If you are like most banks you have your credit approval and risk process based around loan size. The assumption is that the larger the loan the more risk the bank is taking on so a greater level of risk review is needed. But, suppose the data didn’t bear that assumption out? If that assumption is wrong, then that means that your bank is probably underpricing the smaller loans, overpricing the larger loans, applying the wrong cost structure to the larger loans and misaligning risk against your capital.
The last quarter in the year is typically a suboptimal time to generate commercial loans. Most bankers have met their annual goals factoring the existing pipeline of credits. Furthermore, banks that have not met their goals for the year are likely to price and structure more aggressively, thereby depressing profitable opportunities for more disciplined lenders.
In banking, as everywhere else in life, you never get a second chance to make a first impression. The first page of a credit memo is essential for credit analysts, lenders, management, and board members. The first page is prime real estate where the average reader will spend 25% to 50% of the time reviewing the credit submission. Because the first page commands so much of the average reader’s time, it is vital to draft the first page clearly, concisely and compellingly.
The Credit Memo
Recent data, just released from Real Capital Analytics, shows that since the start of the year (month-end April), commercial real estate (CRE) has appreciated 2.6% in 2019. This is good news for banks as it shows that every significant loan sector likely has improvements in both debt service coverage and loan-to-value. In major markets, this appreciation has been closer to 4.9%, and in secondary markets, price appreciation has been 1.5%. In this article, we take a look at the details to help banks better manage their pricing and risk.
Whenever your bank is looking at underwriting commercial real estate (CRE), you are probably looking at a variety of macro factors such as rent and occupancy trends, absorption, and capitalization rates. However, since we see hundreds of underwriting packages a month from a variety of banks across the country, it is rare that we see banks, and even borrowers, adjust rents for new construction. In this article, we present our methodology, data, and adjustment factors that banks can use to have more accurate underwriting.
In addition to traditional underwriting, some banks utilize a scorecard to rank their commercial properties. Projects are run through a scorecard and then rated on a numerical value. For banks without a credit or pricing model that provides a probability of default and expected loss, the scorecard allows an intermediate way to compare loan quality. In this article, we take a look at a sample scorecard and give banks some examples of how to use the methodology for better commercial real estate (CRE) underwriting and pricing.
Many community bankers have expressed an interest in adopting debt-yield ratio for underwriting purposes.
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 one of our blogs last week, we discussed why real estate loans originated today at 1.20X DSCR and 75% 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. We argued that community banks should be favoring 1.50X DSCR credits, as that is the minimum cash flow required to withstand a standard recession. We also stated that lenders must incorporate a minimum debt yie
If your bank is lending on a property with a variety of units available to lease, there is a chance that all those units might be leased up and there is a chance that none of the units will maintain their lease over the life of the loan. The reality is, the outcome is likely somewhere in between. The average banker would look at one set of cash flow and calculate their debt service coverage off a base case using a set of assumptions. The good news is you are not an average banker. Otherwise, you wouldn’t be reading this.