How to calculate present value of future cash flows for a TDR

Sageworks
February 27, 2014
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In a recent webinar, Garrett Morris, senior credit and risk management consultant at Sageworks, discussed how to use present value of future cash flows for a TDR when calculating loan impairment.

From the video:

Present value of future cash flows should be used when there is an expectation of cash payment from the borrower, most often when dealing with troubled debt restructure (TDR) scenarios.

In a TDR, the loan structure payment schedule has been modified or restructured with the expectation that some portion of the principle will be repaid. A TDR should always be considered impaired, even when the valuation determines that no reserve is needed.

Furthermore, TDR occurs when an institution modifies the structure of a loan to benefit the borrower as a result of the borrower’s exhibited financial difficulties. This can include interest rate concessions, interest-only payments for a period of time before returning to full principle and interest payments and other similar concessions.

One very important item of interest is to make certain that when working with present value of future cash flows for TDR’s, we are using the original contractual interest rate, as that is a key item of interest since the loan has been restructured. Additionally, a month-to-month payment schedule for analysis should be utilized and documented, with flexibility to include balloon payments and other adjustments as needed.

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Lastly, as a common rule, a TDR should always be considered impaired.

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

Sageworks

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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