Company: MCHB
Filing Date: 2025-07-03
Form Type: S-4
Source: 0001140361-25-024872
Chunk: 345

Company: Mechanics Bancorp
Filing Date: 2025-07-03
Form: S-4
Chunk 345
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 data are credit model specific. Prepayments are estimated by loan type using historical information and adjusted for current and future conditions.

When computing allowance levels, credit loss assumptions are estimated using models that analyze loans according to credit risk ratings, historic loss experience, past due status and other credit trends and risk characteristics, including current conditions and reasonable and supportable forecasts about the future. Determining the appropriateness of the allowance is complex and requires judgment by management about the effect of matters that are inherently uncertain. Future factors and forecasts may result in significant changes in the allowance and provision (reversal) for credit losses in those future periods. The allowance for credit losses will primarily reflect estimated losses for pools of loans that share similar risk characteristics but will also consider individual loans that do not share risk characteristics with other loans.

#### Collectively Evaluated Loans
In estimating the allowance for credit losses for collectively evaluated loans, segments are derived based on loans pooled by product types and similar risk characteristics or areas of risk concentration. In determining the allowance for credit losses, the Bank utilizes models for loss forecasting for the majority of MB’s portfolio. These models ensure that we employ sophisticated methodologies and industry-leading analytics to inform our credit loss estimations accurately. Economic forecasts are a crucial component of our estimation process, applied over a period deemed reasonable and supportable by management. These forecasts, alongside historical data, credit model-specific reversion assumptions and management judgment, inform our credit loss assumptions. The following models are utilized for the Bank’s portfolios:

Auto Loans . The Bank uses models which incorporate macroeconomic forecasts and loan level models for estimating probabilities of default and prepayment. While the Bank has access to national data, we use a custom model based on MB internal historical data applying them to a blend of forecasted scenarios. Based on the portfolio’s composition of loans and their respective credit characteristics and delinquencies, a cash flow schedule of losses is produced providing the expected loss rate for the segment. Model outputs are then back-tested on an ongoing basis to determine adequacy and accuracy on a quarterly basis.

Commercial Real Estate – Non-Owner Occupied CRE and Multifamily Loans. The Bank uses models specific to Non-Owner Occupied CRE and Multifamily loans. The model addresses traditional commercial real estate products dependent on cash flow generated from rents. Based on property information (DSC, LTV, Geography, Property Type), the model generates a PD and LGD at the individual loan level over the life of the loan, producing an expected loss rate for each instrument across all future periods. Collect