Using Your MCIF for Relationship Pricing.

As bank marketers we can be so focused on our own marketing campaigns that we forget that our customers actually purchase other products from other places. Our customers are so used to receiving a discount from stores like Wal-Mart when they purchase in bulk, that they think it is logical that they are rewarded for "bulk" purchases of their banking products. And, customers are so used to having all of their purchases listed on one receipt--is it any wonder they want to have their banking products consolidated on one statement?

But, you say, "It's unfair that our customers are treating us this way. After all, we are a bank!" In fact, to meet their demands, we would need to reprogram our mainframe, reformat our report designs and try to figure out all sorts of ways to reprice our products in order to accommodate our customers.

Welcome to the 21st century! If you don't reward your customers for their consolidated balances and if you don't provide consolidated statements for them, someone else (perhaps Wal-Mart!) will.

Fortunately, you can use your MCIF to help you understand the combinations of products that are purchased by your customers. The MCIF can also help you price your most profitable combinations of products. This process is called "relationship pricing." Finally, you can use your MCIF to enable your data provider to implement relationship pricing and consolidated statement rendering.

How do I use MCIF research and reports to establish relationship pricing?

The most powerful feature in an MCIF is its ability to "household" all of your customers' accounts so you can have a holistic view of your customers' relationships. Using householding, you can view the customer's total deposit or loan balances. Better yet, you could construct a research query that would pinpoint customers who exceed some combined minimum balance level, based on total balances. Then, you could and use this file to run a "service combinations report" to view the most profitable combinations of products based on these minimum balance levels.

You could also use this research file with a "product summary report" to view the profitability of the individual services that make up these combinations. You could then export this "product summary report" into a spreadsheet and perform a what-if analysis of your relationship pricing by adjusting the rates and fees of your products. By doing this exercise, you would better understand the impact of reducing your fees, raising your rates on deposits or lowering your rates on loans for this profitable group of customers.

The most important thing to remember in relationship pricing is this: The carrot is more powerful than the stick. If you tell your customer that you wouldn't charge your minimum balance fee if they kept $2,500 in their deposit account, then they would be likely to keep a total of $2,505 in that account to avoid your "stick." However, if you told your customer that you would give them better rates for combined balances of $20,000 or more, then they would be more likely to bring you $50,000 in deposits or loans because of your "carrot"!

How do I use my MCIF to help process relationship pricing?

If your bank does not have the ability to automatically calculate relationship pricing, it is possible for you to export account level relationship pricing codes from your MCIF into your data processing system. For instance, a code of "A" would mean that your customer has $20,000 or more in deposit or loan balances. The data processing system would hopefully be able to waive the fees on all customers who have a code of "A" Also, if the data processing system does not have the ability to automatically generate consolidated statements, it would hopefully be able to segregate all of the statement information on customers who have a code of "A" and you could have a third party generate these statements.

John J. Coffey, CPA, and Gene Palm are the principals of Profit Resources, a consulting company that specializes in MCIF technologies: