The allowance for credit losses ("ACL") for 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 for loans as recoveries, and finally to interest income.

The ACL for 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 includes 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.

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 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 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.

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 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 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 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.

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.

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 consist of dealer 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

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

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 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.

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 of the loan. 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 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 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.

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.