Take Advantage of These Common Misconceptions For Lending Profit

Lending Profitability

Relationships between different variables can be very complex in the real world and banking is a perfect example of this complexity. The human mind, however, is skewed to perceive relationships in a linear fashion and this can lead bankers to make the wrong decisions.  With the odd shape of the yield curve, we are seeing smart bankers making very profitable lending decisions because they understand their business model, the shape of the yield curve and the nonlinearity of commercial loan pricing. In this article, we highlight some of the more common non-linear relationships that many bankers believe to be linear.


Examples of Nonlinearity


To first clarify the concept, let us consider one common example of a nonlinear relationship outside of banking.  We all agree that there is some form of relationship between the level of taxation and the prosperity of a nation.  One view may be that lower taxation leads to greater prosperity – and that view may be represented as a right-wing view and shown below.   This relationship demonstrates that prosperity is maximized when the tax rate approaches zero and prosperity becomes completely eroded as tax rate reaches 100%.


Nonlinear views in banking


The alternative view is that higher taxation leads to greater prosperity – and that view may be represented as a left-wing view and shown below. This relationship demonstrates that prosperity is maximized when tax rate approaches 100% and prosperity is completely eroded as tax rate reaches 0%.


Linear thinking in banking


Most rational people agree that the relationship between tax rate and prosperity is not a simple linear relationship and is a nonlinear connection that looks something like the graph below.  The only debate is where prosperity tops out, but it is somewhere between 0% and 100% tax rate and not at either extreme. Empirically, it looks something close to the graph below.


nonlinear thinking in banking


Nonlinearity In Commercial Lending


Nonlinear relationships abound in banking. For example, the relationship between debt service coverage and credit is often discussed in bank credit circles as a linear relationship. We just heard the other day that, “five times debt service coverage (DSC) is twice as good as 2.5 times coverage.” That is not exactly true. The probability of default and debt service is a non-linear function that can be seen below for a commercial real estate loan.


CRE Probability of Default


Similarly, bankers often assume that credit risk is linear throughout the life of a loan. It is not. In the later years, payment seasoning, appreciation, and loan amortization all decrease credit risk. This helps explain why a longer-term loan is much more profitable for a bank in addition to just providing a longer set of cash flows. Many bankers unwittingly think nothing of putting a balloon maturity right at a point when credit risk is the highest and profitability is the lowest.


Annual Probability of default


Finally, one of the most common non-linear misconceptions is over the shape of the yield curve.  The news media, economists, and bankers are all discussing the flatness of the yield curve.  However, the assertion that the yield curve is flat is incorrect because all of these participants define the relative shape of the curve by looking at only two points (usually two-year and ten-year differential), without considering the nonlinear shape of the entire curve.  The yield curve has steepness at the front end and is flat at the back end.


Below is a graph showing the yield curve from 1 month to 20 years.  The relationship is nonlinear and shows a steep yield curve for the first two years and then a flatness beyond three years.


US DOllar Swap Curve Loan Hedging


Opportunity for Bankers


By understanding the shape of the yield curve and human behavior, knowledgeable bankers can take advantage of the nonlinear relationship between interest rates and tenor and obtain above market pricing on commercial loans.  The incremental cost of funding from three years to 20 years is minimal.  The incremental cost of funding a loan between three years and 20 years is currently only 14 basis points.  However, borrowers are willing to pay a much higher premium for longer-term commitments than the actual cost for banks to lock these longer-term rates.   


Currently, community banks can offer longer-term financing (ten, 15 or even 20 years) at incremental pricing that is 25, 50 or even 75bps above three-year fixed rates.  The difference between what the borrower is willing to pay and the bank’s cost of funds for that period flows directly to the bottom line.  Smart bankers are positioning their loan duration further out on the curve, converting the yield to floating and enhancing the return on assets by 25 to 75 basis points.




The shape of the yield curve can also deceive bankers and lead to poor decisions.  For example, most of the shape of the yield curve is between one-month and three-year tenor.  The market expects the Federal Reserve to more aggressively raise interest rates over the next 2 or 3 years, and the industry’s cost of funding will surely follow.  Therefore, pricing loans in the two to three-year tenor is probably an unwise move.  The average yield on three-year commercial loans is about 4.50 to 4.75%, which is an adjusted yield of only 1.50% to 1.75% over LIBOR.  Bankers that make that lending decision in the two or three-year term and factoring their current cost of funding are taking a large risk. 


There are currently four reasons to avoid three-year commercial loan duration:


  1. The market is expecting interest rates to rise most prominently during this period,
  2. We expect deposit betas to normalize to 0.6 to 0.7 during that same period,
  3. The repricing risk for the borrower creates credit risk for the bank in an environment where cap rates are low, LTVs are climbing, and DSC ratios are skinny, and
  4. The three-year duration positions the loan to possibly reprice during the next recession.




Insightful bankers are taking advantage of the nonlinear nature of the credit and yield curve to maximize the ROA on their loan portfolio.  The opportunities in the market today involve pricing loans between five and 20 years (but eliminating interest rate risk) and striving for a debt service coverage ratio of at least over 1.40. It is in these areas where banks can earn the greatest relative value. Loans priced in the two and three-year portion of the yield curve are generally less profitable and more risky for community banks.