Fair Value Determinations

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Fair Value Footnotes

We provide fair value estimates for financial instruments.

Why Choose Us

Our thorough understanding of credit risk derived from our asset liability management (ALM) and current expected credit losses (CECL) work combined with our knowledge of purchase accounting fair value determinations make us highly qualified to offer this service. Our input assumptions are based on the results from hundreds of engagements we have undertaken since the firm’s founding in 2003.

Effective in 2018, publicly traded financial institutions must disclose the fair value of their financial instruments at an “exit price.” This is a change from the entry price methodology typically used. Fair value estimates can be made in several different ways. One method is to discount the contractual cash flows using an all-in fair value discount rate. This is generally done through the financial institution’s ALM software or by its ALM provider. The result meets the requirements of the accounting standard but provides little insight regarding balance sheet risk management.

A second method is to estimate the cash flows expected to be collected, including prepayments and credit losses, and discount the result at a rate that excludes credit spread. We use the second method, and our estimates include the dollar amount of life-of-loan expected credit losses. Our credit loss estimates are made at the proper level of granularity in full accordance with the CECL model. As a result, we can easily produce Allowance for Credit Losses (ACL) loss estimates in full accordance with CECL by changing our discount rate from fair value to the note rate on the loan or investment.

Our Approach

We begin by obtaining the attributes of the loan portfolio at the loan level to determine contractual cash flows. Our next step is determining input assumptions for voluntary repayment, involuntary repayment, and loss severity to derive expected cash flows. To develop our input assumptions, we stratify the portfolio by loan attributes. For example, we separate first lien residential real estate loans from junior lien loans. We further divide the first liens into fixed and variable, and junior liens between closed and open-ended. For auto loans, we separate new from used, and further segment by direct and indirect. We do this because our modeling experience has shown that these loan types perform differently, even with similar credit indicators.

We then segment the loan categories by predictive credit indicators. For residential real estate loans, we use FICO and combined loan to value. For other consumer loans, we rely primarily on FICO. For commercial loans, we typically apply the credit assumptions by risk rating, debt service coverage, and NAICS code. We do this based on our analysis of the historical performance of billions of dollars of loans across the most recent 10-year business cycle.

For a given loan or loan cohort, we develop model input estimates for:

Voluntary prepayment – the conditional repayment rate (CRR)
Involuntary prepayment – the conditional default rate (CDR)
Loss severity if a default occurs

We adjust the contractual cash flows based on these input assumptions and discount the resulting cash flows back to the valuation date at fair value discount rate net of credit spread.

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Credit Union Merger Results Through 2023 [White Paper]

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