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Many real estate specialists are familiar with the loan-to-value (LTV) ratio and the debt service coverage ratio (DSCR), but less recognize with using the debt yield (DY) ratio to underwrite loans for commercial real estate. For a comparison, see the formulas below with a description and an example of how the LTV, DSCR, and DY are determined.

Loan -to-Value (LTV) = Amount of mortgage loan/Value of the property

Property Value = \$15,400,000

Mortgage loan = \$10,000,000

LTV =65% = \$10,000,000/\$15,000,000

Debt Service Coverage Ration (DSCR) = Net Operating Income (NOI)/Debt Service

Net Operating Income = \$1,000,000

Debt service = \$700,000

DSCR= 1.43 = \$1,000,000/ \$700,000

Debt Yield (DY) = Net Operating Income (NOI)/Loan Amount

Net operating income = \$1,000,000

Loan Amount = \$10,000,000

DY = 10% = \$1,000,000/\$10,000,000

While it’s pretty clear how LTV and DSCR relate to the operation of the property, it’s typically less clear to those brand-new to real estate what the debt yield informs a lender. You can also look at the debt yield as the return that the lender would receive if it needed to seize the residential or commercial property. And much like LTV and DSCR, the debt yield will change in time depending upon how the property performs.

Why Not Just Use LTV and DSCR?
For many years, lenders depend on the LTV and DSCR to size loans on commercial real estate. So why develop a new metric if the previous techniques were working just fine? To actually comprehend why debt yield is various and why lenders have begun to consider it when making loans, we need to walk through a couple of examples. Bear with us as we walk through this slowly. There are quite a few inputs that require to be thought about to set up the circumstance in which the differences end up being apparent.

Assumptions
Before we start, we ought to examine a few of the fundamentals of property assessment and lending. Remember that the value of a asset can be approximated by dividing the NOI of the multi-family or commercial property by an appropriate market cap rate.

Market Value = NOI/Cap Rate

That was easy enough. Now we require to determine how much a lender is willing to loan on a home. Let’s very first look at the traditional metrics of LTV and DSCR to illustrate the limitations. In order to do this, we require to add a couple of more metrics into the mix. This time we’ll consist of the marketplace LTV and DSCR. Similar to rate of interest and cap rates, the market generally sets levels for the LTV and DSCR that a lender wants to accept. For the LTV, this range is typically in between 60% and 70%. The DSCR has actually a lower bound constraint of around 1.25. It’s crucial to keep in mind that the LTV and DSCR both differ by property type and class, however a much deeper discussion of the varieties is beyond the scope of this paper.

The table listed below strolls us through an analysis of the valuation, loan amount and payment for an industrial residential or commercial property in a low cap rate market. For the LTV, we’re assuming a market level of 60%, leading to a loan amount of \$12,000,000. Then applying a 5.25% mortgage rate and a 25-year amortization, we get a yearly payment of around \$863,000. So far this looks ok. However, the DSCR on \$1,000,000 of NOI with an \$863,000 annual payment is just 1.16, which is extremely low and most likely listed below what a lender will require to make the loan.

NOI           \$1,000,000

Cap Rate                  5%

Market Value  \$20,000,000

LTV                      60%

Loan Amount   \$12,000,000

Loan Interest Rate  5.25%

Amortization (years)  25

Annual Payment   \$862,917

DSCR   1.16

Alternatively, the table listed below walks through the analysis of a residential or commercial property in a high cap rate market. In this scenario, we’ll reverse the analysis and look initially at the DSCR constraint. Here we see that the market is requiring a minimum of a 1.40 DSCR. Utilizing the NOI of \$1,000,000 and the DSCR of 1.40, we can back into the optimal payment allowed of \$714,286. Using the exact same loan metrics as above, a 5.25% loan interest rate and a 25-year amortization schedule, we find that a payment of \$714,286 will support a loan amount of \$9,933,089 (using a present value formula). This seems ok until you take a look at the LTV that arises from a loan of \$9,933,089 on a residential or commercial property that’s valued at \$12,500,000 in this market: 79.46%. This is probably much higher than a lender would want to accept on a loan.

NOI  \$1,000,000

Cap Rate  8.0%

Market Value  \$12,500,000

DSCR   1.40

Payment  \$714,286

Loan Interest Rate  5.25%

Amortization (years)  25

Loan Amount \$9,933,089

LTV  79.46%

The situations above show the effect that large variations in cap rates can have on the loan providers choice of how much to loan. In contrast, a loan based exclusively on a debt yield restriction is made without consideration of market cap rates and resulting property valuation.  Some commercial lenders use a combination of DSCR and DY whereby a loan amount is determined by the lower number derived by the respective calculation

Sizing a Loan Using the LTV, DSCR, and Debt Yield
The scenarios illustrating making use of the LTV, DSCR, and Debt Yield above are really simplistic and were suggested to highlight some of the severe differences that can be seen under various scenarios. In the real life, lenders consider all 3 metrics and usually size the loan based on the lower quantity of the 3 techniques, although there is room for adjustment based on elements such as the quality of the home, quality of the borrower, and so on.

Many people ask why lending institutions do not simply need low LTV’s and high DSCR’s on the loans they make. Lenders would probably favor a world where that’s the case, however lots of borrowers tend to want greater leverage in order to boost equity returns. Today, there are hundreds, if not thousands, of commercial real estate lenders. Lenders require to stabilize the danger of making a loan with being competitive in the market. Hence, there is a continuous push and pull in between these metrics to try to attain an ideal outcome for both lending institutions and customers.