include all performing loans at June 30, 2023 and December 31, 2022, as well as nonperforming loans internally classified as consumer loans. Nonperforming consumer loans are not typically individually evaluated for impairment, but receive a portion of the statistical allocation of the ACL. Loans individually evaluated for impairment include all internally classified commercial nonaccrual loans at June 30, 2023 and all internally classified commercial nonaccrual loans and TDRs at December 31, 2022, which are individually evaluated for impairment in accordance with U.S. GAAP (see Note 1 - Summary of Significant Accounting Policies of the Notes to Consolidated Financial Statements included in Park’s 2022 Form 10-K). The composition of the ACL at June 30, 2023 and at December 31, 2022 was as follows:
| June 30, 2023
(In thousands) | Commercial, financial and agricultural |  | Commercial real estate |  | Construction real estate |  | Residential real estate |  | Consumer |  | Leases |  | Total
ACL: |  |  |  |  |  |  |  |  |  |  |  |  |
Ending allowance balance attributed to loans: |  |  |  |  |  |  |  |  |  |  |  |  |
Individually evaluated for impairment | $ | 3,899 |  | $ | 233 |  | $ | — |  | $ | — |  | $ | — |  | $ | — |  | $ | 4,132
Collectively evaluated for impairment | 12,379 |  | 18,908 |  | 4,886 |  | 18,419 |  | 28,370 |  | 112 |  | 83,074
Acquired with deteriorated credit quality | — |  | — |  | — |  | — |  | — |  | — |  | —
Total ending allowance balance | $ | 16,278 |  | $ | 19,141 |  | $ | 4,886 |  | $ | 18,419 |  | $ | 28,370 |  | $ | 112 |  | $ | 87,206
Loan balance: |  |  |  |  |  |  |  |  |  |  |  |  |
Loans individually evaluated for impairment | $ | 22,463 |  | $ | 17,621 |  | $ | 986 |  | $ | 2,331 |  | $ | — |  | $ | 486 |  | $ | 43,887
Loans collectively evaluated for impairment | 1,264,477 |  | 1,778,418 |  | 273,077 |  | 1,883,644 |  | 1,942,257 |  | 17,894 |  | 7,159,767
Loans acquired with deteriorated credit quality | 63 |  | 3,401 |  | 643 |  | 348 |  | — |  | — |  | 4,455
Total ending loan balance | $ | 1,287,003 |  | $ | 1,799,440 |  | $ | 274,706 |  | $ | 1,886,323 |  | $ | 1,942,257 |  | $ | 18,380 |  | $ | 7,208,109
ACL as a percentage of loan balance: |  |  |  |  |  |  |  |  |  |  |  |  |
Loans individually evaluated for impairment | 17.36 | % |  | 1.32 | % |  | — | % |  | — | % |  | — | % |  | — | % |  | 9.42 | %
Loans collectively evaluated for impairment | 0.98 | % |  | 1.06 | % |  | 1.79 | % |  | 0.98 | % |  | 1.46 | % |  | 0.63 | % |  | 1.16 | %
Loans acquired with deteriorated credit quality | — | % |  | — | % |  | — | % |  | — | % |  | — | % |  | — | % |  | — | %
Total | 1.26 | % |  | 1.06 | % |  | 1.78 | % |  | 0.98 | % |  | 1.46 | % |  | 0.61 | % |  | 1.21 | %
|  | December 31, 2022
(In thousands) |  | Commercial, financial and agricultural |  | Commercial real estate |  | Construction real estate |  | Residential real estate |  | Consumer |  | Leases |  | Total
ACL: |  |  |  |  |  |  |  |  |  |  |  |  |  |
Ending allowance balance attributed to loans: |  |  |  |  |  |  |  |  |  |  |  |  |  |
Individually evaluated for impairment |  | $ | 3,426 |  | $ | 131 |  | $ | — |  | $ | — |  | $ | — |  | $ | 9 |  | $ | 3,566
Collectively evaluated for impairment |  | 13,561 |  | 17,698 |  | 5,550 |  | 16,831 |  | 28,021 |  | 152 |  | 81,813
Acquired with deteriorated credit quality |  | — |  | — |  | — |  | — |  | — |  | — |  | —
Total ending allowance balance |  | $ | 16,987 |  | $ | 17,829 |  | $ | 5,550 |  | $ | 16,831 |  | $ | 28,021 |  | $ | 161 |  | $ | 85,379
Loan balance: |  |  |  |  |  |  |  |  |  |  |  |  |  |
Loans individually evaluated for impairment |  | $ | 41,307 |  | $ | 32,423 |  | $ | 1,712 |  | $ | 2,191 |  | $ | — |  | $ | 708 |  | $ | 78,341
Loans collectively evaluated for impairment |  | 1,259,524 |  | 1,758,118 |  | 323,043 |  | 1,794,302 |  | 1,904,981 |  | 18,929 |  | 7,058,897
Loans acquired with deteriorated credit quality |  | 102 |  | 3,513 |  | 660 |  | 378 |  | — |  | — |  | 4,653
Total ending loan balance |  | $ | 1,300,933 |  | $ | 1,794,054 |  | $ | 325,415 |  | $ | 1,796,871 |  | $ | 1,904,981 |  | $ | 19,637 |  | $ | 7,141,891
ACL as a percentage of loan balance: |  |  |  |  |  |  |  |  |  |  |  |  |  |
Loans individually evaluated for impairment |  | 8.29 | % |  | 0.40 | % |  | — | % |  | — | % |  | — | % |  | 1.27 | % |  | 4.55 | %
Loans collectively evaluated for impairment |  | 1.08 | % |  | 1.01 | % |  | 1.72 | % |  | 0.94 | % |  | 1.47 | % |  | 0.80 | % |  | 1.16 | %
Loans acquired with deteriorated credit quality |  | — | % |  | — | % |  | — | % |  | — | % |  | — | % |  | — | % |  | — | %
Total |  | 1.31 | % |  | 0.99 | % |  | 1.71 | % |  | 0.94 | % |  | 1.47 | % |  | 0.82 | % |  | 1.20 | %

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