It is a sobering reality that the "80-20 rule" of customer profitability-80% of profit typically derives from 20% of customers-often understates the case in the financial services industry. The top 20% often effectively subsidize all the rest, who can range from marginally profitable to downright losses.

This dramatic skewing has motivated financial services professionals to find ways to improve the profitability of the customers who perform worst.

It is probably impossible to prevent these skews from happening, but today they can be managed more effectively than before. Sophisticated models of customer purchasing and behavior can segment customers by usage patterns and economics. Armed with this information, financial institutions can develop targeted "relationship pricing" structures that directly link prices to each customer's buying and usage behavior.

With relationship pricing, the targeting mechanism is embedded in the pricing structure: Individual customers "activate" the appropriate pricing action (such as a fee or fee waiver) according to their actual use of the product or service.

The payoff from relationship pricing can be both swift and substantial. Our experience has shown that a policy of relationship pricing can recoup 60% to 85% of the profits previously "lost" on low-profit customers.

For one thing, the new price structure typically leads to the attrition of unprofitable accounts. Other profits come directly from the price increases or when customers react to the new prices by migrating from expensive channels to less expensive ones.

The trick, of course, is to increase prices in a way that turns unprofitable customers into profitable ones-and ensures that the changes remain transparent to the most valuable customers. Maintaining transparency is imperative in the financial services sector, since repricing a single financial product can affect other customer activities and channels.

We believe financial services executives should not set prices by intuition or in response to competitors' actions. Instead the financial institution must start with a clear understanding of the relationship between customer behavior and overall profitability.

This is not as easy as it might seem. A bank may not be making a profit from a customer in one product line-for example, a savings account-but if that customer uses other banking services, the overall relationship may eventually prove to be highly valuable.

Advanced segmentation tools can identify aspects of customer usage that are the major drivers of profitability. Armed with this information, a bank can learn precisely where to focus repricing activities.

Once we know where to reprice, the next step is to decide how. Financial modeling helps gauge the likely economic impact of various repricing options.

The first step is to forecast all major behavioral cost and revenue drivers, then overlay the results to determine which pricing structures make the most sense.

Our experience has shown that the gains from repricing are almost always large-often dramatically so. Though there are many obstacles to be addressed-including regulatory concerns, systems inflexibility, and fear of customer attrition-evaluating and understanding the trade-offs has enabled many organizations to realize a variety of benefits.

Relationship pricing increases customer profitability by bringing prices in line with use-or alternatively, by bringing use in line with prices.

It is natural for bankers to focus on the secondary outcome: In the wake of repricing, some customers might prefer to close their accounts and leave. The possibility of losing even a limited number of customers runs against the grain of the industry's traditional mind-set.

We believe that the time has come to change that marketplace-driven mind-set. If repricing is done correctly, it will be the unprofitable customers who leave. Financial institutions that let concerns about attrition affect their repricing strategies will inevitably find themselves spending huge resources to chase unprofitable customers.

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