Trustmark’s ACL methodology for LHFI is based upon guidance within the Financial Accounting Standards Board (FASB) Accounting Standards Codification (ASC) Subtopic 326-20 as well as applicable regulatory guidance. The ACL is a valuation account that is deducted from the loans’ amortized cost basis to present the net amount expected to be collected on the loans. Credit quality within the LHFI portfolio is continuously monitored by Management and is reflected within the ACL for LHFI. The ACL is an estimate of expected losses inherent within Trustmark’s existing LHFI portfolio. The ACL for LHFI is adjusted through the PCL, LHFI and reduced by the charge off of loan amounts, net of recoveries.

The methodology for estimating the amount of expected credit losses reported in the ACL has two basic components: a collective, or pooled, component for estimated expected credit losses for pools of loans that share similar risk characteristics, and an asset-specific

component involving individual loans that do not share risk characteristics with other loans and the measurement of expected credit losses for such individual loans. In estimating the ACL for the collective component, loans are segregated into loan pools based on loan product types and similar risk characteristics.

The loans secured by real estate and other loans secured by real estate portfolio segments include loans for both commercial and residential properties. The underwriting process for these loans includes analysis of the financial position and strength of both the borrower and guarantor, experience with similar projects in the past, market demand and prospects for successful completion of the proposed project within the established budget and schedule, values of underlying collateral, availability of permanent financing, maximum loan-to-value ratios, minimum equity requirements, acceptable amortization periods and minimum debt service coverage requirements, based on property type. The borrower’s financial strength and capacity to repay their obligations remain the primary focus of underwriting. Financial strength is evaluated based upon analytical tools that consider historical and projected cash flows and performance in addition to analysis of the proposed project for income-producing properties. Additional support offered by guarantors is also considered. Ultimate repayment of these loans is sensitive to interest rate changes, general economic conditions, liquidity and availability of long-term financing.

The commercial and industrial LHFI portfolio segment includes loans within Trustmark’s geographic markets made to many types of businesses for various purposes, such as short-term working capital loans that are usually secured by accounts receivable and inventory and term financing for equipment and fixed asset purchases that are secured by those assets. Trustmark’s credit underwriting process for commercial and industrial loans includes analysis of historical and projected cash flows and performance, evaluation of financial strength of both borrowers and guarantors as reflected in current and detailed financial information and evaluation of underlying collateral to support the credit.

The consumer LHFI portfolio segment is comprised of loans that are centrally underwritten based on the borrower's credit bureau score as well as an evaluation of the borrower’s repayment capacity, credit, and collateral. Property appraisals are obtained to assist in evaluating collateral. Loan-to-value and debt-to-income ratios, loan amount, and lien position are also considered in assessing whether to originate a loan. These borrowers are particularly susceptible to downturns in economic trends such as conditions that negatively affect housing prices and demand and levels of unemployment.

The state and other political subdivision LHFI and the other commercial LHFI and leases portfolio segments primarily consist of loans to non-depository financial institutions, such as mortgage companies, finance companies and other financial intermediaries, loans to state and political subdivisions, and loans to non-profit and charitable organizations. These loans are underwritten based on the specific nature or purpose of the loan and underlying collateral with special consideration given to the specific source of repayment for the loan. The lease segment primarily consists of commercial equipment finance leases. Trustmark’s credit underwriting process for equipment finance leases includes analysis of historical and projected cash flows and performance, evaluation of financial strength of both borrowers and guarantors as reflected in current and detailed financial information and evaluation of underlying collateral to support the credit.

During the first quarter of 2024 as part of Trustmark's ongoing model monitoring procedures the annual loss driver analysis was performed. The analysis resulted in changes in the loss drivers for all discounted cash-flow models along with changes in the loss drivers for the equipment and finance loans and leases model. These changes were a result of updating Trustmark's peer group and incorporating data through 2022 which led to more intuitive loss drivers. All models were validated by a third party before implementation.

The following table provides a description of each of Trustmark’s portfolio segments, loan classes, loan pools and the ACL methodology and loss drivers at March 31, 2024:


Portfolio Segment	Loan Class	Loan Pool	Methodology	Loss Drivers
Loans secured by real estate	Construction, land development and other land	1-4 family residential construction	DCF	National HPI, National Unemployment
		Lots and development	DCF	National HPI, National Unemployment
		Unimproved land	DCF	National HPI, National Unemployment
		All other consumer	DCF	National HPI, National Unemployment
	Other secured by 1-4 family residential properties	Consumer 1-4 family - 1st liens	DCF	National HPI, National Unemployment
		All other consumer	DCF	National HPI, National Unemployment
		Nonresidential owner-occupied	DCF	Southern Unemployment, National CRE Price Index
	Secured by nonfarm, nonresidential properties	Nonowner-occupied - hotel/motel	DCF	National CRE Price Index, Southern Unemployment
		Nonowner-occupied - office	DCF	National CRE Price Index, Southern Unemployment
		Nonowner-occupied- Retail	DCF	National CRE Price Index, Southern Unemployment
		Nonowner-occupied - senior living/nursing homes	DCF	National CRE Price Index, Southern Unemployment
		Nonowner-occupied - all other	DCF	National CRE Price Index, Southern Unemployment
		Nonresidential owner-occupied	DCF	Southern Unemployment, National CRE Price Index
	Other real estate secured	Nonresidential nonowner -occupied - apartments	DCF	National CRE Price Index, Southern Unemployment
		Nonresidential owner-occupied	DCF	Southern Unemployment, National CRE Price Index
		Nonowner-occupied - all other	DCF	National CRE Price Index, Southern Unemployment
Other loans secured by real estate	Other construction	Other construction	DCF	National CRE Price Index, National Unemployment, BBB 7-10 US CBI
	Secured by 1-4 family residential properties	Trustmark mortgage	WARM	Southern Unemployment


Portfolio Segment	Loan Class	Loan Pool	Methodology	Loss Drivers
Commercial and industrial loans	Commercial and industrial loans	Commercial and industrial - non-working capital	DCF	Trustmark historical data
		Commercial and industrial - working capital	DCF	Trustmark historical data
		Equipment finance loans	WARM	Southern Unemployment, National GDP
		Credit cards	WARM	Trustmark call report data
Consumer loans	Consumer loans	Credit cards	WARM	Trustmark call report data
		Overdrafts	Loss Rate	Trustmark historical data
		All other consumer	DCF	National HPI, National Unemployment
State and other political subdivision loans	State and other political subdivision loans	Obligations of state and political subdivisions	DCF	Moody's Bond Default Study
Other commercial loans and leases	Other commercial loans and leases	Other loans	DCF	BBB 7-10 US CBI, Southern Unemployment
		Commercial and industrial - non-working capital	DCF	Trustmark historical data
		Commercial and industrial - working capital	DCF	Trustmark historical data
		Equipment finance leases	WARM	Southern Unemployment, National GDP

The following table provides a description of each of Trustmark’s portfolio segments, loan classes, loan pools and the ACL methodology and loss drivers at December 31, 2023:


Portfolio Segment	Loan Class	Loan Pool	Methodology	Loss Drivers
Loans secured by real estate	Construction, land development and other land	1-4 family residential construction	DCF	Prime Rate, National GDP
		Lots and development	DCF	Prime Rate, Southern Unemployment
		Unimproved land	DCF	Prime Rate, Southern Unemployment
		All other consumer	DCF	Southern Unemployment
	Other secured by 1-4 family residential properties	Consumer 1-4 family - 1st liens	DCF	Prime Rate, Southern Unemployment
		All other consumer	DCF	Southern Unemployment
		Nonresidential owner-occupied	DCF	Southern Unemployment, National GDP
	Secured by nonfarm, nonresidential properties	Nonowner-occupied - hotel/motel	DCF	Southern Vacancy Rate, Southern Unemployment
		Nonowner-occupied - office	DCF	Southern Vacancy Rate, Southern Unemployment
		Nonowner-occupied- Retail	DCF	Southern Vacancy Rate, Southern Unemployment
		Nonowner-occupied - senior living/nursing homes	DCF	Southern Vacancy Rate, Southern Unemployment
		Nonowner-occupied - all other	DCF	Southern Vacancy Rate, Southern Unemployment
		Nonresidential owner-occupied	DCF	Southern Unemployment, National GDP
	Other real estate secured	Nonresidential nonowner -occupied - apartments	DCF	Southern Vacancy Rate, Southern Unemployment
		Nonresidential owner-occupied	DCF	Southern Unemployment, National GDP
		Nonowner-occupied - all other	DCF	Southern Vacancy Rate, Southern Unemployment
Other loans secured by real estate	Other construction	Other construction	DCF	Prime Rate, National Unemployment
	Secured by 1-4 family residential properties	Trustmark mortgage	WARM	Southern Unemployment
Commercial and industrial loans	Commercial and industrial loans	Commercial and industrial - non-working capital	DCF	Trustmark historical data
		Commercial and industrial - working capital	DCF	Trustmark historical data
		Equipment finance loans	WARM	Southern Unemployment, Southern GDP
		Credit cards	WARM	Trustmark call report data
Consumer loans	Consumer loans	Credit cards	WARM	Trustmark call report data
		Overdrafts	Loss Rate	Trustmark historical data
		All other consumer	DCF	Southern Unemployment
State and other political subdivision loans	State and other political subdivision loans	Obligations of state and political subdivisions	DCF	Moody's Bond Default Study
Other commercial loans and leases	Other commercial loans and leases	Other loans	DCF	Prime Rate, Southern Unemployment
		Commercial and industrial - non-working capital	DCF	Trustmark historical data
		Commercial and industrial - working capital	DCF	Trustmark historical data
		Equipment finance leases	WARM	Southern Unemployment, Southern GDP

In general, Trustmark utilizes a DCF method to estimate the quantitative portion of the ACL for loan pools. The DCF model consists of two key components, a loss driver analysis (LDA) and a cash flow analysis. For loan pools utilizing the DCF methodology, multiple assumptions are in place, depending on the loan pool. A reasonable and supportable forecast is utilized for each loan pool by developing a LDA for each loan class. The LDA uses charge off data from Federal Financial Institutions Examination Council (FFIEC) reports to construct a periodic default rate (PDR). The PDR is decomposed into a PD. Regressions are run using the data for various macroeconomic variables in order to determine which ones correlate to Trustmark’s losses. These variables are then incorporated into the application to calculate a quarterly PD using a third-party baseline forecast. In addition to the PD, a LGD is derived using a method referred to as Frye Jacobs. The Frye Jacobs method is a mathematical formula that traces the relationship between LGD and PD over time and projects the LGD based on the levels of PD forecasts. This model approach is applicable to all pools within the construction, land development and other land, other secured by 1-4 family residential properties, secured by nonfarm, nonresidential properties and other real estate secured loan classes as well as consumer loans and other commercial loans.

During 2022, Management elected to incorporate a methodology change related to the other construction pool. Components of this change include management utilizing an alternative LDA to support the PD and LGD assumptions necessary to apply a DCF methodology to the other construction pool. Fundamentally, this approach utilizes publicly reported default balances and leverages a generalized linear model (GLM) framework to estimate PD. Taken together, these differences allow for results to be scaled to be specific and directly applicable to the other construction segment. LGD is assumed to be a through-the-cycle constant based on the actual performance of Trustmark’s other construction segment. These assumptions are then input into the DCF model and used in conjunction with prepayment data to calculate the cash flows at the individual loan level. Previously, the other construction pool used the weighted average remaining maturity (WARM) method. Management believes this change is commensurate with the level of risk in the pool.

For the commercial and industrial loans related pools, Trustmark uses its own PD and LGD data, instead of the macroeconomic variables and the Frye Jacobs method described above, to calculate the PD and LGD as there were no defensible macroeconomic variables that correlated to Trustmark’s losses. Trustmark utilizes a third-party Bond Default Study to derive the PD and LGD for the obligations of state and political subdivisions pool. Due to the lack of losses within this pool, no defensible macroeconomic factors were identified to correlate.

The PD and LGD measures are used in conjunction with prepayment data as inputs into the DCF model to calculate the cash flows at the individual loan level. Contractual cash flows based on loan terms are adjusted for PD, LGD and prepayments to derive loss cash flows. These loss cash flows are discounted by the loan’s coupon rate to arrive at the discounted cash flow based quantitative loss. The prepayment studies are updated quarterly by a third-party for each applicable pool.

An alternate method of estimating the ACL is used for certain loan pools due to specific characteristics of these loans. For the non-DCF pools, specifically, those using the WARM method, the remaining life is incorporated into the ACL quantitative calculation.

Trustmark determined that reasonable and supportable forecasts could be made for a twelve-month period for all of its loan pools. To the extent the lives of the loans in the LHFI portfolio extend beyond this forecast period, Trustmark uses a reversion period of four quarters and reverts to the historical mean on a straight-line basis over the remaining life of the loans. The econometric models currently in production reflect segment or pool level sensitivities of PD to changes in macroeconomic variables. By measuring the relationship between defaults and changes in the economy, the quantitative reserve incorporates reasonable and supportable forecasts of future conditions that will affect the value of Trustmark’s assets, as required by FASB ASC Topic 326. Under stable forecasts, these linear regressions will reasonably predict a pool’s PD. However, due to the COVID-19 pandemic, the macroeconomic variables used for reasonable and supportable forecasting changed rapidly. At the macroeconomic levels experienced during the COVID-19 pandemic, it was not clear that the models in production would produce reasonably representative results since the models were originally estimated using data beginning in 2004 through 2019. During this period, a traditional, albeit severe, economic recession occurred. Thus, econometric models are sensitive to similar future levels of PD.

In order to prevent the econometric models from extrapolating beyond reasonable boundaries of their input variables, Trustmark chose to establish an upper and lower limit process when applying the periodic forecasts. In this way, Management will not rely upon unobserved and untested relationships in the setting of the quantitative reserve. This approach applies to all input variables, including: Southern Unemployment, National Unemployment, National Gross Domestic Product (GDP), National Home Price Index (HPI), National Commercial Real Estate (CRE) Price Index and the BBB 7-10 Year US Corporate Bond Index (CBI). The upper and lower limits are based on the distribution of the macroeconomic variable by selecting extreme percentiles at the upper and lower limits of the distribution, the 1stand 99th percentiles, respectively. These upper and lower limits are then used to calculate the PD for the forecast time period in which the forecasted values are outside of the upper and lower limit range. Due to multiple periods having a PD or LGD at or near zero as a result of the improving macroeconomic forecasts, Management implemented PD and LGD floors to account for the risk associated with each portfolio. The PD and LGD floors are based on Trustmark’s historical loss experience and applied at a portfolio level.

While all these factors are incorporated into the overall methodology, only three are currently considered active at March 31, 2024: (i) economic conditions and concentrations of credit, (ii) nature and volume of the portfolio and (iii) performance trends.

Two of Trustmark’s largest loan classes are the loans secured by nonfarm, nonresidential properties and the loans secured by other real estate. Trustmark elected to create a qualitative factor specifically for these loan classes which addresses changes in the economic conditions of metropolitan areas and applies additional pool level reserves. This qualitative factor is based on third-party market data and forecast trends and is updated quarterly as information is available, by market and by loan pool.

Trustmark's current quantitative methodologies do not completely incorporate changes in credit quality. As a result, Trustmark utilizes the performance trends qualitative factor. This factor is based on migration analyses, that allocates additional ACL to non-pass/delinquent loans within each pool. In this way, Management believes the ACL will directly reflect changes in risk, based on the performance of the loans within a pool, whether declining or improving.

The performance trends qualitative factor is estimated by properly segmenting loan pools into risk levels by risk rating for commercial credits and delinquency status for consumer credits. A migration analysis is then performed quarterly using a third-party software and the results for each risk level are compiled to calculate the historical PD average for each loan portfolio based on risk levels. This average historical PD rate is updated annually. For the mortgage portfolio, Trustmark uses an internal report to incorporate a roll rate method for the calculation of the PD rate. In addition to the PD rate for each portfolio, Management incorporates the quantitative rate and the k value derived from the Frye-Jacobs method to calculate a loss estimate that includes both PD and LGD. The quantitative rate is used to eliminate any additional reserve that the quantitative reserve already includes. Finally, the loss estimate rate is then applied to the total balances for each risk level for each portfolio to calculate a qualitative reserve.

During 2022, Management elected to activate the nature and volume of the portfolio qualitative factor as a result of a sub-pool of the secured by 1-4 family residential properties growing to a significant size along with the underlying nature being different as well. The nature and volume of the portfolio qualitative factor utilizes a WARM methodology that uses industry data for the assumptions to support the qualitative adjustment. The industry data is used to compile a PD based on credit score ranges along with using the industry data to compile an LGD. The sub-pool of credits is then aggregated into the appropriate credit score bands in which a weighted average loss rate is calculated based on the PD and LGD for each credit score range. This weighted average loss rate is then applied to the expected balance for the sub-segment of credits. This total is then used as the qualitative reserve adjustment.

The external factors qualitative factor is Management’s best judgment on the loan or pool level impact of all factors that affect the portfolio that are not accounted for using any other part of the ACL methodology (e.g., natural disasters, changes in legislation, impacts due to technology and pandemics). Trustmark's External Factor – Pandemic ensures reserve adequacy for collectively evaluated loans most likely to be impacted by the unique economic and behavioral conditions created by the COVID-19 pandemic. Additional qualitative reserves are derived based on two principles. The first is the disconnect of economic factors to Trustmark’s modeled PD (derived from the econometric models underpinning the quantitative pooled reserves). During the pandemic, extraordinary measures by the federal government were made available to consumers and businesses, including COVID-19 loan payment concessions, direct transfer payments to households, tax deferrals, and reduced interest rates, among others. These government interventions may have extended the lag between economic conditions and default, relative to what was captured in the model development data. Because Trustmark’s econometric PD models rely on the observed relationship from the economic downturn from 2007 to 2009 in both timing and severity, Management did not expect the models to reflect these conditions. For example, while the models would predict contemporaneous unemployment peaks and loan defaults, this might not have occurred when borrowers could request payment deferrals. Thus, for the affected population, economic conditions were not fully considered as a part of Trustmark’s quantitative reserve. The second principle is the change in risk that is identified by rating changes. As a part of Trustmark’s credit review process, loans in the affected population were given more frequent screening to ensure accurate ratings were maintained through this dynamic period. Trustmark’s quantitative reserve did not directly address changes in ratings, thus a migration qualitative factor was designed to work in concert with the quantitative reserve.

As discussed above, the disconnect of economic factors means that changes in rating caused by deteriorating and weak economic conditions as a result of the pandemic were not being captured in the quantitative reserve. During 2020, due to unforeseen pandemic conditions that varied from Management’s expectations, additional reserves were further dimensioned in order to appropriately reflect the risk within the portfolio related to the COVID-19 pandemic. In an effort to ensure the External Factor-Pandemic qualitative factor was reasonable and supportable, historical Trustmark loss data was leveraged to construct a framework that was quantitative in nature. To dimension the additional reserve, Management used the sensitivity of the quantitative commercial loan reserve to changes in macroeconomic conditions to apply to loans rated acceptable or better (RR 1-4). In addition, to account for the known changes in risk, a weighted average of the commercial loan portfolio loss rate, derived from the performance trends qualitative factor, was used to dimension additional reserves for downgraded credits. Loans rated acceptable with risk (RR 5) or watch (RR 6) received the additional reserves based on the average of the macroeconomic conditions and weighted-average of the commercial loan portfolio loss rate while the loans rated special mention (RR 7) and substandard (RR 8) received additional reserves based on the weighted-average described above. During 2022, Management noted that all pass rated loans (RR 5 & RR 6) related to the External Factor-Pandemic qualitative factor either did not experience significant stress related to the pandemic or had since recovered and did not expect future stresses attributed to the pandemic that could affect these loans. As a result, Management decided to accelerate the release of the additional pandemic reserves on all pass rated loans as a result of pandemic conditions resolving. During the fourth quarter of 2023, Management decided to resolve the External Factor-Pandemic qualitative factor as a result of the remaining loan balances that were identified as COVID affected loans being immaterial from both a reserve and balance perspective. The remaining loans were incorporated back into the performance qualitative factor as a result of this resolution. Further, due to this resolution there is no longer any active External Factor as of December 31, 2023.