NOTE 5 – LOANS

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 non-owner 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 following table details the Company’s loans at March 31, 2025 and December 31, 2024:

The credit quality of the loan portfolio is summarized 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 credit 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 table below presents loan balances classified by credit quality indicator, loan type and based on year of origination as of March 31, 2025:

Loans by credit quality indicator, loan type and based on year of origination as of December 31, 2024 were as follows:

Loans by performance status as of March 31, 2025 and December 31, 2024 were as follows:

Loans by past due status as of March 31, 2025 and December 31, 2024 were as follows:

Under the current expected credit losses (“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 discounted cash flow (“DCF”) method to estimate ACL for all loan pools except for commercial 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 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 March 31, 2025 and December 31, 2024, 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. The Company expects national unemployment to rise and national GDP growth rate to decline compared to the December 31, 2024 forecast.

The Company uses a loss-rate method to estimate expected credit losses for its commercial revolving lines of credit and credit card pools. The commercial 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 also applied the loss-rate method to commercial and industrial (“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 downturns 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.

The following table presents changes in the ACL, segregated by loan type, for the three months ended March 31, 2025 and March 31, 2024.

We maintain an ACL on unfunded commercial lending commitments and letters of credit to provide for the risk of loss inherent in these arrangements. The ACL 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 provision for credit losses. The ACL on unfunded commitments was $768,000 at March 31, 2025 and $608,000 at December 31, 2024. The provision expense for unfunded commitments for the three months ended March 31, 2025 and 2024 was $160,000 and $167,000, respectively.

Loans that no longer share similar risk characteristics with 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 three months ended March 31, 2025 and 2024:

The following table summarizes the financial impacts of loan modifications made to borrowers experiencing financial difficulty during the three months ended March 31, 2025 and 2024:

No loans modified on or after March 31, 2024 were past due greater than 30 days or on non-accrual as of March 31, 2025.

As of March 31, 2025, the Company did not have any loans made to borrowers experiencing financial difficulty that were modified during the first quarter of 2025 that subsequently defaulted. For purposes of this disclosure, default is defined as 90 days past due and still accruing or placement on nonaccrual status. Beginning in the second quarter of 2024, the policy surrounding the definition of borrowers experiencing financial difficulty was refined.