M&A Monday:* The Forgivable Promissory Note

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November 13, 2023

by a professional from Georgetown University in Maryland, USA

The Forgivable Promissory Note (FPN) is a powerful tool for buyers to offer higher offers with lower risk.

(1) How does an FPN work? FPN is a portion of the purchase price seller lends to buyer and is repaid over time. Often between 10%-20% of purchase price. The Note can be secured or personally guaranteed, but always subordinated. Interest rates vary, but I see 5%-10%. FPN can also be used for post-closing indemnification obligations or even working capital adjustments, allowing a buyer to reduce or remove an escrow at closing.

While I like to include FPN in most LOIs, the following situations lend naturally to FPN (note: often a similar goal can be achieved with an earnout or rollover):

  1. Seller wants to calculate a purchase price on pro forma financials.
  2. Fluctuations in the financials.
  3. Key customer uncertainties.
  4. Seller is key to post-closing transitions.

(2) What are the primary benefits for Buyer?

  1. Buyer can offer a higher purchase price.
  2. Remove an escrow and give seller more cash at closing.
  3. Reduce risk post-closing.
  4. Pay off part of the purchase price over time.
  5. Seller remains invested in the business post-closing (“skin in the game”).
  6. Buyer brings less cash to closing - higher leveraged IRR. An FPN is beneficial for seller because it increases the purchase price, moves consideration into another tax year, gets interest on the payments, and it can be more secure than an earnout.

(3) How is the forgiveness calculated? The goal of forgiveness calculation is to adjust the purchase price to reflect what it would have been had X occurred post-closing. Example: buyer is assuming a 4x multiple on $2m EBITDA and after closing, EBITDA declines to $1.8, $800k would be forgiven (of course, it is not usually dollar for dollar). The forgiveness mechanism needs to target the specific post-closing risk.

Forgiveness metrics are very situationally specific. Here are a few metrics:

  1. EBITDA. This is best for buyer, but sellers rarely agree. If sellers do agree, they usually ask for covenants requiring post-closing expenses to stay stable and the business has to operate per past practice.
  2. Revenue. It is more common that forgiveness is tied to revenue. A certain decline in revenue will trigger forgiveness of part of the note.
  3. Gross Profit. This is better for the buyer than revenue and better for the seller than EBITDA.
  4. Key customer. If a key customer leaves or reduces purchasing, x% of FPN is forgiven.
  5. Key employee or seller performance. Forgiveness can be tied to retention of key employees or seller’s performance after closing. This blurs the line between performance-based compensation and purchase price consideration.

SBA 7(a): If financing with an SBA 7(a) loan, a forgivable note is allowed. However, the metrics have to be rooted in historical financials. Otherwise, the SBA will view it as an earnout, which is not permitted.

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Reply by a searcher
from Stanford University in Redwood City, CA, USA
Great post thank for the insights Eli! How to the mechanics of the forgivable note typically work in terms of how often payments are made and how the target metrics are validated?

Asking since I'm talking to a seller of a ~$500K EBITDA painting business that is open to a very large forgivable seller note (95% of purchase price) contingent maintaining some large customer accounts with GCs. If the seller wants to be paid monthly, are you typically calculating the forgiveness metrics and revised purchase price and monthly payment every month or on some less regular cadence? I imagine this gets even more complicated with seasonal businesses without robust financials or monthly reporting (both are the case with this deal).

Also curious if a 3rd party escrow service is typically used that is able to validate the forgiveness metrics and payment due to reduce the risk of disagreements down the line.
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Reply by a searcher
from IE Business School in London, UK
Thank you for the insights
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