Among many bank marketing experts an article of faith is that 80% of a bank’s profits come from 20% (or fewer) of a bank’s customers. I don’t know whether that’s a valid statistic, but it’s a provocative point for examining how well your bank hits that target.
Is a basic getting short shrift?
I’ve been leading a course for the ABA’s e-learning efforts for a few years that deals in part with improving net non-interest profitability. The industry term for measuring and tracking account and household profitability is “account analysis.”
The first time I ever ran into this was many years ago in Miami. My bank, a prominent regional institution, had a largely automated way of collecting and aggregating costs and income components by account and presenting the information in a comparative format.
The process was not necessarily precise—we could always disagree on the formulae for allocating cost and income. However, over time and through consistent application, the process became reasonably accurate as a way of calculating account profitability. It also afforded the opportunity to do a relative ranking of the bank’s deposit and lending business customer by customer.
What has surprised me during the last two or three years is how a number of participants in my ABA course have no working knowledge of account analysis.
I can’t imagine that banks don’t perform these calculations with greater or lesser formality across the industry. But I suspect that the information is not plugged into the frontline thinking of some institutions.
Risks of not getting this right
If account (and household) profitability isn’t top of mind these days, is your bank risking its strategic viability?
Another way to state this, in terms of a practical consequence, is that if you don’t really know who is profitable—as well as who is not—you’ll be less likely to maintain your independence.
“We know who our profitable relationships are” some of you will say to me.
My response is, “No, you don’t, if such conclusions are not driven by hard data.”
The consequences of using guesswork or simple assumptions, rather than empirical information, is subpar profit performance over time. That’s one of the consequences of using seat of the pants thinking.
And it’s potentially a major source of risk to your company’s long-term viability.
As I’ve maintained consistently for years, being less profitable than one sustainably can be is a pernicious form of operational risk.
Looking back at the Sheshunoff method
It’s been several years since Alex Sheshunoff, a banking consultant known to many of us, published an article on the subject of customer relationship management that became an instant classic in bank marketing. And it’s as relevant today as it was the day it was written. It only seems a bit dated by his emphasis on technology to produce the information and the desired results, the sort of capability beyond the reach of many community banks in a cost-effective way only a few years ago.
His methodology in the conceptual sense is simple enough and applicable to big banks and small and can be summarized simply in my own words as follows:
1. Know who your best customers are and make sure you value them in specific, tangible ways.
Say thank you sincerely and often.
2. Know which customers are marginally profitable and develop an array of strategies to improve their value to the bank.
This is “share of wallet” thinking and is basic cross selling.
3. Figure out who the losers are and develop a plan (or a series of strategies) to improve their profitability.
This can mean both cross selling and more discipline in collecting service charges.
4. Make a candid assessment about which customers inhabit the bottom tier of profitability.
If there are ways to improve their value, then start right away. If not, develop a strategy to get them out of the bank.
As simple as this sounds, there are some community banks that fail to address basic customer profitability for one—or both—of the following reasons:
1. They don’t know who their profitable and unprofitable relationships are.
2. They lack the will and discipline to eliminate those with little prospect of improvement.
Yes, I said “eliminate.”
Force the bottom tier, those chronic and unfixable losers, out of the bank.
Revisiting account analysis essentials
Account analysis, for those for whom this is an unfamiliar concept, begins with a breakdown of account activity into components of revenue. These include such factors as interest income, commitment fees, imputed income on deposit account balances, and service charges collected. The next step is to subtract all allocable expenses. These include such factors as cost of funds to support lending activity, capital allocation, and loan and account transaction processing costs.
Items of revenue are offset by items of expense and the result is net profitability by account and, through aggregation of related accounts, by household.
While this is not necessarily a precise process, especially the part requiring an explicit costing of a bank’s internal services through allocation of expense items, it nonetheless yields reasonably accurate information over time in the relative profitability sense.
Large banks have taken account analysis to very sophisticated levels but sophistication need not be the governing concern at the community bank level. Rather, consistency of collection and reporting of account profitability information—and using it as a tool of account management—is what gives the information value and meaning.
All analysis systems require software and maintenance and have acquisition and maintenance costs associated with them.
So consider this old-fashioned thought:
Information only has value if you would do something different for having it.
Is blindness or ignorance an affordable expense?
Think of it this way: If you were pretty certain that you knew who was unprofitable and why, would you act on that information?
The foundation of a functioning customer relationship management system is information—consistently and regularly produced and reported.
This costs money, though economies of scale certainly apply.
It’s here that some smaller banks simply fail to see the value of such information relative to its cost. They rationalize their lack of hard information as a justifiable cost/benefit trade off.
That’s an assumption that should be carefully analyzed by their directors.
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