By John J. Coffey, C.P.A. and Gene Palm, www.profitres.com, originally published September 2005, ABA Bank Marketing

Are You Gellin’?^TM

Dr. Scholl's^®’s “Are You Gellin’?^TM” TV ads communicate one thing – if your feet feel good, then you’ll have an absolutely great attitude when things go wrong.  If only life were that simple!  But Dr. Scholl's^® has a good point.  If you paid attention to the details, you wouldn’t have to worry about the big things.

As a bank marketer, one of the “details” to which you should pay attention is how the bank makes money!  Specifically, how the bank calculates how it makes money.  Because this involves breaking out the banks income statement, this is not a simple task.  First, you have to calculate net interest income, non-interest income, non-interest expenses, provision for loan losses; which, then leads to net income.  In total this may seem easy, but doing it at the account level is really something!  However, once this has been done, the bank can calculate product, customer, and branch profitability – as well as how profitable your marketing campaigns are!

While you may not be the person who works directly on a project such as this, you should have a good understanding for how this is done.  If your Finance Department has developed a profitability model, it is very likely that they have mapped the bank’s General Ledger (or G/L) data into their model.  The G/L is often called the “Chart of Accounts” or “Trial Balance.”  Among other things, this report contains a detailed listing of all of the bank’s non-interest expenses and all the bank’s sources of non-interest income.

How G/L Accounts Are Mapped

Your bank can map its G/L data in a variety of ways to help the bank more accurately calculate its non-interest expenses and non-interest income at the account level.  Because this process is subjective, it is as much an art as it is a science.

For example, non-interest income G/Ls are much easier to map because most of your banks fees are directly related to specific products.  For instance, NSF fees would be mapped to the checking products, which gave rise to the NSF income.

However, the operations of the operations of a bank are much too complex to expect non-interest expense to fall into line so easily.

For instance, you’ll find that only a few non-interest expense G/Ls are related to specific products – one example might be if your bank logged a specific expense for the cost of booking an NSF fee every time a customer overdrafts their checking account, like a commission paid to a third-party vendor.  If this were the case, then the expense could be mapped to the same checking products (which gave rise to the NSF income) so that they could absorb a portion of the NSF expenses.

For other non-interest expense G/Ls, you might find that they are more closely related to processes than they are to specific products.  For example, the cost of postage could be related to statement rendering, CD renewal notices, loan late payment notifications, or even marketing initiatives.  As such, these may require you to collect baseline data, to determine “rules” that would assign every account in the bank a portion of these costs.  Sometimes these rules are expressed as weight factors or percentages; and, both approaches work just fine.

Finally, you will find many non-interest expense G/Ls that are related to the bank’s organizational units (such as branches and cost centers).  Chief among these would be salaries and benefits, occupancy, and equipment expenses.  These expenses tend to be the most difficult to map.  In this case, the first step is to determine total expenses related to each organizational unit.  Then, you must identify the products with which each unit works so you can map these expenses only to those products.

However, some of those organizational units do not work directly with bank products; instead, they provide support functions.  For these, you will have to forgo the “functional assignment” and assign them using other rationale based on their function.

Using G/L Data in Your Marketing Campaigns

Once your bank has completed this mapping, the total non-interest expenses and non-interest income of all of your accounts will equal the total amounts for the bank.  This process is referred to as “fully allocated” or “fully loaded,” especially as it relates to costs.

It is important to know that when you design a pro-forma ROI analysis for a marketing campaign, you do not need to include all of the costs of the bank because the bank is not going to add more people or add more buildings as a result of your successful marketing efforts.  However, you do need to add the incremental costs such as the cost of the marketing campaign, data processing costs, etc..  You can identify these incremental costs when the G/Ls are mapped into the profit model.  By using just the incremental costs in your pre- and post-campaign ROI analysis, you can give your Management a much more realistic (and profitable) assessment of your marketing campaigns.

Are you G/Lin’?  If you are, then you are paying attention to the details and can let the big things take care of themselves!

John J. Coffey, C.P.A. and Gene Palm are the principals of Profit Resources, a consulting company that specializes in MCIF technologies.  © Profit Resources, Inc. 2006