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Underwriting a Tenant with Private Credit (Updated June 2024)

Recently, we had an Accelerator member ask a question about how to accurately determine a credit rating and spec income discount rate for a private tenant in a single tenant net lease deal. While the scenario specifically involved a medical office tenant (a doctor’s practice), the application could easily be applied to a number of tenants.

In short, the doctor had been in practice at the location for a number of years. But how would you assess the risk profile of such a tenant? Public companies have transparent financials, with readily available public credit ratings from the major agencies. Gauging risk for a private company can be a bit tricker. So, in my response, I helped answer two questions

  • How can you underwrite the credit of a private company or individual? and
  • What would be a reasonable rate to discount the cash flows?

When You Might Need to Underwrite Private Credit in Real Estate

So, this question came up in regard to using our Single-Tenant Net Lease Valuation model. That particular model requires that you input two different discount rates: a credit discount rate and a speculative discount rate.

The credit discount rate relates to the rate at which the credit cash flows (i.e. in-place contract cash flows tied to the existing lease) are discounted in the present value calculation. The speculative discount rate relates to the rate at which the speculative cash flows (i.e. future cash flows NOT tied to an existing lease) are discounted in the present value calculation. The sum of the discounted cash flows for the two cash flow types (i.e. speculative and credit), is the theoretic value of the property.

The Accelerator member was underwriting a property where the tenant was a private dental practice, with no public credit rating was available. And therefore, the it became necessary to derive an appropriate credit discount rate with minimal information. I shared one possible methodology for accomplishing that.

Are you an Accelerator member? Learn more about using the DCF method for valuing real estate in the core curriculum of the Accelerator. Not yet an Accelerator member? Considering joining our comprehensive real estate financial modeling training program available and take your skills to the next level.

1. Create a Private Credit Rating

In terms of the first question, private credit (i.e. the discount rate for the Credit Income of private entities or individuals) is tough to underwrite. This is because no two private companies (or individuals) are the same. It really depends on the creditworthiness of the business and/or the individual personally guaranteeing the lease.

So, for instance, if Bill Gates personally guarantees the lease, the credit quality would essentially be AAA and would therefore merit a very low discount rate (e.g. UST + 50 bps) for the credit income.

In contrast, if the private company is on the brink of bankruptcy and has no solid personal guarantor behind the lease, the credit quality is essentially junk (e.g. D) and might merit a discount rate in the 15%-20% range.

One way to solve for this is to make your own best estimate of likelihood of default over the next ten years. This is a best guess, of course, but should help you arrive at a relatively appropriate credit rating equivalent. Once you’ve made that assumption, you can compare that likelihood to the cumulative default rates by S&P-rated companies over the past thirty years (see below) to derive your own private credit rating.

Underwriting Private Credit through Global corporate annual default rates

2. Use the Private Credit Rating to Estimate a Bond Yield Equivalent

With that private credit rating developed, you would then find the bond yield of the equivalent public credit, and add some real estate risk and illiquidity premium (e.g. 100 bps) to that rate to arrive at a credit income discount rate. This involves comparing your estimate of default risk of the private tenant with the default risk of companies rated publicly.

So, for instance, imagine your analysis determines that the tenant has a 10% chance of defaulting over the next ten years. That is approximately equivalent to the 10-year default rate of a BB to BB+ equivalent credit on S&P. BB corporate bonds currently trade at about a 6.4% yield. Add 100 bps to that to arrive at a credit income discount rate of 7.4%.


3. Estimating a Speculative Discount Rate

In terms of speculative discount rate, that’s much simpler. Consider the cap rate of a non-corporate credit medical office tenant, and then add projected rent growth (e.g. 2%). So, for instance, if a medical office (without a corporate guarantee) typically trades at a 6.0% cap rate and you expect an average 2% growth in rent over the next ten years, then you would use an 8.0% (6% + 2%) speculative discount rate.


Hopefully, that gives you an idea of how to approach these types of scenarios. You will bring a lot of value to your position in being able to apply some well-thought-out analysis where there is ambiguity. Accurately identifying risk is a major part of CRE underwriting and an opportunity where you can really prove your worth.

Finally, where it may apply, and for more targeted guidance in your tenant valuations, consider using our specialized STNL Valuation Model GPT. This tool is designed to help increase your valuation precision, especially when dealing with private tenants like we discussed in this article. It integrates seamlessly into your workflow, providing actionable insights and a systematic approach to determine credit ratings and appropriate discount rates. Explore the capabilities of this tool here.

About the Author: Born and raised in the Northwest United States, Spencer Burton has over 20 years of residential and commercial real estate experience. Over his career, he has underwritten $30+ billion of commercial real estate at some of the largest institutional real estate firms in the world. He is currently President and member of the founding team at Stablewood. Spencer holds a BS in International Affairs from Florida State University and a Masters in Real Estate Finance from Cornell University.