MAKING CUSTOMER PROFITABILITY WORK FOR YOU

by Kim Sutherland, Director, Market Line Associates

Much has been written about Account and Customer Profitability in the financial services industry over the past 5-10 years and many myths exist about both the process and the uses of the results. The purpose of this article is to provide you with some guidelines about what is considered to be important in an account and customer profitability valuation. In that manner, you can use these guidelines to compare your own efforts to date. And, you can use them as a template for the best next steps.

Profitability Evolution

The first efforts with regard to profitability, other than overall bank profitability, occurred in the 1960s and early 1970s when organizations began evaluating organizational profitability. They were able to look at various parts of the banking business and evaluate where the profits were coming from within a given organization.

In the latter part of the 1970s and the early 1980s, companies began to focus on product profitability. While manufacturing concerns had been conversant in product profitability for years - especially process costing; it was a fairly new paradigm for service industries. Mellon Bank in Pittsburgh, PA and Wachovia Bank in Winston Salem, NC were among the pioneers in the development of product profitability for the banking industry.

It wasn't until the late 1980s and early 1990s with the advent of customer databases, formerly known as MCIF (Marketing Customer Information File) systems, that attention to account and customer profitability came to the forefront. The notion that some customers were contributing more than others to the bottom line (perhaps regardless of their balances) seemed intuitively correct. Additionally, the desire to target marketing efforts to households rather than to individuals supported the notion. However, the ability to accurately create information at the account and customer level that could be supported by bank financials was lagging far behind the desire to have it.

Current Situation

Although there are still more institutions talking about customer profitability than actually have it, more and more banks are attempting to have this information readily available. Unfortunately many have spent millions of dollars only to be very unsatisfied with the results.

Barriers to Success

We have found that key barriers to a satisfactory solution include the following:

Not knowing what components truly drive better profitability valuations. This means you don't know where you can make compromises without diluting the value of the output.

Partnering with an inexperienced vendor. Most of them don't have more than 3 customers actively using their profitability modules let alone clients that are pleased with the process and outcomes.

Lack of commitment within the organization to get to the "right" data. The devil is truly in the details. It's worth spending a little time to "get it right"

Thinking you can make a list of fields needed to calculate profitability and be done with it. Every institution is dealing with its own universe of available information. It's far more productive to start with what you have than to ask for something that might not exist.

Understanding that it is a "process" and an ongoing effort and not a one-time project. This impacts not only the FTEs within the organization necessary to support such an endeavor, but also the amount of support you can count on from other areas of the bank that will be affected.

Thinking you can simply publish the information and that it will find its way into the sales efforts of contact staff. There's no point in sharing the information unless you are prepared to instruct people in how they should be using it and be prepared to answer their questions.

Fields You Want to Include

The important thing to remember in beginning this process is to gather as much information at the account level as you can. Every distinction you can make instead of allocating things in an ordinal fashion across groups of accounts will enhance your ability to make better distinctions at the account level. The table below details some key items you want to gather into your database/data warehouse for input into the profitability valuation Sample Account-Level Data Elements

It is also important to understand how you might use the information. The best way to maximize the uses of the information is to also includes fields by which you will review the profitability output - "slice and dice" fields, if you will. Listed below are basic data elements you would also want to include in your database/data warehouse to facilitate analysis.

Sample Account-Level Analysis Elements

Banks that have begun this process know that gathering the information is not necessarily a guarantee of success. To assist you with avoiding some of the barriers discussed earlier, and to support your own efforts, we have constructed a template for the successful implementation of account and customer profitability.

Template for Success

To assist you with avoiding some of these problems and to support your own efforts, we have constructed a template for the successful implementation of account and customer profitability.

1. Team Approach and Sponsorship. The project must have a champion. This may not necessarily be the CEO, but it should involve at least the head of retail or commercial banking. Additionally, there must be someone within the organization whose primary job will be the successful completion of your first conversion and the monitoring of ongoing monthly efforts thereafter. The team should include representatives from the area where the output information will reside, as well as, finance, systems, line management, and marketing.

2. Data Manipulation. There are several components to data manipulation; they include but are not limited to: data sources, data extracts, data quality review, formula development, formula maintenance, default values, and output needs - both electronic and hardcopy. As valuations become more sophisticated, the number of data feeds and extracts increases, as does the expertise required to manage the data. There are no easy answers here - but focus on data quality testing improves the process.

3. Transaction Files. Most state-of-the art valuations today include transaction files for both assets and liabilities. While the asset transactions have been less important until recent years, they are extremely important as a source of fee income and the use of various channels for payments. Additionally, they provide much more detailed information for the creation of a higher-level valuation for mortgage customers. It is also important to know the source of each transaction in addition to the account that has the transaction. In this manner, branches that service more customers than others can be identified. Most institutions also mine this transaction data to discern key customer behaviors. Most often transaction data is also used to support efforts in finance. This provides a high degree of synergy whereby the volumes captured by the profitability project can be used to support finance and the unit costs developed in finance can support the profitability project.

4. Account-level Data Assumptions. The best valuations today include the following all executed at the account level: marginal maintenance or servicing costs, transaction costs by channel, fees and fee reversals, funds transfer pricing assignment, opening/origination costs, multiple levels of risk (interest rate, credit and operating), capital and liquidity assignments, fixed costs, and overhead. This should translate into having multiple "levels" of profitability available for use. This is important because different types of post-calculation projects require different views of profitability. At a minimum, your valuation should include Net Contribution, Net Income Before Taxes (NIBT) and Net Income After Taxes (NIAT). Many others also calculate Net Income After Capital Charge (NIACC) and an ROE.

5. Data Quality and Reconciliation. State-of-the art projects include multiple data quality review checkpoints. It's far easier to check the data being supplied to the valuations than it is to find the anomalies after profitability has been calculated. We have found that it is not unusual for as much as 15% of the data elements to "shift" in a given month. Most of these shifts necessitate formula revisions in the current month, as well as returning formulas to their original state for the next valuation. Most anomalies are not permanent, however, most anomalies do not involve the same fields from month to month.

Additionally the valuation must reconcile to the known institution financials. Most institutions set an acceptable target with a + or - range. If the output of basic number of account, balance, income and expense information falls within this range, the valuation is considered to be reconciled.

This does not obviate you from testing outbound account and relationship values. While many items look okay "in total" there may be quite a bit of distortion at the account level. Due diligence must be done on this output, especially if you are sharing account level output with customer contact areas.

6. Smoothing Information. It is important that account and customer profitability information be "smoothed" for more than one time period before it is used. Several years ago, and even today, many consulting firms support a 12-month period as being the best. However, we have shown that this time period is too long to support a useful understanding of customer relationship values. Especially in the case of deterioration, the customer is long gone before the institution has the opportunity to reestablish the previous relationship. Today most progressive institutions smooth the information over a 3-month period. They may then utilize four 3-month periods at the account level - providing them with the same 12-month view, but allowing them to capture and respond to relationship shifts in a timely fashion. Most importantly you should understand that an revenue model, such as rate times balance, risks misclassifying customers by 40%-50%, nearly a random event!

7. Using the Information. The fastest way to gain acceptance within the organization is to know how you intend to use it. Many will be waiting with great anticipation to incorporate customer profitability into their initiatives - others however, will not be so receptive. It is important to not only understand the "personality" of your organization but also to understand the "perceptions" of your potential audiences. Relationship managers and loan officers will love having more accurate ways to evaluate the pricing of current and future bank relationships, but only if they believe the value includes "everything".

• Product managers will have access to better information than they've ever had, but it has to be timely and easy to get to.

• Call centers and branch personnel will be more likely to use the information if it's kept simple and straightforward. Additionally, they will need to understand how they can use the information if it is to be helpful to them. Don't incent volume increases or cross-sell, for example, if what you really want is increased relationship profitability.

8. Aggressive Integration Into Strategic Initiatives. Most institutions have 2-3 immediate applications of customer profitability information. These initiatives typically include:

• product realignment evaluations (especially in organizations growing through acquisition), product design or retooling,

• relationship product development and relationship pricing efforts,

• preferential customer efforts,

• segmentation and target marketing,

• direct mail target selection,

• promotional review (comparing new business to the overall portfolio),

• line of business or customer segment evaluations (Small Business, Middle Market, etc.),

• branch closing and opening analyses.

Summary

Customer profitability is not a new concept. However, efficient execution of such endeavors is certainly not a standard yet in the financial services industry. We do know that institutions that prevail and focus on the appropriate process steps and translate the output into strategies and initiatives for their sales forces can achieve as much as a 30% improvement in average relationship value in a 12-month period. Hopefully, some of the concepts covered in this article will help you launch or improve the profitability efforts at your own institution.

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