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Receivables, Loans, Notes Receivable, and Others (Policies) | 12 Months Ended
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Dec. 31, 2024
Receivables [Abstract] |
Financing Receivable, Excluding Accrued Interest, Allowance For Credit Losses Policy For Uncollectible Amounts | Allowance for Credit Losses - Loans. The allowance for credit losses on loans is a contra-asset valuation account, calculated in accordance with ASC 326, that is deducted from the amortized cost basis of loans to present management's best estimate of the net amount expected to be collected. Loans are charged-off against the allowance when deemed uncollectible by management. Expected recoveries do not exceed the aggregate of amounts previously charged-off and expected to be charged-off. Adjustments to the allowance are reported in our income statement as a component of credit loss expense. Management has made the accounting policy election to exclude accrued interest receivable on loans from the estimate of credit losses. Further information regarding our policies and methodology used to estimate the allowance for credit losses on loans is presented in Note 3 - Loans. Allowance For Credit Losses - Loans. The allowance for credit losses on loans is a contra-asset valuation account, calculated in accordance with ASC 326, that is deducted from the amortized cost basis of loans to present the net amount expected to be collected. The amount of the allowance represents management's best estimate of current expected credit losses on loans considering available information, from internal and external sources, relevant to assessing collectibility over the loans' contractual terms, adjusted for expected prepayments when appropriate. The contractual term excludes expected extensions, renewals and modifications unless (i) management has a reasonable expectation that a loan to an individual borrower that is experiencing financial difficulty will be modified or (ii) such extension or renewal options are not unconditionally cancellable by us and, in such cases, the borrower is likely to meet applicable conditions and likely to request extension or renewal. Relevant available information includes historical credit loss experience; current conditions; and reasonable and supportable forecasts. While historical credit loss experience provides the basis for the estimation of expected credit losses, adjustments to historical loss information may be made for differences in current portfolio-specific risk characteristics, environmental conditions, or other relevant factors. The allowance for credit losses is measured on a collective basis for portfolios of loans when similar risk characteristics exist. Loans that do not share risk characteristics are evaluated for expected credit losses on an individual basis and excluded from the collective evaluation. Expected credit losses for collateral dependent loans, including loans where the borrower is experiencing financial difficulty but foreclosure is not probable, are based on the fair value of the collateral at the reporting date, adjusted for selling costs as appropriate. Credit loss expense related to loans reflects the totality of actions taken on all loans for a particular period including any necessary increases or decreases in the allowance related to changes in credit loss expectations associated with specific loans or pools of loans. Portions of the allowance may be allocated for specific credits; however, the entire allowance is available for any credit that, in management’s judgment, should be charged off. While management utilizes its best judgment and information available, the ultimate appropriateness of the allowance is dependent upon a variety of factors beyond our control, including the performance of our loan portfolio, the economy, changes in interest rates and the view of the regulatory authorities toward loan classifications. In calculating the allowance for credit losses, most loans are segmented into pools based upon similar characteristics and risk profiles. Common characteristics and risk profiles include the type/purpose of loan, underlying collateral, geographical similarity, and historical/expected credit loss patterns. In developing these loan pools for the purposes of modeling expected credit losses, we also analyzed the degree of correlation in how loans within each portfolio respond when subjected to varying economic conditions and scenarios as well as other portfolio stress factors. For modeling purposes, our loan pools include (i) commercial and industrial non-revolving, (ii) commercial and industrial revolving, (iii) energy, (iv) commercial real estate - owner occupied, (v) commercial real estate - non-owner occupied, (vi) commercial real estate - construction/land development, (vii) consumer real estate and (viii) consumer and other. Prior to 2023, energy loans were included within the commercial and industrial loan pools. See discussion of the 2023 model updates below. We periodically reassess each pool to ensure the loans within the pool continue to share similar characteristics and risk profiles and to determine whether further segmentation is necessary. For each loan pool, we measure expected credit losses over the life of each loan utilizing a combination of models which measure (i) probability of default (“PD”), which is the likelihood that loan will stop performing/default, (ii) probability of attrition (“PA”), which is the likelihood that a loan will pay-off prior to maturity, (iii) loss given default (“LGD”), which is the expected loss rate for loans in default and (iv) exposure at default (“EAD”), which is the estimated outstanding principal balance of the loans upon default, including the expected funding of unfunded commitments outstanding as of the measurement date. For commercial loan portfolios, the PD is calculated using a transition matrix to determine the likelihood of a customer’s risk grade migrating from one specified range of risk grades to a different specified range. Expected credit losses are calculated as the product of PD (adjusted for attrition), LGD and EAD. This methodology builds on default probabilities already incorporated into our risk grading process by utilizing pool-specific historical loss rates to calculate expected credit losses. These pool-specific historical loss rates may be adjusted for current macroeconomic assumptions, as further discussed below, and other factors 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 as of the measurement date. Each time we measure expected credit losses, we assess the relevancy of historical loss information and consider any necessary adjustments to address any differences in asset-specific characteristics. Due to their short-term nature, expected credit losses for overdrafts included in consumer and other loans are based solely upon a weighting of recent historical charge-offs over a period of three years. The measurement of expected credit losses is impacted by loan/borrower attributes and certain macroeconomic variables. Significant loan/borrower attributes utilized in our modeling processes include, among other things, (i) origination date, (ii) maturity date, (iii) payment type, (iv) collateral type and amount, (v) current risk grade, (vi) current unpaid balance and commitment utilization rate, (vii) payment status/delinquency history and (viii) expected recoveries of previously charged-off amounts. Significant macroeconomic variables utilized in our modeling processes include, among other things, (i) Gross State Product for Texas and U.S. Gross Domestic Product, (ii) selected market interest rates including U.S. Treasury rates, bank prime rate, 30-year fixed mortgage rate, BBB corporate bond rate, among others, (iii) unemployment rates, (iv) commercial and residential property prices in Texas and the U.S. as a whole, (v) West Texas Intermediate crude oil price and (vi) total stock market index. PD and PA were estimated by analyzing internally-sourced data related to historical performance of each loan pool over a complete economic cycle. PD and PA are adjusted to reflect the current impact of certain macroeconomic variables as well as their expected changes over a reasonable and supportable forecast period. We have determined that we are reasonably able to forecast the macroeconomic variables used in our modeling processes with an acceptable degree of confidence for a total of two years with the last twelve months of the forecast period encompassing a reversion process whereby the forecasted macroeconomic variables are reverted to their historical mean utilizing a rational, systematic basis. The macroeconomic variables utilized as inputs in our modeling processes were subjected to a variety of analysis procedures and were selected primarily based on statistical relevancy and correlation to our historical credit losses. By reverting these modeling inputs to their historical mean and considering loan/borrower specific attributes, our models are intended to yield a measurement of expected credit losses that reflects our average historical loss rates for periods subsequent to the twelve-month reversion period. The LGD is based on historical recovery averages for each loan pool, adjusted to reflect the current impact of certain macroeconomic variables as well as their expected changes over a two-year forecast period, with the final twelve months of the forecast period encompassing a reversion process, which management considers to be both reasonable and supportable. This same forecast/reversion period is used for all macroeconomic variables used in all of our models. EAD is estimated using a linear regression model that estimates the average percentage of the loan balance that remains at the time of a default event. Management qualitatively adjusts model results for risk factors that are not considered within our modeling processes but are nonetheless relevant in assessing the expected credit losses within our loan pools. These qualitative factor (“Q-Factor”) and other qualitative adjustments may increase or decrease management's estimate of expected credit losses by a calculated percentage or amount based upon the estimated level of risk. The various risks that may be considered in making Q-Factor and other qualitative adjustments include, among other things, the impact of (i) changes in lending policies and procedures, including changes in underwriting standards and practices for collections, write-offs, and recoveries, (ii) actual and expected changes in international, national, regional, and local economic and business conditions and developments that affect the collectibility of the loan pools, (iii) changes in the nature and volume of the loan pools and in the terms of the underlying loans, (iv) changes in the experience, ability, and depth of our lending management and staff, (v) changes in volume and severity of past due financial assets, the volume of non-accrual assets, and the volume and severity of adversely classified or graded assets, (vi) changes in the quality of our credit review function, (vii) changes in the value of the underlying collateral for loans that are non-collateral dependent, (viii) the existence, growth, and effect of any concentrations of credit and (ix) other factors such as the regulatory, legal and technological environments; competition; and events such as natural disasters or health pandemics. In some cases, management may determine that an individual loan exhibits unique risk characteristics which differentiate the loan from other loans within our loan pools. In such cases, the loans are evaluated for expected credit losses on an individual basis and excluded from the collective evaluation. Specific allocations of the allowance for credit losses are determined by analyzing the borrower’s ability to repay amounts owed, collateral deficiencies, the relative risk grade of the loan and economic conditions affecting the borrower’s industry, among other things. A loan is considered to be collateral dependent when, based upon management's assessment, the borrower is experiencing financial difficulty and repayment is expected to be provided substantially through the operation or sale of the collateral. In such cases, expected credit losses are based on the fair value of the collateral at the measurement date, adjusted for estimated selling costs if satisfaction of the loan depends on the sale of the collateral. We reevaluate the fair value of collateral supporting collateral dependent loans on a quarterly basis. The fair value of real estate collateral supporting collateral dependent loans is evaluated by our internal appraisal services using a methodology that is consistent with the Uniform Standards of Professional Appraisal Practice. The fair value of collateral supporting collateral dependent construction loans is based on an “as is” valuation. During the first quarter of 2024, we updated our non-owner-occupied commercial real estate loan models as well as our consumer and other loan models. Our prior non-owner-occupied commercial real estate loan models were legacy models developed for stress-testing purposes by a third-party using external market data. The updated non-owner-occupied commercial real estate loan models are now based on internal historical loan data and risk grade information and the modeling processes are now consistent with those used with our other commercial loan models. Our prior consumer and other loan models relied upon certain components that did not use loan level attributes and were less sensitive to macroeconomic variables. The updated consumer and other loan models are now based on internal historical loan data and utilize more loan-level attributes and the modeling processes are now consistent with those used with our consumer real estate loan models. The overall approximate impact of the model updates during the first quarter was a $7.2 million increase ($6.2 million related to non-owner-occupied commercial real estate loans and $923 thousand related to consumer and other loans) in modeled expected credit losses on loans; however, the impact of this increase was largely offset by reductions in qualitative adjustments as some of the risks to which those qualitative adjustments related are now considered and incorporated in the updated models. During the first quarter of 2023, we recalibrated and updated all of our commercial loan models, with the exception of the models related to commercial real estate - non-owner-occupied loans, as well as our consumer real estate loan models. While the fundamental modeling methodologies remain unchanged, the updates included (i) separating the energy loan pool from the commercial and industrial pool as a result of differences in loss characteristics observed in recent history and (ii) changing the modeling approach related to loan renewals whereby each renewal is treated as a separate loan which impacted loan life assumptions. The overall approximate impact of the model updates during the first quarter was a $45.0 million decrease in modeled expected credit losses on loans though the impact of this decrease was largely offset with discretionary qualitative adjustments. The decrease in modeled expected credit losses on loans was largely driven by lower measurements for PD and LGD based on the historical data series (2008 through 2018) used for the recalibration. This period was one of relatively low losses and included higher levels of government stimulus. The lower PD and LGD measurements were also impacted by shorter loan life assumptions due to the aforementioned change in the modeling approach related to loan renewals. Generally, a commercial loan, or a portion thereof, is charged-off immediately when it is determined, through the analysis of any available current financial information with regards to the borrower, that the borrower is incapable of servicing unsecured debt, there is little or no prospect for near term improvement and no realistic strengthening action of significance is pending or, in the case of secured debt, when it is determined, through analysis of current information with regards to our collateral position, that amounts due from the borrower are in excess of the calculated current fair value of the collateral. Notwithstanding the foregoing, generally, commercial loans that become past due 180 cumulative days are charged-off. Generally, a consumer loan, or a portion thereof, is charged-off in accordance with regulatory guidelines which provide that such loans be charged-off when we become aware of the loss, such as from a triggering event that may include new information about a borrower’s intent/ability to repay the loan, bankruptcy, fraud or death, among other things, but in any event the charge-off must be taken within specified delinquency time frames. Such delinquency time frames state that closed-end retail loans (loans with pre-defined maturity dates, such as real estate mortgages, home equity loans and consumer installment loans) that become past due 120 cumulative days and open-end retail loans (loans that roll-over at the end of each term, such as home equity lines of credit) that become past due 180 cumulative days should be classified as a loss and charged-off.

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