Every week we are sent stories and facts by bankers looking to help us out. We appreciate it, but we admit that it is sometimes hard to tell fact from fiction. At BIG, we have to constantly use our intuition, rigorous analysis and astute powers of observations to distinguish the truth. Take this week for example. how do we distinguish the truth in these stories: 1) Donald Trump thinks his hair looks "terrific"; 2) The total combined weight of the world's ant population is heavier than the weight of the human population; 3) Friday the 13th is actually lucky; 4) A Prime +1.50% construction loan with 1.00% fee is less profitable than a 5.75% fixed-rate, 5Y term loan with a 25bp in fees.
While the first 2 items on the list above are beyond our ability to calculate, a Dutch study did conclude that fewer traffic accidents happen on Friday the 13th. In addition, we can professionally apply ourselves to item #4 and use our analysis to prove that net revenue on construction loans are not nearly as high as those on fixed-rate, term loans.
First, our intuition tells us that loans that are higher risk, smaller dollar amount, low-usage and short-term combined with high underwriting costs and large administrative costs are not profitable. Second, our powers of observation have taught us that national banks are not eager for construction loans. In fact the national banks have arrangements with certain banks to refer construction business to them, allowing the national bank to return to the borrower when the projects are cash flow stable. Using our Loan Pricing Model and the models at national banks, we are convinced that term loans are more profitable on both risk-adjusted and net revenue basis.
Third, our rigorous calculated analysis shows that stable, longer-term loans are more profitable for a number of reasons: 1) Acquisition costs for banks are much larger than those represented by FAS91 calculations. With average total direct and indirect costs to book a loan totaling $7,500 to $15,000, only large or longer term loans have any prospects of being profitable; 2) The average loan fee does not compensate a bank for the cost to originate the loan. Therefore, return occurs over time as revenue is recognized in the NIM; 3) Because revenue is primarily driven by NIM, the draws on a loan are paramount in driving return (the higher the outstanding, the higher the return to the bank); 4) Banks consistently underestimate the overhead costs associated with high maintenance loans under the premise that the infrastructure is already in place and is a sunk cost. In the long run all costs are variable. But even in the short run, time and resources must be allocated to highest return business, not highest resource business; and 5) Expected losses are not the same across different loan classes. Expected losses are part of doing business and must be factored into any return analysis.
Our rigorous analysis above can be replicated using our subscription-based, proprietary loan pricing model. But the same conclusion can be reached using a simple excel spread sheet that can be created in just 30 minutes. We created such a spread sheet and for anyone who wants a copy, please let us know (we'll send it out to you within 3 business days, and no, there is no charge). We have always found it easier to show return on capital than to figure out why, despite having billions and access to mirrors, Donald Trump goes around looking like a troll doll.