There is data and then there is the context around the data. Changing the context of the data changes the interpretation of that data. Context allows us to create signal from noise. If we tell you the average bank has one employee for every $5.9mm of assets, you likely would not care. However, if we tell you that bank performance and the assets-per-employee (APE) ratio are highly correlated and that the ratio is an accurate predictor of future performance, your curiosity is likely peaked. Further, if we give you more context and tell you that the average top performing bank as an APE ratio of $9mm and a classic underperforming bank has a ratio of $4.2mm you now have more context. In this article, we highlight several recent examples of how better understanding the context can help you close more quality loans in an effort to increase your APE ratio.
Example of Interest Rate Movement
We recently heard from a borrower who was lamenting that interest rates have increased too much recently and fixed-rate loans have become too expensive and unattractive. Below is a graph showing the ten-year fixed rate through year-to-date. The graph appears to show that interest rates are on a runaway train, and have increased by 60 basis points in just five months.
However, analyzing the cost of funding a ten-year loan over a longer period (30 years) shows a different story. The graph below shows that the ten-year rate is still abnormally low by historical standards.
If our context is five or six months, interest rates have hit the stratosphere, but a normal context stretching the normal up and down business cycles shows that the cost of debt is still exceedingly low. Bankers should be paying attention to the length of time of a typical loan commitment to assess the relative level of interest rates.
By showing the historical context of interest rates, borrowers cannot only make a more informed decision but are significantly more likely to make a decision and move forward with your loan. This is one reason why we equipping our lenders with the needed graphs. This functionality is available to all banks, the details of which can be found HERE.
Example of Corporate Structure
Very few corporate subsidiary charts are as complicated as the one below.
However, bankers that view only the legal entity are not analyzing the full credit risk in proper context. A recent transaction that we witnessed is a good example. A community bank was feeling pressure from a regional bank on a commercial real estate (CRE) loan. The borrower is a special purpose entity with one building. The borrower’s NOI is weak and LTV high, and the community bank wanted to keep the loan spread wide while the competitor was offering a “crazy” low spread.
The issue for the community bank is that the operating company has substantial credit strength, but the operating company does not provide a complete corporate guaranty for the loan to the community bank. The regional bank lends to the operating company and benefits from a much stronger borrower profile. The regional bank is pricing the loan based on the higher credit quality of the operating company, not on the lower quality of the special purpose entity (the borrower). If the community bank could view the greater context of the corporate structure and benefit from the better credit quality of the entire corporate relationship, the community bank could retain the loan and try to expand its relationship with the operating company.
Example of Protecting Cash Flow
We were recently structuring a loan for a construction project and the credit team concluded that they were not comfortable offering the borrower a permanent, “take-out” loan. The reasoning was that with the 24-month forward, the forward rate on the takeout made the debt service coverage (DSC) ratio very tight. A junior credit officer concluded that the bank’s preference was to commit to the construction loan and address the term loan when construction was complete. This is a prime example of how to cultivate future special asset management positions for the bank. The potential non-performing future project is unlikely to be another bank’s problem.
The hope that NOI improves, or interest rates decrease, or another lender takes the takeout loan is not a banking strategy. Below is a graph showing DSC ratio for various starting levels and then showing where interest rates movements will drive the initial ratio. A relatively healthy starting 1.30X DSC loan falls below 1.0X with 2.80% interest rate movement. A loan needs to show 1.50X initial DSC ratio to be able to withstand 3.00% interest rate increase and still be not be a future troubled asset.
Rent increases are slowing, cap rates are at historical lows, and construction costs are rising. Hoping that post-construction interest rates may be lower or NOI higher is not a viable strategy for banks.
Context matters and can be your friend or foe in banking. We assume that every loan booked today will have to withstand an economic downturn. It is important for bankers to view the totality of risk and return in proper context. With a full 360 analysis, community banks will be in a better position to withstand the next downturn.
Submitted by Chris Nichols on June 06, 2018