The Company maintains an ACL for loans and unfunded loan commitments in accordance with ASC 326 - Financial Instruments - Credit Losses. ASC 326 requires the Company to initially recognize estimates for lifetime credit losses on loans and unfunded loan commitments at the time of origination or acquisition. The recognition of credit losses represents the Company’s best estimate of lifetime expected credit losses, given the facts and circumstances associated with a particular loan or group of loans with similar risk characteristics. Determining the ACL involves the use of significant management judgement and estimates, which are subject to change based on management’s ongoing assessment of the credit quality of the loan portfolio and changes in economic forecasts used in the Company’s ACL model. The Company uses a discounted cash flow model when determining estimates for the ACL for commercial real estate loans and commercial loans, which comprise the majority of the loan portfolio, and uses a historical loss rate model for retail loans. The Company also utilizes proxy loan data in its ACL model where the Company’s own historical data is not sufficiently available.

The discounted cash flow model is applied on an instrument-by-instrument basis, and for loans with similar risk characteristics, to derive estimates for the lifetime ACL for each loan. The discounted cash flow methodology relies on several significant components essential to the development of estimates for future cash flows on loans and unfunded loan commitments. These components consist of: (i) the estimated PD, (ii) the estimated LGD, which represents the estimated severity of the loss when a loan is in default, (iii) estimates for prepayment activity on loans, and (iv) the estimated exposure to the Company at default (“EAD”). The PD and LGD are heavily influenced by changes in economic forecasts and key variables employed in the model as well as our portfolio performance and composition over a reasonable and supportable period. The Company’s ACL methodology for unfunded loan commitments also includes assumptions concerning the probability an unfunded commitment will be drawn upon by the borrower. These assumptions are based on the Company’s historical experience.

The Company’s discounted cash flow ACL model for commercial real estate and commercial loans uses internally derived estimates for prepayments in determining the amount and timing of future contractual cash flows expected to be collected. The estimate of future cash flows also incorporates estimates for contractual amounts the Company believes may not be collected, which are based on assumptions for PD, LGD, and EAD. The EAD is determined by the contractual payment schedule and expected payment profile of the loan, incorporating estimates for expected prepayments and future draws on revolving credit facilities. The Company discounts cash flows using the effective interest rate on the loan. The effective interest rate represents the contractual rate on the loan; adjusted for any purchase premiums or discounts, and deferred fees and costs associated with an originated loan. The Company has made an accounting policy election to adjust the effective interest rate to take into consideration the effects of estimated prepayments. The ACL for loans is determined by measuring the amount by which a loan’s amortized cost exceeds its discounted cash flows expected to be collected. The ACL for credit facilities is determined by discounting estimates for cash flows not expected to be collected.

The PD for investor loans secured by real estate is based largely on a model provided by a third party, using proxy loan information. The PDs generated by this model are reflective of current and expected economic conditions in the commercial real estate market, and how they are expected to impact loan level and property level attributes, and ultimately the likelihood of a default event occurring. This model incorporates assumptions for PD at a loan’s maturity. Significant loan and property level attributes include: loan-to-value (“LTV”) ratios, debt service coverage ratio, loan size, loan vintage, and property types.

The PD for business loans secured by real estate and commercial loans is based on an internally developed PD rating scale that assigns PDs based on the Company’s internal credit risk grades for loans. This internally developed PD rating scale is based on a combination of the Company’s own historical data and observed historical data from the Company’s peers, which consist of banks that management believes align with our business profile. As credit risk grades change for these loans, the PD assigned to them also changes. As with investor loans secured by real estate, the PD for business loans secured by real estate and commercial loans is also impacted by current and expected economic conditions, including U.S. GDP growth and U.S. unemployment rate forecasts.

LGDs for commercial real estate loans are derived from a third party, using proxy loan information, and are based on loan and property level characteristics for loans in the Company’s loan portfolio, such as: LTV ratio, estimated time to resolution, property size, and current and estimated future market price changes for underlying collateral. LGDs are highly dependent upon LTV ratios, and incorporates estimates for the expense associated with managing the loans through to resolution. LGDs also incorporate an estimate for the loss severity associated with loans where the borrower fails to meet their debt obligation at maturity, such as through a balloon payment or the refinancing of the loan through another lender. External factors that have an impact on LGDs include: changes in the index for CRE pricing, GDP growth rate, unemployment rates, and the Consumer Price Index. LGDs are applied to each loan in the commercial real estate portfolio, and in conjunction with the PD, produce estimates for net cash flows not expected to be collected over the estimated term of the loan.

LGDs for commercial loans are also derived from a third party that has a considerable database of credit related information specific to the financial services industry and the type of loans within this segment, and is used to generate annual default information for commercial loans. These proxy LGDs are dependent upon data inputs such as: credit quality, borrower industry, region, borrower size, and debt seniority, as well as external factors,

In order to develop reasonable and supportable forecasts of future conditions, the Company estimates how those forecasts are expected to impact a borrower’s ability to satisfy their obligation to the Bank and the ultimate collectability of future cash flows over the life of a loan. The Company uses macroeconomic scenarios from an independent third party. These scenarios are based on past events, current conditions, and the likelihood of future events occurring. These scenarios typically are comprised of: a base-case scenario, an upside scenario, representing slightly better economic conditions than currently experienced and, a downside scenario, representing recessionary conditions. Management evaluates appropriateness of economic scenarios and may decide that a particular economic scenario or a combination of probability-weighted economic scenarios should be used in the Company’s ACL model. The economic scenarios chosen for the model, the extent to which more than one scenario is used, and the weights that are assigned to them, are based on the likelihood that the economy would perform better than each scenario, which is based in part on analysis performed by an independent third party. Economic scenarios chosen, as well as the assumptions within those scenarios, and whether to use a probability-weighted multiple scenario approach, can vary from one period to the next based on changes in current and expected economic conditions, and due to the occurrence of specific events. The Company’s ACL model at December 31, 2024 includes assumptions concerning the interest rate environment, general uncertainty concerning future economic conditions, and the potential for recessionary conditions.

The Company currently forecasts PDs and LGDs based on economic scenarios over a two-year period, which we believe is a reasonable and supportable period. Beyond this point, PDs and LGDs revert to their long-term averages. The Company has reflected this reversion over a period of three years in each of its economic scenarios used to generate the overall probability-weighted forecast. Changes in economic forecasts impact the PD, LGD, and EAD for each loan, and therefore influence the amount of future cash flows the Company does not expect to collect for each loan.

It is important to note that the Company’s ACL model relies on multiple economic and model variables, which are used in several economic scenarios. Although no one variable can fully demonstrate the sensitivity of the ACL calculation to changes in the economic variables used in the model, the Company has identified certain economic variables that have significant influence in the Company’s model for determining the ACL. These key economic variables include forecasted changes in the U.S. unemployment rate, U.S. real GDP growth, CRE prices, and interest rates.

The Company recognizes that historical information used as the basis for determining future expected credit losses may not always, by itself, provide a sufficient basis for determining future expected credit losses. The Company, therefore, considers the need for qualitative adjustments to the ACL on a quarterly basis. Qualitative adjustments may be related to and include, but not be limited to, factors such as: (i) management’s assessment of economic forecasts used in the model and how those forecasts align with management’s overall evaluation of current and expected economic conditions, (ii) organization specific risks such as credit concentrations, collateral specific risks, regulatory risks, and external factors that may ultimately impact credit quality, (iii) potential model limitations such as limitations identified through back-testing, and other limitations associated with factors such as underwriting changes, acquisition of new portfolios, and changes in portfolio segmentation, and (iv) management’s overall assessment of the adequacy of the ACL, including an assessment of model data inputs used to determine the ACL.

As of December 31, 2024, qualitative adjustments primarily relate to certain segments of the loan portfolio deemed by management to be of a higher-risk profile or other factors where management believes the quantitative component of the Company’s ACL model may not be fully reflective of levels deemed adequate in the judgement of management. Certain qualitative adjustments also relate to heightened uncertainty as to future macroeconomic conditions and the related impact on certain loan segments. Management reviews the need for an appropriate level of qualitative adjustments on a quarterly basis, and as such, the amount and allocation of qualitative adjustments may change in future periods.


	For the Year Ended December 31, 2024

(Dollars in thousands)	Beginning ACL Balance		Charge-offs		Recoveries		Provision for Credit Losses		Ending ACL Balance
Investor loans secured by real estate
CRE non-owner-occupied	$	31,030	$	(7,483)	$	1,500	$	1,361	$	26,408
Multifamily	56,312		(7,372)		5		4,360		53,305
Construction and land	9,314		—		—		(4,084)		5,230
SBA secured by real estate	2,182		(696)		194		42		1,722
Business loans secured by real estate
CRE owner-occupied	28,787		(5,983)		184		8,806		31,794
Franchise real estate secured	7,499		(212)		—		(1,451)		5,836
SBA secured by real estate	4,427		—		5		(601)		3,831
Commercial loans
Commercial and industrial	36,692		(3,837)		622		4,126		37,603
Franchise non-real estate secured	15,131		(100)		3,609		(7,846)		10,794
SBA non-real estate secured	458		(7)		12		(104)		359
Retail loans
Single family residential	505		—		3		685		1,193
Consumer loans	134		(896)		4		869		111
Totals	$	192,471	$	(26,586)	$	6,138	$	6,163	$	178,186


	For the Year Ended December 31, 2023
(Dollars in thousands)	Beginning ACL Balance		Charge-offs		Recoveries		Provision for Credit Losses		Ending ACL Balance
Investor loans secured by real estate
CRE non-owner-occupied	$	33,692	$	(3,472)	$	159	$	651	$	31,030
Multifamily	56,334		(1,872)		1		1,849		56,312
Construction and land	7,114		—		—		2,200		9,314
SBA secured by real estate	2,592		(108)		—		(302)		2,182
Business loans secured by real estate
CRE owner-occupied	32,340		(2,370)		40		(1,223)		28,787
Franchise real estate secured	7,019		—		—		480		7,499
SBA secured by real estate	4,348		—		248		(169)		4,427
Commercial loans
Commercial and industrial	35,169		(10,474)		1,041		10,956		36,692
Franchise non-real estate secured	16,029		—		150		(1,048)		15,131
SBA non-real estate secured	441		(67)		71		13		458
Retail loans
Single family residential	352		(90)		1		242		505
Consumer loans	221		(896)		35		774		134
Totals	$	195,651	$	(19,349)	$	1,746	$	14,423	$	192,471


	For the Year Ended December 31, 2022
(Dollars in thousands)	Beginning ACL Balance		Charge-offs		Recoveries		Provision for Credit Losses		Ending ACL Balance
Investor loans secured by real estate
CRE non-owner-occupied	$	37,380	$	(4,760)	$	—	$	1,072	$	33,692
Multifamily	55,209		—		—		1,125		56,334
Construction and land	5,211		—		—		1,903		7,114
SBA secured by real estate	3,201		(70)		—		(539)		2,592
Business loans secured by real estate
CRE owner-occupied	29,575		—		56		2,709		32,340
Franchise real estate secured	7,985		—		—		(966)		7,019
SBA secured by real estate	4,866		—		—		(518)		4,348
Commercial loans
Commercial and industrial	38,136		(8,387)		2,904		2,516		35,169
Franchise non-real estate secured	15,084		(448)		—		1,393		16,029
SBA non-real estate secured	565		(50)		51		(125)		441
Retail loans
Single family residential	255		—		148		(51)		352
Consumer loans	285		(4)		—		(60)		221
Totals	$	197,752	$	(13,719)	$	3,159	$	8,459	$	195,651

The decrease in the ACL for loans held for investment during 2024 of $14.3 million was reflective of $20.4 million in net charge-offs, partially offset by $6.2 million in provision for credit losses. During 2024, the provision for credit losses was driven in large part by loans within the investor and business loans secured by real estate and retail loans segments, partially offset by a reversal of provision for credit losses within the commercial loans segment. The provisions for credit losses in the investor and business loans secured by real estate segments totaling $1.7 million and $6.8 million, respectively, were attributed to changes in economic forecasts, partially offset by a decrease in the balances of loans as well as improvements in asset quality in investor loans secured by real estate. Additionally, the decrease in the balance of construction and land loans, franchise real estate secured loans, and SBA real estate secured loans was the primary factor behind the reversal of provision for credit losses during 2024 for these loan classes. The provision for credit losses for the retail loans segment totaling $1.6 million was largely attributed to changes in economic forecasts as well as an increase in single family residential loans stemming from loan purchases in the fourth quarter of 2024. The reversal of provision for credit losses for commercial loans totaling $3.8 million was largely attributed to a decrease in the balance of loans throughout this segment, which was the primary driver behind the reversal of provision for credit losses in the franchise non-real estate secured and SBA non-real estate secured loan classes. The impact of lower loan balances within this segment was partially offset by changes in economic forecasts, which was the primary factor behind the provision for credit losses for C&I loans during 2024.

Charge-offs during 2024 were largely attributed to a $2.3 million charge-off on a CRE non-owner-occupied loan in the fourth quarter, a $1.2 million charge-off associated with the sale of a CRE owner-occupied loan in the third quarter, $11.5 million in charge-offs related to the sales of a substandard multifamily loan and a substandard CRE non-owner-occupied loan during the second quarter, and $5.7 million in charge-offs associated with the sales of various special mention and substandard CRE and franchise loans during the first quarter of 2024.

The decrease in the ACL for loans held for investment during 2023 of $3.2 million was reflective of $17.6 million in net charge-offs, partially offset by $14.4 million in provision for credit losses. The provision for credit losses in 2023 was largely attributed to $9.9 million in provision expense for commercial loans, as well as $4.4 million in provision expense for investor loans secured by real estate. The provision expense for commercial loans was attributed to changes in economic forecasts, as well as unfavorable changes in asset quality for C&I loans within that segment, offset in part by decreases in loan balances across the segment. The provision expense for the investor loans secured by real estate segment was attributed to changes in economic forecasts on loans, partially offset by improvements in asset quality and the decreases in loan balances.