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Common challenges with impairment analysis

March 20, 2014
Read Time: 0 min

In a recent webinar, Garrett Morris, senior credit and risk management consultant at Sageworks, discussed common challenges with loan impairment. 

From the video:

Let’s look at the general challenges faced when determining impairment. Examining those common challenges with impairment, we find there are quite a few. 

First, using present value of future cash flows can be a somewhat subjective method when determining a valuation for FAS 114 impairment loans

Additionally, examiners are wary of excessive optimism. Under the present value of future cash flows there should be documentation of the expected amount and timing of payments, use of the effective interest rate to discount cash flows (incorporating the original contractual interest rate in the loan agreement) and then of course documentation of the basis for the determination of our cash flow assessment. 

In addition to that, other factors that might make this calculation difficult include trends within the borrower’s industry, relevant political and economic changes, incorporating seasonality, correctly calculating balloon payments when needed and if the loan becomes collateral dependent resulting in a change of the valuation method itself. That is, moving to a collateral valuation for impairment, off of future value of cash flows. 

Now this goes back to an earlier conversation, where we state that the most common challenge is which valuation method should be utilized in accordance with guidance. And of course lastly, really documenting and defending that given approach. 

For more resources on the allowance for loan and lease losses, join the ALLL Forum for Bankers on LinkedIn or browse the Sageworks ALLL resources.

About the Author


Raleigh, N.C.-based Sageworks, a leading provider of lending, credit risk, and portfolio risk software that enables banks and credit unions to efficiently grow and improve the borrower experience, was founded in 1998. Using its platform, Sageworks analyzed over 11.5 million loans, aggregated the corresponding loan data, and created the largest

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