Where to Set Minimum Debt Yield Ratio

Improving CRE Underwriting - picture of a office building

In one of our blogs last week we discussed why community banks should adopt minimum debt yield ratio for underwriting purposes.  We demonstrated how a debt yield ratio could help community banks properly measure the interplay between cap rates, interest rates, and cash flow.  We analyzed how real estate loans originated today at 1.20X debt service coverage ratio (DSCR) and 75% loan-to-value (LTV) may quickly become substandard credits if cap rates normalize, interest rates rise to long-term averages, or NOI is stressed in an economic downturn.  In response to our blogs, many readers asked where bankers should set minimum debt yields for various properties.  In this blog, we would like to outline one methodology that community bankers can use to define minimum debt yields.

 

Debt Yield Ratio Revisited

 

As readers recall, the debt yield ratio is a property’s net operating income (NOI) divided by the property’s debt, and this measures the cash-on-cash return on the bank’s investment.  As a credit tool, debt yield is not fooled by a stretched amortization schedule, historically low-interest rates, historically low cap rates, or other variables that can temporarily increase real estate values.  By measuring only DSCR and LTV, many banks would make the loan as outlined in the table below at 1.22X DSCR and 71% LTV (8.4% debt yield).  Unfortunately, at the project-level, that same loan cannot withstand NOI declining by 15%, cap rates increasing from 6% to 8%, or interest rates increasing by 200bps.  The same loan underwritten to a 10.1% debt yield is a substantially better credit.   

Debt Service Coverage Calculation

How to Set Debt Yield Levels

 

The goal of community bank lending is to underwrite loans with a positive risk-adjusted return on capital that is in excess of a bank’s cost of capital. However, credit risk is driven by inherent future uncertainty.  This future uncertainty can be quantified with financial tools that have been used for decades with very strong predictive values.  Losses on commercial real estate are driven by two primary triggers:

 

  1. The cash flow from the property is inadequate to cover mortgage payments; and
  2. The value of the underlying commercial property is worth less than the outstanding mortgage.

 

Because commercial real estate is an asset class whose primary focus is on producing rental income (whether as an investment property or occupied by the owner), it is more productive to focus on the income production of the asset, especially because the income largely determines the value of the commercial property. 

 

The issue is that a property’s NOI is not static and the level of cash flow at origination can vary over time.  While decades of experience at community banks demonstrates that a borrower’s decision to default is not purely a financial matter, the steps below are a simple approximation of a borrower’s decision.

If a property is not generating enough NOI to cover the periodic mortgage payment, a borrower must consider the following options: 

  1. Cover payment shortfall out-of-pocket.  This is preferred by the borrower if the shortfall is deemed temporary.
  2. Sell the property and pay back the mortgage.  This consideration involves quantifying marketing costs, transaction costs and carry costs.
  3. Default on the loan by missing payments and negotiate with the lender on restructure or foreclosure.

 

As a lender, we would like to quantify the possibility of NOI falling below mortgage payment.  In the graph below, we show historical NOI for a hypothetical property in the red line, the 1.20X DSCR in the blue line, and mortgage payment in the green line.  While this property starts at 1.22X DSCR, we want to quantify the probability that cash flow decreases below the mortgage payment line and set our debt yield accordingly.   

NOI Graph

Luckily substantial raw data exists for the historical volatility of cash flow for various property types, and in individual markets.  By measuring the volatility of cash flow we can apply debt yield to ensure that for a specific property type and in a specific market the NOI would not fall below the mortgage payment to a specific confidence level.  The table below (reproduced from a research paper submitted to the Real Estate Research Institute, February 2011) shows long-term average standard deviation for NOI for different property types:

Standard Deviation By Property Type

The volatility numbers above can be adjusted for specific markets, specific lenders or even borrower circumstances.  However, the methodology for solving the debt yield level is similar.  We want to ensure that the NOI from the property does not decrease below the mortgage payment for a specific confidence interval.  Banks can then use 2 or 3 standard deviation interval to measure the minimum necessary debt yield for 95% or 99% confidence of non-default.  Using the above volatility numbers, we create the table shown.  

 

Required Debt Yield

 

The above table demonstrates that for office property, assuming 10.6% standard deviation for NOI (and this number can be refined for individual markets and sub-properties) a community bank must set its minimum debt yield to 10.14% for an approximate 1% probability of default.  Each bank can calibration assumptions for its specific market and sub-segment.

 

How to Apply at Your Bank

 

Banks should be including minimum debt yield ratios in their underwriting standards because unlike DSCR or LTV, the debt yield is not affected by longer amortization schedules, low-interest rates, low cap rates, or any other variable that can temporarily increase real estate values.  The methodology and process of setting minimum debt yield are not onerous.  Generally, minimum debt yield should be in the 10% range – slightly lower for less volatile NOI properties (such as multi-family) and slightly higher for more volatile NOI properties.