The loan portfolio is classified based on the underlying collateral utilized to secure each loan for financial reporting purposes. This classification is consistent with the Quarterly Report of Condition and Income filed by ServisFirst Bank with the Federal Deposit Insurance Corporation (“FDIC”).

Commercial, financial and agricultural - Includes loans to business enterprises issued for commercial, industrial, agricultural production and/or other professional purposes. These loans are generally secured by equipment, inventory, and accounts receivable of the borrower and repayment is primarily dependent on business cash flows.

Real estate – construction – Includes loans secured by real estate to finance land development or the construction of industrial, commercial or residential buildings. Repayment is dependent upon the completion and eventual sale, refinance or operation of the related real estate project.

Owner-occupied commercial real estate mortgage – Includes loans secured by nonresidential properties for which the primary source of repayment is the cash flow from the ongoing operations conducted by the party that owns the property.

1-4 family real estate mortgage – Includes loans secured by residential properties, including home equity lines of credit. Repayment is primarily dependent on the personal cash flow of the borrower.

Non-owner occupied commercial real estate mortgage – Includes loans secured by nonowner-occupied properties, including office buildings, industrial buildings, warehouses, retail buildings, and multifamily residential properties. Repayment is primarily dependent on income generated from the underlying collateral.

Consumer – Includes loans to individuals not secured by real estate. Repayment is dependent upon the personal cash flow of the borrower.

The composition of loans at December 31, 2024 and 2023 is summarized as follows:

Changes in the ACL during the years ended December 31, 2024, 2023 and 2022 are as follows:

GAAP requires a current expected credit losses (“CECL”) methodology for estimating all expected losses over the life of a financial asset. Under the CECL methodology, the ACL is measured on a collective basis for pools of loans with similar risk characteristics. For loans that do not share similar risk characteristics with the collectively evaluated pools, evaluations are performed on an individual basis. For all loan segments collectively evaluated, losses are predicted over a period of time determined to be reasonable and supportable, and at the end of the reasonable and supportable forecast period losses are reverted to long-term historical averages. The estimated loan losses for all loan segments are adjusted for changes in qualitative factors not inherently considered in the quantitative analyses.

The Company uses the DCF method to estimate ACL for all loan pools except for commercial and industrial (“C&I”) revolving lines of credit and credit cards. For all loan pools utilizing the DCF method, the Company utilizes and forecasts national unemployment rate as a loss driver. The Company also utilizes and forecasts gross domestic product (“GDP”) growth as a second loss driver for its agricultural and consumer loan pools. Consistent forecasts of the loss drivers are used across the loan segments. At December 31, 2024 and 2023, the Company utilized a reasonable and supportable forecast period of twelve months followed by a six-month straight-line reversion to long-term averages. The Company leveraged economic projections from reputable and independent sources to inform its loss driver forecasts. At December 31, 2024, the Company expects the national unemployment rate to rise during the forecast period with a declining national GDP growth rate, with both economic indicators showing improvement when compared to the forecast at December 31, 2023.

The Company uses a loss-rate method to estimate expected credit losses for its C&I revolving lines of credit and a remaining life methodology on credit card pools. The C&I revolving lines of credit pool incorporates a probability of default (“PD”) and loss given default (“LGD”) modeling approach. This approach involves estimating the pool average life and then using historical correlations of default and loss experience over time to calculate the lifetime PD and LGD. These two inputs are then applied to the outstanding pool balance. The credit card pool incorporates a remaining life modeling approach, which utilizes an attrition-based method to estimate the remaining life of the pool. A quarterly average loss rate is then calculated using the Company’s historical loss data. The model reduces the pool balance quarterly on a straight-line basis over the estimated life of the pool. The quarterly loss rate is multiplied by the outstanding balance at each period-end resulting in an estimated loss for each quarter. The sum of estimated loss for all quarters is the total calculated reserve for the pool. Management has applied the loss-rate method to C&I lines of credit and to credit cards due to their generally short-term nature. An expected loss ratio is applied based on internal and peer historical losses.

Each loan pool is adjusted for qualitative factors not inherently considered in the quantitative analyses. The qualitative adjustments either increase or decrease the quantitative model estimation. The Company considers factors that are relevant within the qualitative framework, which include the following: lending policy, changes in nature and volume of loans, staff experience, changes in volume and trends of problem loans, concentration risk, trends in underlying collateral values, external factors, quality of loan review system and other economic conditions.

Inherent risks in the loan portfolio will differ based on type of loan. Specific risk characteristics by loan portfolio segment are listed below:

Commercial and industrial loans include risks associated with borrower’s cash flow, debt service coverage and management’s expertise. These loans are subject to the risk that the Company may have difficulty converting collateral to a liquid asset if necessary, as well as risks associated with degree of specialization, mobility and general collectability in a default situation. These commercial loans may be subject to many different types of risks, including fraud, bankruptcy, economic downturn, deteriorated or non-existent collateral, and changes in interest rates.

Real estate construction loans include risks associated with the borrower’s credit-worthiness, contractor’s qualifications, borrower and contractor performance, and the overall risk and complexity of the proposed project. Construction lending is also subject to risks associated with sub-market dynamics, including population, employment trends and household income. During times of economic stress, this type of loan has typically had a greater degree of risk than other loan types.

Real estate mortgage loans consist of loans secured by commercial and residential real estate. Commercial real estate lending is dependent upon successful management, marketing and expense supervision necessary to maintain the property. Repayment of these loans may be adversely affected by conditions in the real estate market or the general economy. Also, commercial real estate loans typically involve relatively large loan balances to a single borrower. Residential real estate lending risks are generally less significant than those of other loans. Real estate lending risks include fluctuations in the value of real estate, bankruptcies, economic downturn and customer financial problems.

Consumer loans carry a moderate degree of risk compared to other loans. They are generally more risky than traditional residential real estate loans but less risky than commercial loans. Risk of default is usually determined by the well-being of the local economies. During times of economic stress, there is usually some level of job loss both nationally and locally, which directly affects the ability of the consumer to repay debt.

Changes in the allowance for credit losses, segregated by loan type, during the years ended December 31, 2024 and 2023, respectively, are as follows:

Allocation of a part of the ACL to one loan type does not preclude its ability to absorb losses in other loan types. We maintain an ACL for credit losses on unfunded commercial lending commitments and letters of credit to provide for the risk of loss inherent in these arrangements. The allowance is computed using a methodology similar to that used to determine the ACL for loans, modified to take into account the probability of a drawdown on the commitment.  The ACL on unfunded loan commitments is classified as a liability account on the Consolidated Balance Sheets within other liabilities, while the corresponding provision for these credit losses is recorded as a component of other expense.  The allowance for credit losses on unfunded commitments was $608,000 and $575,000 at December 31, 2024 and 2023, respectively. The provision expense for unfunded commitments was $32,000 for the year ended December 31, 2024 and was $0 for the year ended December 31, 2023.

The credit quality of the loan portfolio is determined no less frequently than quarterly using categories similar to the standard asset classification system used by the federal banking agencies. The following table presents credit quality indicators for the loan loss portfolio segments and classes. These categories are utilized to develop the associated allowance for credit losses using historical losses adjusted for current economic conditions defined as follows:

The tables below presents loan balances classified by credit quality indicator, loan type and based on year of origination as of December 31, 2024 and 2023:

Nonperforming loans include nonaccrual loans and loans 90 or more days past due and still accruing. Loans by performance status as of December 31, 2024 and 2023 are as follows:

Loans by past due status as of December 31, 2024 and 2023 are as follows:

There was no interest earned on nonaccrual loans for the years ended December 31, 2024 and 2023.

Loans that no longer share similar risk characteristics with the collectively evaluated pools are estimated on an individual basis. A loan is considered collateral-dependent when the borrower is experiencing financial difficulty and repayment is expected to be provided substantially through the operation or sale of the collateral. The following table summarizes collateral-dependent gross loans held for investment by collateral type as follows:

The table below details the amortized cost basis at the end of the reporting period for loans made to borrowers experiencing financial difficulty that were modified during the years ended December 31, 2024 and 2023:

The following table summarizes the financial impacts of loan modifications made to borrowers experiencing financial difficulty during the year ended December 31, 2024: