(Part 2 of a 3-part blog series)
In part one of this blog series, my colleague Roy Berelowitz demonstrated — through the customer’s eyes — why bank and credit union executives should understand the value of their customers/members (hereafter referred to as customers), and the implications of not doing so. In this follow-up blog, I explore how to better identify individual customer value, first by measuring the contribution of each customer to overall institution profitability, and then by assessing the full scope of each customer’s influence. Through these two steps, financial institutions gain a thorough understanding of their customers based on experience and observation — the hallmarks of data-based and sound business practice.
Measuring Customer Profitability
To quantify the profitability of an individual customer, data points that contribute to profitability are required on each account that the customer holds with your financial institution. Profitability calculations should provide the following information for individual customers:
- Net Interest Margin: This typically is the largest component of overall institutional profitability, so it is critical to get this calculation right for each customer. Net interest margin at the account level includes interest income (loans) or interest expense (deposits). It also includes the funds transfer pricing (FTP) rate and corresponding FTP charge (loans) or credit (deposits/shares). A matched-term (also known as “matched-funded”) transfer pricing methodology enables accurate calculation of FTP at the individual account level.
- Non-interest Income and Expense: This metric includes both direct (such as loan officer salaries) and indirect revenues and costs (for example, salaries in Human Resources). Several approaches can be used to attribute revenue and costs at an account level, including an allocation process, unit costing calculations, and/or activity-based costing calculations. Many organizations use a combination of these approaches based on the materiality of each item.
- Provision for Loan Loss (PLL): Typically determined as a percentage of the loan amount based on the loan type and the customer’s risk rating, the PLL can have a significant impact on the profitability of each account, and therefore must be included in profitability measurebment for each loan account.
- Capital: This metric enables the institution to apply a capital charge/credit or to determine a return on capital based on the amount of capital assigned to each account held by a customer. A best-practice approach to capital allocation uses an economic capital framework to allocate capital based on the risk profile of each product in the bank or credit union. The resulting risk-adjusted return on capital (RAROC) metric is a better indicator of each account’s performance than a pure profitability measure.
Accounting for each of these components enables the institution to then analyze profitability at the account level, as well as any aggregate level, including customer and relationship.
Assessing the Customer’s Scope of Influence
In some cases, this next step is even more critical than the first in understanding the full value a customer brings to the financial institution. A quick example will help illustrate this scope of influence; the following describes just a small portion of the institution’s relationships with ABC Healthcare, a business client:
- ABC Healthcare is a local medical practice. The practice has a business checking account, a commercial equipment loan, and a line of credit.
- Three of the five partners in the practice also are customers of the institution.
- Two of these partners each has a checking account and a savings account
- The third partner is Jane Smith.
- Jane and her husband have two daughters, both in college. Jane Smith and her husband have checking and savings accounts, a credit card, and a mortgage. Each of Jane’s daughters has a checking account, a student loan, and a credit card.
- Jane Smith is also the chairperson for a local hospital’s board. The hospital has a business checking account, a commercial real estate loan on its building, and a line of credit.
Is ABC Healthcare’s importance to the institution determined only by its direct business accounts? Certainly not! Does the profitability of these accounts alone accurately define the value of its relationship with the institution? The practice clearly has a wider scope of influence, with other partners and employees who might have similar networks. Defining and quantifying these relationships are a critical part of profitability analysis in the financial services industry. By mapping all of these relationships, and then aggregating the profitability to a total relationship level, the institution gains a complete picture and understanding of the value of their relationship with the practice. This understanding should inform how the practice and related customers are handled institution-wide.
Managing this process of defining groups of related accounts in the financial services industry has several names, including “householding,” “super-householding,” and “relationship management.” Householding typically refers to the retail side of the business, where customers that share a single domicile are grouped together. Full “relationship management”, or “super-householding” is typically related to commercial accounts where an individual’s business network is accounted for in their scope of influence.
Loan officers/relationship managers, marketing staff, and information technology personnel typically own the creation and maintenance of broad, networked relationships. The mechanism is to connect these relationships is a unique relationship identifier (ID) for each group of accounts comprising a total relationship. The ID applies to immediate and obvious relationships, such as spouse and children, but also to extended relationships, such as business partners and their families and others. Most often, relationship IDs are stored in a financial institution’s core system or marketing customer information file (MCIF).
A robust profitability tool can identify and quantify all profitability metrics described earlier at the individual customer level, and aggregate these at the network/relationship level to help inform broader customer interactions.
The next step is using this information to improve customer experience at your institution. In other words, bringing profitability analysis from the back office to the front lines. The third and final blog in this series, “Know Your Customers Empirically: Value-Based Execution,” will explore considerations and approaches for using profitability information to enrich customer interactions.