How Banks Can Use Customer Profitability Analytics to Thrive in Uncertain Times

Transcription

1 How Banks Can Use Customer Profitability Analytics to Thrive in Uncertain Times An Executive Brief Sponsored by IBM

2 Stratecast Frost & Sullivan HOW BANKS CAN USE CUSTOMER PROFITABILITY ANALYTICS TO THRIVE IN UNCERTAIN TIMES INTRODUCTION Most banks have an idea of which customers are most valuable. Or, rather, they have many ideas, with each department using various criteria, metrics, and rules of thumb to assess and nurture its own account base. Thus, for example, branch managers may value customers with multiple retail products (credit card, checking account, certificates of deposit). The trust department may focus on high net worth individuals. Lenders gravitate toward proven borrowers. However, value should not be a subjective measure. As banks watch their margins dwindle, there is only one measure of customer value: profitability. And not just current profitability, but profitability over the long term. A bank that builds its business around consistent and accurate measures of customer profitability is armed with the data it needs to make smart decisions decisions that help it lower costs, enhance operating efficiencies, and increase revenues. This is the domain of Customer Profitability Analytics, a field of analytics that utilizes sophisticated data modeling to deliver customer-level intelligence that can be used to make smart business decisions. Using predictive and prescriptive analytics, Customer Profitability Analytics solutions provide a cohesive, bank-wide view of each customer, their current and lifetime profitability, and their likely behavior in response to various situations. The results enable the bank to respond more quickly to regulatory or market changes, and ensure that all departments are working toward a common goal. The challenges in the current banking environment call for a new, data-driven way of doing business one that captures a common and useful view of customer profitability. In the new world, tools and metrics that have been in place for decades are no longer sufficient to identify which customers are profitable, and (more importantly) are likely to remain so. Nor can they adequately predict which customers represent an opportunity for additional revenue, or the potential lifetime value of any given customer. In this white paper, Stratecast defines Customer Profitability Analytics. We show how banks can benefit from adopting a profitability-driven approach. Finally, we examine the relationship between profitability and customer satisfaction, for banks that are looking to balance the two Stratecast. All Rights Reserved.

3 How Banks Can Use Customer Profitability Analytics to Thrive in Uncertain Times DEFINING CUSTOMER PROFITABILITY ANALYTICS Customer profitability analytics is a type of data analytics designed to provide insight into a customer s current and potential value to the bank. A robust profitability analytics solution takes data about costs and revenue from multiple sources, including financial systems, customer relationship management systems, transaction databases, social networking, and marketing tools. It applies sophisticated algorithms that sort the data, identify patterns, and model alternate scenarios. For banks, a Customer Profitability solution enables them turn the data they are already collecting into intelligence (what does it mean?); and then into practical and meaningful action (what should we do?). Thus, customer profitability analytics allow the bank to determine: which customers are most profitable today which are likely to be the most profitable over the long term (lifetime value) which can be made more profitable by increasing their revenue and which can be made more profitable by decreasing the cost to serve them. This knowledge can, in turn, drive specific actions related to customer service, product development, pricing, and marketing efforts. For example: Less profitable customers can be driven to a less costly channel, through education, incentives for switching, or fees for not switching. Highly profitable customers identified as likely to balk at a new fee can be offered a waiver or other incentive to stay. Customers with lower profitability ratings will not be offered such an incentive. Customers identified as up-sell candidates will receive consistent and relevant offers across every interaction, including account statement inserts, tellerengaged transactions, and outbound marketing efforts. HOW DO CUSTOMER PROFITABILITY ANALYTICS SYSTEMS WORK? Customer Profitability Analytics systems generally involve three types of analytics engines: Profitability Calculator Using best practice management accounting methods (Funds Transfer Pricing, Risk based Capital allocations, and both activity-based costing and expense allocation), the system calculates profitability across multiple dimensions: by customer, by account, by product, by channel. The 360-degree view of profitability ensures that every department shares a common understanding and view of the factors that contribute to customer profitability Stratecast. All Rights Reserved. 3

4 Stratecast Frost & Sullivan Predictive Analytics The system derives the lifetime value of a customer. It also enables users to model customer behavior based on input scenarios. How many, and which, customers will leave if minimum balances are raised? Will a new prepaid debit card product generate enough users to be profitable? Business Intelligence Through data mining and analysis, the system delivers insights that each line of business can use to make better business decisions. Business Intelligence reporting provides users with profitability data that is based on a common view of the business, but relevant to their specific roles. Access to this information enables business users to make decisions based on facts. For all banks, it is important that the data output be accessible and usable to line of business managers. Thus, it is worth investing in a Customer Profitability Analytics system that offers easy to use dashboard reporting that enables senior executives to quickly assess profitability per customer, account, product, and channel. Trending charts should trace improvements over time, based on specific activities (e.g., introduction of a new product or launch of an advertising campaign). Executives and other stakeholders should also be able to build and test scenarios through a simple common-language user interface. The interface should be designed to hide the analytics engine, so that non-technical users can easily find the information they need to do their jobs, without going through IT. WHY NOW? THE URGENCY OF TRANSFORMING INTO A PROFITABILITY-DRIVEN ORGANIZATION It s a new world for the once-staid banking industry. Globally, the banking industry is facing a dizzying onslaught of profit-sapping market conditions and regulatory constraints. As economies tighten, more loans default, causing banks to suffer loss of revenue, leaving less revenue available to lend to a shrinking pool of eligible borrowers. The current regulatory environment is particularly inhospitable for banks. In the U.S. and Europe, following bailouts of failing banks, governments have stepped up oversight and imposed new restrictions and regulations. These include tighter credit rules (designed to protect shareholders from risky loans); limits on bank and credit card fees (designed to protect consumers); and greater equity ratio (designed to protect against highly leveraged loans). In the U.S., American Banker has called the regulatory environment no less than an assault on bank profitability. Furthermore, industry consolidation remains very much a factor, with smaller banks continuing to be absorbed by larger competitors. For regional banks that want to stay independent, this increases the pressure to produce profits that shareholders will find acceptable. For banks that are actively seeking a buyout, profitability measures can mean the difference between hefty payouts and a fire sale. At the same time, new revenue opportunities are being created. Banks are spearheading Stratecast. All Rights Reserved.

5 How Banks Can Use Customer Profitability Analytics to Thrive in Uncertain Times innovations that are upending the very concept of money. Technology has introduced new and cost-effective ways to interact with customers, including Internet and mobile banking. Electronic bill pay and debit card transactions are lowering operating costs while immersing banks more deeply into their customers daily lives. Banks are just beginning to understand the impact of such enhancements on customer profitability. The market conditions impact all banks; yet, none feel the effects more than mid-sized or regional banks. Regional banks are held to the same regulations as the global behemoths with whom they compete for the same local customers. Yet, their smaller size means they have always operated leaner, with fewer staffers and less specialized expertise. In a smaller bank, it is more difficult to reapportion budget to fund a new initiative or respond to a new regulatory requirement. And it is much more challenging to protect and replace revenue sources lost to competitors. And yet, this is exactly the right time for regional banks to transform their operating models. In an environment in which so much is beyond the control of the banking industry, in which customers have more banking options, and in which first-to-market technologies may prove important to competitive success, regional banks need to reevaluate how they invest their budget and energy. The best way for any bank to be prepared for change is to be armed with useable data. WHY THE OLD PROCESSES NO LONGER WORK IN THE NEW BANKING ENVIRONMENT Without customer profitability analytics, banks don t know enough about their customers or about the ideal customer to make smart investment choices. Without a common and stringent profitability metric to guide them, banks are left with inconsistent and informal assessments even gut feel to make their most important business decisions. Banks may find themselves in the following situations: Problem: Departmental objectives are misaligned with customer profitability. Chances are that sales teams are measured on products sold. Customer service teams may be measured on customer satisfaction ratings. Marketing objectives are likely tied to campaign results. In fact, it is possible for every department to achieve or exceed its objectives, even as bank profits decline. With the right Customer Profitability analytics system, everyone in the bank has a shared view of the customer, and a shared notion of profitability and individual and departmental objectives can be aligned. Problem: Marketing efforts may or may not be effective. Marketers are familiar with retailer John Wanamaker s alleged lament, Half the money I spend on advertising is wasted. The trouble is I don t know which half. For bank marketers, the downside risk is greater than simply wasted budget: their marketing efforts may be attracting customers that end up costing more than they bring in. Without Customer Profitability analytics to provide a clear sense of what a profitable customer looks like, marketers are unable to target their efforts to ideal customers Stratecast. All Rights Reserved. 5

6 Stratecast Frost & Sullivan Problem: The bank is uncertain how to respond to aggressive competitive moves. Suppose a competitor announces a product you don t offer, such as no-fee checking? Suppose a new bank moves into your neighborhood, promising the lowest auto loan rates in town? Suppose a formerly quiet credit union engages its marketing muscle? Without Customer Profitability analytics, banks cannot adequately predict how their customers will respond or how their revenue will be impacted. Nor can they determine what (if any) counter-steps should be taken. Problem: Potential new regulations that may cap certain fees or restrict interest rates. Many regulations limit banks arsenal of revenue tools, and impose additional costs associated with compliance. Without Customer Profitability analytics, banks may take months to return to profitability. In contrast, a profitability analytics system enables the bank to test multiple scenarios long before the legislation is passed; for example, determining if other fees or products fill the gap. Thus, as soon as new rules are announced, instead of scrambling to replace the revenue, the bank can smoothly transition into a new business plan. THE RELATIONSHIP BETWEEN CUSTOMER PROFITABILITY AND CUSTOMER SATISFACTION In any service industry, customer satisfaction is an important business driver. This is especially true in regional or community banks, which often depend on their friendly, service-oriented approach to compete against the perceived impersonality of large banks. Regional banks often use satisfaction as a proxy for profitability. The thinking goes like this: A satisfied customer is likely to be a loyal (long-term) customer. Management theory has long held that customers are more profitable over time, as higher revenue offsets acquisition costs. Thus (the logic goes), the more satisfied the customer is, the more profitable it is, and will become. Unfortunately, the logic does not capture the complexity of current banking. In 2010, American Banker looked at the performance of banks ranked at the top of the J.D. Power customers satisfaction survey, and discovered that more than a quarter of the banks rated number one in customer satisfaction in their regions operated at a loss in some cases, totaling millions of dollars. In contrast, the three largest banks in the U.S. ranked below average or even last in the J.D. Power survey in their regions. Articles, like that in American Banker, support the rising belief that customer satisfaction and profitability are incompatible a situation Forbes ascribed in 2012 to the Bizarro world of American banking. The Forbes article captured many customer fears and frustrations with the banking industry, particularly that customers will end up with the short end of the deal. Yet, the belief that satisfied customers are unprofitable is as useless as the belief that satisfied customers are profitable. In fact, satisfaction is only one contributor to profitability. Furthermore, no bank should be using generic or industry-wide trends as a basis for decisions involving individual customers Stratecast. All Rights Reserved.

7 How Banks Can Use Customer Profitability Analytics to Thrive in Uncertain Times Consider these satisfaction-related examples: A senior citizen visits her local bank branch regularly to deposit checks and withdraw cash from her small savings and checking accounts. She is on a firstname basis with the tellers, who greet her warmly and offer her a cup of coffee. This is a very satisfied customer. And yet, because of her frequent use of the most expensive channel, the unlikelihood that she will purchase more services in the future, and the limits to her long-term patronage, a profitability analysis may well show this valued customer may be among the bank s least profitable. A college student has moved out of state, but retained his student checking account. His paycheck is directly deposited into a checking account, from which he withdraws money via debit card or ATM. He also has a small loan, co-signed by his parents. The student has never responded to the annual customer satisfaction survey. As an out of stater and a student account holder, this customer is not considered to be a loyal or particularly satisfied customer, and, therefore, is not included in any retention or up-sell programs. However, a profitability analysis may show that, like many young people, this customer is very comfortable maintaining a banking relationship strictly through the Internet. He is comfortable with the bank, and has no plans to look for another. Furthermore, as he moves beyond college into the workforce, he is a good candidate for a credit card; and even a mortgage, down the line. A small business customer balks at a new requirement to provide collateral for a previously unsecured loan. The business has taken to social media to blast the bank s ruthless loan practices; and has told the loan officer that he will take all his business and personal accounts to a competitor. A profitability analysis might indicate whether the threats are likely to be carried through, and also provide a basis for the bank to determine how hard it wants to work to keep the customer. In each case, a customer profitability analytics system could have assessed the short- and long-term profitability significantly more accurately than any rules of thumb. The system would have ensured that each customer received appropriate treatment across all bank channels (marketing, branch, care). Furthermore, it must be pointed out: Customer Profitability Analytics does not assume that profitability is the sole driver of bank actions. As part of their mission statements, community banks often assume responsibility for serving and investing in their communities. Thus, the bank may choose to continue to offer hightouch (high-cost) or low-revenue banking options for customer segments that contribute to its community leader perception; for example, special products for senior citizens, children, or local businesses. The key is that profitability analytics provides the bank the data it needs to understand the cost of such decisions. A well-informed bank can make smarter decisions, for the short-term and the long-term Stratecast. All Rights Reserved. 7

8 Stratecast Frost & Sullivan Stratecast The Last Word Saddled by shrinking margins, increased regulatory oversight, and declining customer loyalty, regional banks are facing tough times. Banks that have always competed against much larger institutions on a customer service platform are seeing their profitability impacted in a way that threatens survival (at least as an independent bank). Do midsized banks need to choose between profitability and customer satisfaction? The answer is: until they can accurately identify their profitable customers, they have no way of knowing. Customer Profitability Analytics enables banks to take what they know (data about customers, accounts, products, and transactions); apply costing models (activity-based and allocation); to determine a single, bank-wide view of profitability on a per-customer basis. Furthermore, by applying predictive analytics, they can derive a lifetime value for each customer; and even model likely behavior in hypothetical situations. For a midsized bank, with limited staff and budget, Customer Profitability Analytics can transform departmental operations from best effort to laser-like efficiency. Branches, sales, and loan officers will all share a common view of the customer eliminating inconsistent or even counter-productive efforts, and ensuring investments yield the desired results. Finance will have a consistent source for key performance metrics, including cost of revenue, loan yields, and return on equity. Customer service teams will be able to handle customers in a way that reflects their value to the bank: with exclusive phone queues or special offers for the most profitable customers. Marketing will be empowered to attract not just any customer, but the near-ideal customer. In this environment, banks have the tools at hand to deliver customer service profitably. They have the data and modeling tools to understand each customer s satisfaction threshold and tolerance level, based on likely response to a variety of scenarios. Furthermore, they can make an informed decision as to which customers satisfaction is most important, and take appropriate action. In a highly regulated, complex and competitive industry, knowledge is power. For midsized banks, Customer Profitability Analytics provides the knowledge they need to thrive. Lynda Stadtmueller Program Director Cloud Computing Stratecast Frost & Sullivan lstadtmueller@stratecast.com Stratecast. All Rights Reserved.

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