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SUMMARY OF SIGNIFICANT ACCOUNTING POLICIES | 3 Months Ended
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Mar. 31, 2025
Organization, Consolidation and Presentation of Financial Statements [Abstract] |
SUMMARY OF SIGNIFICANT ACCOUNTING POLICIES | 1. SUMMARY OF SIGNIFICANT ACCOUNTING POLICIES Basis of Presentation The accompanying unaudited consolidated financial statements of Central Pacific Financial Corp. and Subsidiaries (herein referred to as the "Company," "we," "us," or "our") have been prepared in accordance with U.S. generally accepted accounting principles ("GAAP") for interim financial information and instructions to Form 10-Q and Rule 10-01 of Regulation S-X. Accordingly, certain information and footnote disclosures normally included in financial statements prepared in accordance with GAAP have been condensed or omitted pursuant to such rules and regulations. These interim condensed consolidated financial statements and notes should be read in conjunction with the Company's consolidated financial statements and notes thereto filed on Form 10-K for the fiscal year ended December 31, 2024. In the opinion of management, all adjustments necessary for a fair presentation have been made and include all normal recurring adjustments. Interim results of operations are not necessarily indicative of results to be expected for the year. Allowance for Credit Losses on Loans The allowance for credit losses ("ACL") on loans is a valuation account that is deducted from the amortized cost basis of loans to present the net amount expected to be collected on loans. The Company’s policy is to charge off a loan against the ACL during the period in which the loan is deemed to be uncollectible and all interest previously accrued but uncollected, is reversed against current period interest income. Subsequent receipts, if any, are credited first to the remaining principal, then to the ACL on loans as recoveries, and finally to interest income. The ACL on loans represents management's estimate of all expected credit losses over the expected life of the Company’s loan portfolio as of a given balance sheet date. Management estimates the ACL balance using relevant information available from both internal and external sources, regarding the collectability of cash flows impacted by past events, current conditions, and reasonable and supportable forecasts of future economic conditions. When the Company is unable to forecast future economic events, management may revert to historical information. The Company's ACL model incorporates a reasonable and supportable forecast period of one year and reverts to historical loss information on a straight-line basis over one year when its forecast is no longer deemed reasonable and supportable. Historical loss experience provides the basis for the Company’s expected credit loss estimate. Adjustments to historical loss information may be made for differences in current loan-specific risk characteristics, such as differences in underwriting standards, portfolio mix, or when historical asset terms do not reflect the contractual terms of the financial assets being evaluated. The Company's ACL model may also consider other adjustments to address changes in conditions, trends, and circumstances such as local industry changes that could have a significant impact on the risk profile of the loan portfolio and provide for adjustments that may not be reflected or captured in the historical loss data. These factors include: lending policies, imprecision in forecasting future economic conditions, loan profile, lending staff, problem loan trends, loan review, collateral, credit concentration, or other internal and external factors. The Company uses Moody’s Analytics ("Moody's"), a firm widely recognized and used for its research, analysis, and economic forecasts, for its economic forecast assumptions. The Company generally uses Moody’s most recent Baseline forecast, which is updated at least monthly with a variety of upside and downside economic scenarios and considers both national and Hawaii-specific economic indicators. In addition, the Company uses a qualitative factor for forecast imprecision to account for economic and market volatility or instability. The ACL on loans is measured on a collective or pool basis when similar risk characteristics exist. The following is a description and the risk characteristics of each segment: Commercial and industrial loans - SBA Paycheck Protection Program loans Paycheck Protection Program (“PPP”) loans are considered lower risk as they are guaranteed by the Small Business Administration (“SBA”) and may be forgivable in whole or in part in accordance with the requirements of the PPP. Commercial and industrial loans - Others Commercial and industrial loans consist primarily of term loans and lines of credit to small- and middle-market businesses and professionals. The predominant risk characteristics of this segment are the cash flows of the business we lend to, global cash flows including guarantor liquidity, as well as economic and market conditions. Although our underwriting policy and practice generally requires secondary sources of support or collateral to mitigate risk, cash flow generated from the borrower’s business is typically regarded as the principal source of repayment. Construction loans Construction loans include both residential and commercial development projects. Each construction project is evaluated for economic viability and construction loans pose higher credit risks than typical secured loans. Financial strength of the borrower, completion risk (the risk that the project will not be completed on time and within budget) and geographic location are the predominant risk characteristics of this segment. Commercial real estate loans - Multi-family Multi-family mortgage loans can comprise multi-building properties with extensive amenities or a single building with no amenities. The predominant risk characteristic of this segment is operating risk or the ability to generate sufficient rental income from the operation of the property. Commercial real estate loans - Others Commercial real estate loans are secured by commercial properties. The predominant risk characteristic of this segment is operating risk, which is the risk that the borrower will be unable to generate sufficient cash flows from the operation of the property. Interest rate conditions and the commercial real estate market through economic cycles also impact risk levels. Residential mortgage loans Residential mortgage loans primarily includes fixed-rate or adjustable-rate loans secured by single-family owner-occupied primary residences in Hawaii. Economic conditions such as unemployment levels, future changes in interest rates, Hawaii home prices and other market factors impact the level of credit risk inherent in the portfolio. Home equity lines of credit Home equity lines of credit include fixed or floating interest rate loans and are also primarily secured by single-family owner-occupied primary residences in Hawaii. They are underwritten based on a minimum FICO score, maximum debt-to-income ratio, and maximum combined loan-to-value ratio. Home equity lines of credit are monitored based on credit score, delinquency, end of draw period and maturity. Consumer loans - Other revolving Other revolving consumer loans consist of unsecured consumer lines of credit. The predominant risk characteristics of this segment relate to current and projected economic conditions, as well as employment and income levels attributed to the borrower. Consumer loans - Non-revolving Non-revolving consumer loans consist of non-revolving (term) consumer loans, including automobile dealer loans. The predominant risk characteristics of this segment relate to current and projected economic conditions, as well as employment and income levels attributed to the borrower. Purchased consumer loans Purchased consumer loans consist of automobile and unsecured consumer loans. Credit risk for purchased consumer loans is managed on a pooled basis. The predominant risk characteristics of this segment include current and projected economic conditions, employment and income levels, and the quality of purchased consumer loans. The following table presents the Company's loan portfolio segments and the methodology used to measure expected credit losses. The historical look-back period is 2008 to present, economic forecast length is one year and the reversion method is one year (on a straight-line basis) for all segments.
|  | Expected Credit Loss Methodology |  | Historical Look-Back Period |  | Economic Forecast Length |  | Reversion Method
Loan Segment |  | After June 30, 2023 |  | June 30, 2023 and Prior |  |  |
Commercial and industrial - SBA PPP |  | Zero Loss |  | Zero Loss |  | 2008 to present |  | One year |  | One year (straight-line basis)
Commercial and industrial - All others |  | DCF |  | PD/LGD |  |  |
Construction |  | DCF |  | PD/LGD |  |  |
Commercial real estate - Multi-family |  | DCF |  | PD/LGD |  |  |
Commercial real estate - All others |  | DCF |  | PD/LGD |  |  |
Residential mortgage |  | DCF |  | Loss-Rate Migration |  |  |
Home equity |  | DCF |  | Loss-Rate Migration |  |  |
Consumer - Other revolving |  | DCF |  | Loss-Rate Migration |  |  |
Consumer - Non-revolving |  | DCF |  | Loss-Rate Migration |  |  |
Consumer - Purchased portfolios |  | WARM |  | WARM |  |  |
During the third quarter of 2023, the Company updated its methodology to measure expected credit losses from the Probability of Default/Loss Given Default ("PD/LGD") or Loss-Rate Migration methods to the Discounted Cash Flow ("DCF") method for all segments except the SBA PPP and purchased consumer loan segments. The Company believes that the DCF methodology has better alignment with the Current Expected Credit Losses ("CECL") standard for forward looking forecasting, while also factoring in more detailed assumptions. At the time of the methodology update, the Company ran the ACL model under both the current and previous methodologies and noted that the changes to the ACL model and the differences in methodologies did not result in a material impact to the Company's financial statements and as a percentage of the ACL. The Company is utilizing an industry leading software platform to perform the DCF analysis using a historical look back period of 2008 to present. The Company continues to use the Moody's baseline forecast with an economic forecast length of one year and a one-year, straight-line reversion method. We revert to the historical average of the macroeconomic variables being used. Forecast models exclude the post-2019 COVID-19 pandemic period due to abnormal and volatile behavior. The ACL on the purchased consumer loan portfolios continues to be calculated using the Remaining Life methodology (also known as the Weighted Average Remaining Maturity or "WARM" methodology) as this portfolio is evaluated on a pooled basis. Because SBA PPP loans are guaranteed by the SBA and may be forgivable in whole or in part in accordance with the requirements of the PPP we anticipate zero losses on these loans and accordingly apply a Zero Loss methodology. The following is a description of the methodologies utilized to measure expected credit losses from the third quarter of 2023 to present: Discounted Cash Flow The DCF methodology calculates CECL reserves as the difference between the amortized cost of a loan and the discounted expected value of future cash flows. Expected future cash flows are calculated based on assumptions of PD/LGD, prepayments and recovery rates, and are discounted using the loan’s effective interest rate. Remaining Life or Weighted Average Remaining Maturity Under the remaining life or WARM methodology, lifetime losses are calculated by determining the remaining life of the loan pool, and then applying a loss rate over this remaining life. The methodology considers historical loss experience to estimate credit losses for the remaining balance of the loan pool. The calculated loss rate is applied to the contractual term (adjusted for prepayments) to determine the loan pool’s current expected credit losses. The following is a description of the methodologies utilized to measure expected credit losses as of June 30, 2023 and prior: Probability of Default/Loss Given Default The PD/LGD calculation is based on a cohort methodology whereby loans in the same cohort are tracked over time to identify defaults and corresponding losses. PD/LGD analysis requires a portfolio segmented into pools, and we elected to then further sub-segment by risk characteristics such as Risk Rating, loans modified for borrowers experiencing financial difficulty, TDRs prior to the adoption of ASU 2022-02 and nonaccrual status to measure losses accurately. PD measures the count or dollar amount of loans that defaulted in a given cohort. LGD measures the losses related to the loans that defaulted. Total loss rate is calculated using the formula 'PD times LGD'. Loss-Rate Migration Loss-rate migration analysis is a cohort-based approach that measures cumulative net charge-offs over a defined time-horizon to calculate a loss rate that will be applied to the loan pool. Loss-rate migration analysis requires the portfolio to be segmented into pools then further sub-segmented by risk characteristics such as days past due, delinquency counters, loans modified for borrowers experiencing financial difficulty, TDRs prior to the adoption of ASU 2022-02 and nonaccrual status to measure loss rates accurately. The key inputs to run a loss-rate migration analysis are the length and frequency of the migration period, the dates for the migration periods to start and the number of migration periods used for the analysis. For each migration period, the analysis will determine the outstanding balance in each segment and/or sub-segment at the start of each period. These loans will then be followed for the length of the migration period to identify the amount of associated charge-offs and recoveries. A loss rate for each migration period is calculated using the formula: net charge-offs over the period divided by beginning loan balance. Other Under both the previous and current methodologies utilized to measure expected credit losses, if a loan ceases to share similar risk characteristics with other loans in its segment, it will be moved to a different pool sharing similar risk characteristics. Loans that do not share risk characteristics are evaluated on an individual basis based on the fair value of the collateral or other approaches such as the discounted cash flows methodology. Individually evaluated loans are not included in the collective evaluation. Impact of Recently Issued Accounting Pronouncements on Future Filings In December 2023, the FASB issued ASU 2023-09, "Income Taxes (Topic 740): Improvements to Income Tax Disclosures". ASU 2023-09 expands existing income tax disclosures for rate reconciliations by requiring disclosure of certain specific categories in the rate reconciliation, as well as additional qualitative information about the reconciliation, and additional disaggregated information about income taxes paid. ASU 2023-09 is effective for fiscal years beginning after December 15, 2024, with early adoption permitted, and is to be applied on a prospective basis. The Company adopted the amendments of ASU 2023-09 effective January 1, 2025, which did not have a material impact on its consolidated financial statements. The Company will include the required disclosures in its Annual Report on Form 10-K for the year ending December 31, 2025. In November 2024, the FASB issued ASU 2024-03, "Income Statement—Reporting Comprehensive Income—Expense Disaggregation Disclosures (Subtopic 220-40): Disaggregation of Income Statement Expenses". ASU 2024-03 requires public entities to provide disaggregated disclosures, in the notes to the financial statements, of certain categories of expenses that are included in expense line items on the face of the income statement. The amendments in ASU 2024-03 are effective for annual periods beginning after December 15, 2026, and interim periods within fiscal years beginning after December 15, 2027. Early adoption is permitted. The Company does not expect the adoption of this standard to have a material impact on the Company’s financial position or results of operations.

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