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Customer-Profitability Analysis for Community Banks

By: Gary S. Shaivitz

In light of the latest onslaught of regulatory changes and increasing capital requirements, expectations for returns in the banking business have been dramatically reduced. As a result, strategic resource management, and thus profitability analysis, is more critical than ever. Yet, with profit margins constrained and with more waking hours devoted to regulatory issues, where does a community bank executive find the time and money to do one more thing?

Start with those that bring you your paycheck — the customers. Those customers who actually do pay you, that is.

But how does a community bank build a system that determines which customers contribute to the bottom line (and those who do not) without a major resource commitment? And if you get it done, how do you make this information meaningful and actionable so that it has a significant impact on bank performance?

Follow this six-step approach to building a customer profitability system and you will be on your way to meeting, and hopefully beating, performance expectations.

Step 1: Get Organized

Make it a priority. How can it not be? We are talking about our customers who help us make payroll.

Create a task force with the minority being from finance. Use the accountants as an important resource for modeling support and data input, but leadership of the effort should come from customer-facing management.

Put someone in charge. Task forces and committees are fine; however, when decisions must be made, get everyone’s input and then make someone responsible for making the final calls and moving on.

Step 2: Break it Down

Build the basics for income and expense. Start simple. Do not, for example, get stuck on determining the right funds transfer method. Just pick one and get on with it.

Collect account-level data. This is very important as account-level information is the primary building block for customer profitability systems. Get as much as you can and then some, including transaction data (type and channel) to the extent possible.

Assign accounts to a relationship type that your systems can handle (tax ID, household/CIF, if available). Again, simple and expedient is better. You can always revisit.

Assign a segment identifier to each relationship using basic segmentation schemes (i.e., general consumer, small business, middle market commercial, affluent consumer). Save identifying “mixed” relationships for later.

Compile as much demographic information (i.e. date of relationship [you may have to reach back to the first account opened], date of birth, address/geography) in your relationship or household database as well.

Step 3: Conduct the Initial Analysis — Ad Hoc First — and Use the Results

Use a basic database tool (Microsoft Access or even Excel can be sufficient at first, depending on the size of your bank) to collect and analyze the data.

At the account and customer level, study your customers’ source of business, revenues and costs. What need(s) are being met (i.e. credit, transaction, savings)? How does the customer use (or abuse) the product (transaction type, volume, channel)?

Start with creating profit tiers (using three-to-six month smoothed relationship profit) within segment (high-profit, marginal, losers). Analyze the customer base within the profit tiers by key driver (margin, fees, delivery cost) to help answer these questions.

Identify at least three learnings that you can apply in the short term. Assign responsibility for implementation.

Step 4: Automate the Analysis System

Wait to implement an automated profitability analysis tool until you have built the basics first and conducted the initial analysis. Going about it in this way gets you results more quickly, enables deeper involvement in the modeling and analysis process and therefore adds value to the end product and increases buy-in.

Most core systems providers offer a customer-profitability module or the ability to integrate with third-party software. Take your time in evaluating the systems alternatives. Among other factors, consider ease of integration with your core system and existing customer databases.

Step 5: Refine with Time

Focus on the issues that are identified by most of your team and will likely make a difference in your strategic, tactical and customer level decision-making.

Apply the 80/20 rule. Do not pursue perfection as you will not be able to make everyone happy anyway. As the saying goes, Rome wasn’t built in a day … on second thought who wants Rome anyway?

Step 6: Build into Your Way of Doing Business

Use it regularly. Develop regular reporting for customer-profitability results by segment and integrate with other customer/relationship metrics reporting (i.e. services per household, revenue by financial need) and track changes resulting from the implementation of strategic and tactical initiatives.

Integrate into strategic planning and budgeting processes. Set customer-profitability, revenue and relationship expansion goals by segment or line of business. Link revenue enhancement and cost management strategies to customer profitability goals, and develop strategic and tactical initiatives to improve performance based on the analysis.

Share with your customer-contact staff. Provide selected information to the front lines but train on its uses. The primary uses by front line staff should be to focus retention efforts on high-value customers, expand relationships through better understanding of customer needs and behavior, and guide customers to products that better fit their needs and how they interact with the bank.

Build in to performance management. For all levels of customer-facing staff, set team or individual goals for customer profitability (and other customer metrics). Add to incentive systems and you will see significant results.

In the long run, nothing is more important to any business enterprise than understanding who helps us earn our living. Non-financial businesses have known this for years. Bankers need to do this as well, no matter how big or small and especially in the new, more challenging environment of increased regulatory burden and revenue compression. Taking a structured approach to measuring, analyzing and using customer-profitability information is one way to help meet the challenge.

Gary S. Shaivitz, CFA, is partner and senior consultant of Phoenix-based CCG Catalyst, a bank consulting firm providing strategic guidance for financial institutions. For more information, visit the company’s website at

Copyright © September 2011 BankNews Media