SMALL STEPS LEAD TO BIG RESULTS

Yesterday we gave a few tips around loan portfolio management to help bankers gain traction as new loan origination begins to accelerate. Today, we pick up by focusing on another area where you may want to devote summer intern resources. Consider how great it would be right now if you already had certain data loaded onto your system(s) and had the ability to quickly report on borrower exposures by lending type, NAICS code, property type and geographic area. These are all data points that don't change over time, so once loaded they can deliver ongoing value to your bank in multiple areas. Admittedly, most community banks do business in a small geographic area, but that doesn't mean you can't get leverage and insight by delving even deeper into city, metropolitan statistical area (MSA) or zip code level data. In most cases you already have this information, you just need to figure out how to drop it into a spreadsheet or database so you can leverage the information to better identify current and potential exposures. It is important to closely check the address loaded on your system using a complex group of loans first. That way, you can verify the data collected is the one(s) you want to track (multiple addresses are common for guarantors, legal entities, etc.). Next, include North American Industry Classification System (NAICS) codes for each loan. Use 6 digits to capture everything you can and make sure you add this as a field to check when you next audit to ensure all loans have been properly classified. If you are already capturing NAICS for 3 or 4 digits right now, expanding it will allow for more robust analysis in the future. For those who don't do this yet, consider that NAICS coding is a standardized approach the U.S. Census Bureau uses to classify businesses. Using these codes allows you to gather statistical and economic analysis from multiple sources that you can leverage (think loan loss reserves, borrower concentrations, etc.). The Census Bureau assigns a code to each business based on the activity that generates the most revenue. Since you care about loan cashflow the most, leveraging this coding system makes sense and adds flexibility for your bank. As a quick aside, NAICS coding is designed so that the 1st & 2nd digits represent the economic sector; the 3rd digit is the subsector; the 4th is the industry group, the 5th is the industry grouping and the 6th digit is the national industry grouping. As an example, a loan to a car wash would be found under #8 for transportation and warehousing; then 81 for Other Services; 811 for Repair and Maintenance; 81119 for Other Automotive Repair and Maintenance and 811192 for car washes. Note that code 811192 includes all establishments that primarily engage in cleaning, washing and/or waxing automotive vehicles. When you look it up you will find it includes businesses that do automotive detailing, washing, polishing, car detailers, mobile car and truck washes, self service car washes and truck and bus washes. That gives you a lot of information and flexibility. Once you have captured the 6 digit NAICS code and the zip code, you now know how many of a certain type of loans you have, the loan grade assigned to each and in aggregate; the loan amounts and the location to name a few data points worth analyzing. This gives you plenty of flexibility to do a great stress test on the impact of debt coverage of these customers if, say, chemical prices rise 15% for materials found in car wash soap. This is easy to do and gives you the ability to determine exposures by different factors. If you aren't all that into stress testing because you have enough stress of your own, consider using this data to improve pricing and profitability. Simply by being able to view similar loans by NAICS code, you can determine how well you are maintaining pricing discipline, track trends and identify sectors that might need attention (as well as those that are just fine). No matter how you use this data, the first step is to collect it, so make it a priority for the summer and get a couple of interns to start dropping it onto your system. Then check it, audit it and start using it to make improved decisions about overall loan portfolio risk. Start slow, take one step at a time and break the project into mini-projects so you can see your footsteps as you go.