If you think your bank has tough employees, consider a bank that brought in a motivational consultant that had the employees walk on a 6 ft. wide path of hot coals.
Tag: Predictive Analytics
The volatility that is kicking up in the market is causing a resurgence for banks to develop early warning signals on credit. Banks sit on a treasure trove of data that is only partially utilized.
Say what you will about hospitality lending, but it is one of the more responsive industries in our economy and highly predictive of economic cycles. It was one of our first indications banks had back in 2007 to tell us something was amiss in the economy. That warning sign is flashing yellow again, and it is causing us to pay a little closer attention to our data. In this article, we look at hotel sector fundamentals, hospitality loan performance and what current data is saying about the current economic cycle.
Daniel Björkegren, an economist at Brown University in Providence, released research that shows that banks can predict how likely someone was to pay back a loan based on cell phone call metadata. After analyzing data from 3,000 borrowers from a bank in Haiti — the number of calls, the length, frequency and who was called, Björkegren found the bank can reduce consumer loan defaults by 43 percent.
Many banks talk about delivering a targeted local approach, but end up spending their marketing budget to garner a mass appeal. Nine times out of ten, this is a mistake and by utilizing a different approach, banks can be more efficient in their marketing dollars. As usual, solving this marketing problem is a function of asking the right questions. The question is not “How does the bank acquire more customers,” but “How does the bank acquire the right customers.” This means that first you have to understand who the right customer is.
This week’s SBA announcement that the Agency will make available borrower’s credit score that takes into account both personal and business attributes has sent shock waves through the industry. The funny part is that these shock waves were not the ones intended. The intention was to let the Nation know that Maria Contreras-Sweet, the new head of the SBA, is ready to help minority lending and that will further stimulate the economy.
Do you treat all cash flow the same? That is, does a property with a 1.25x debt service coverage get a “3” rating no matter what type of property it is? If so, your bank is most likely mispricing risk which will hurt performance over time. Every waking business day, bankers have to make decisions and the ones with the best information will have superior performance over time.
You can ignore data when underwriting, but that would be a mistake as sometimes the differences are stark. Our best example comes from fresh data from the office supply sector. Normally, industry probabilities of defaults (“POD”) move by about 7% per year. In 2014 certain industries, like banks and retail office supply stores, moved with large rates of change and even multiple rates of change. While banks are moving in a positive direction and risk is being reduced, retail office supplies are moving in the opposite direction.
What if there were a set of three easy to distinguish factors that, if all present, could predict the future performance of your customer and reduce the probability of default to half that of their respective industry? Would you do anything differently? Would you price lower? Would you extend more credit? Would you change your sales or marketing process at all to go after those accounts?
Knowing where we are in the business cycle is a key input into looking at projected probabilities of default for loan credit underwriting as well as future loan prepayment speeds. If done correctly, banks want to tighten underwriting standards as the economy inflates and loosens them during the troughs of the cycle. Unfortunately, most banks do it the complete opposite loosening standards due to competition when things are overheated and tightening them at the trough.