Knowing the customer: this time it s personal. How analytics can help banks achieve superior CRM, secure growth and drive high performance

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1 Knowing the customer: this time it s personal How analytics can help banks achieve superior CRM, secure growth and drive high performance

2 Table of Contents Introduction How advanced analytics changes customer engagement Six fundamental factors for CRM analytics success Achieving high performance through predictive analytics Why banks need to integrate analytics enterprise-wide Knowing the customer: this time it s personal

3 With the immediate impacts of financial crisis behind them, banks have turned their attention from cost reduction to growth. Yet even in a recovering economy, growth will not be easy. In mature markets such as Europe and the United States, achieving growth will require banks to develop a deep understanding of customer behavior and preferences, and subsequently target the right products and services, to the right customers at the right time across the entire customer lifecycle. Most would agree that the crisis did not have a major impact on banking customers psyche. Indeed, research shows that customers today are increasingly willing to change their bank or financial services provider in large part because the financial crisis has eroded trust in financial institutions across the board. Even more troubling for banks is that not only are customers more interested in switching, they also have more information about what s available from the expanding pool of both traditional and new competitors. As a result, managing customers effectively is more important than ever. An essential element of building and strengthening customer relationships is the ability to identify opportunities for cross-selling and upselling. But today, simply knowing what additional or upgraded product or service a customer may want is no longer sufficient. Banks also must know when and why customers are likely to want that product or service. In other words, banks must understand their customers across the entire lifecycle and that starts even before a customer has bought a single product. How can banks achieve such an understanding? The answer is advanced analytics. By advanced we do not mean the reporting analytics that banks have had and used for some time. Rather, we refer to the new real-time and predictive capabilities that are instrumental in achieving high performance. Advanced analytics can tell you more than simply where you have been. They can help you understand where you are going and, critically, exactly how you will get there. Predictive and real-time analytics offer banks the opportunity to transform their approach to customer relationship management (CRM) and, in the process, generate greater value and grow more profitably. 3

4 How advanced analytics changes customer engagement CRM spans the entire customer lifecycle from preacquisition through termination and reacquisition. Analytics can play an important role at every point of this lifecycle to help a bank achieve greater efficiency and continuity, as well as manage risks and revenues, as a customer moves through each stage. For example, a bank s marketing department can use reporting and analytics to identify high-profit market segments. The marketing professionals work with loan officers who identify appropriate product offerings tailored precisely for the needs of this segment and use analytics to prequalify customers for the loan. The advertising department uses response data to determine the most appropriate channel to reach this segment. The result? A high-profit customer is prequalified for a product that he wants or needs and is offered the product via a channel that he prefers. Analytics also can help banks spot critical events in a customer s life that may indicate a change of circumstances and the need for new products or services. This extends beyond simple lifestyle profiling to looking at real changes in behavior and specific events in a customer s life for example, a job promotion, the birth of a child, or a child leaving the family for college Integrating knowledge of these events with an accurate analysis of customer profitability can enable a bank to target the appropriate crosssell and up-sell activities at the right time. A bank that uses a conventional approach to CRM may well overlook these revealing details and, thus, miss these valuable cues that could suggest opportunities to present relevant offers to customers. Consider the hypothetical situation of James King, a 53-year-old executive. His children have completed college recently, and James decides it s time to treat himself to the European sports car he s always wanted. At the dealership, he takes out a loan for the car with a bank. While James has no existing relationship with this bank, the details he provides on the credit application form combined with information on James the bank has from other external sources indicate that he could be a valuable prospect for a number of different offerings. Several months after James purchases his new car, he makes a larger and earlier payment than his loan agreement stipulates. The bank s analytics engine takes note of this and routes the information to the right customer contact representative, thus setting in motion a chain of actions that make full use of all the information that the bank now has. Presuming James s payment suggests James may have recently benefited from an influx of cash, a salesperson from the bank calls James to discuss a number of wealth management options which may be of interest to him. It turns out that James, indeed, has been looking at investment choices for a bonus he s due to receive, so the salesperson sets up a meeting with one of the bank s specialist advisers. In this scenario, 4 Knowing the customer: this time it s personal

5 analytics turns what could have been a routine automobile financing deal into a potentially long and much more profitable relationship. In Accenture s experience, banks can benefit from predictive analytics in a number of ways. Analytics can help banks: Apply segmentation and rank-order customers during the pre-acquisition phase. Banks can model a wide range of demographics and variations in attitudes and behavior to identify appropriate prospect/customer segments and target the right products/offers. Reduce costs through more effective and efficient target marketing. Using analytics effectively, a bank can help increase the relevance of communications and offers to create contextual and personalized communication at the right time for every customer. Apply predictive models to credit and risk score accounts to improve credit risk underwriting, increase speed to decision and reduce bias in decision-making. Apply logistics analysis and forecasting to the acquisition process to effectively manage the workload of boarding new accounts at the time of acquisition. Analytics can drive superior customer management processes to ensure consistently high customer experience. Use sampling to identify and manage champion/challenger treatment and offer strategies for satisfaction, cross- and upsell, and retention. More granular and timely insights offer enhanced capabilities to respond to or anticipate rapidly changing customer circumstances and requirements. Apply refreshed segmentation and predictive models to manage portfolio strategies including increase, decrease or termination of services. Analytics can create real-time insights that drive a dynamic portfolio management strategy to actively manage possible customer attrition. Effectively manage reacquisition strategies based on modeling that identifies accounts that are worth reacquiring and prioritizes treatment accordingly. 5

6 Six fundamental factors for CRM analytics success To be sure, analytics is a powerful tool that has the potential to substantially improve a bank s revenue stream, market share and overall profitability. Banks seeking to use sophisticated analytics to improve business performance should consider six factors that are critical to the development of analytics capabilities. Provide strong stakeholder governance It s imperative that the right CRM stakeholders are involved from the outset in the development of analytics frameworks and identifying the right questions to ask. These stakeholders should include all lines of business and the support functions (information technology, finance, marketing, and human resources, for instance) so that all the appropriate and desired decision- support requirements are captured from the outset. As part of governance, banks should ensure they address not only the business problems they want to solve with their analytics capabilities, but also the inputs (data, systems of record, methodologies, roles and responsibilities) and the outputs (analysis, reports, roles and responsibilities, etc.) of the analytics process. While stakeholder governance is a foundational stage, in practice it is frequently missing. Know where the data are Knowing where all the required customer and product data resides across the bank, and creating an efficient and effective single repository to aggregate that data for analysis, is critical to avoiding duplication and inefficiency. Have the right tools and people Using analytics to solve the stated business problems requires both sophisticated technologies that enable a bank to conduct advanced customer and behavioral modeling, and the right mix of technical and business analysts who understand the appropriate analysis techniques and how and where to apply them. Embed in processes To be truly effective, analytics capabilities cannot stand alone in the organization. Rather, they must be firmly embedded in key business processes so that insights they generate can be disseminated throughout the enterprise, particularly to the key decision-makers who drive strategy and revenue. Use in all decision-making One of the essential elements of analytics is that it can tell an organization why things are happening, not simply what is happening. Such insight can be invaluable to management in making its day-to-day decisions and setting priorities. Thus, it is critical that these insights are available to decision makers whenever and wherever they need it. 6 Knowing the customer: this time it s personal

7 Establish and maintain feedback loops Analytics is a journey, not a destination in its own right. Thus, it s essential to ensure that there is a formal mechanism in place that enables a bank to learn how analytics is helping the organization and where refinements are necessary to improve the information that is delivered to decision makers. 7

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9 Achieving high performance through predictive analytics As the effects of the financial crisis and resulting recession ease and banks begin refocusing on growth, it is apparent that business as usual is not an option for financial institutions. The customer and competitive landscape has changed so fundamentally in the past few years that banks truly must rethink how and from where they will generate future revenues. And that rethinking necessarily includes banks relationships with customers. Banks must do a much better job of getting in tune with what customers and prospective customers want when they want it and provide relevant solutions to customers at the most opportune time. In Accenture s view, predictive analytics is a powerful tool that can help banks achieve that goal. By developing and using sophisticated analytics capabilities, banks can generate the insight necessary to help build the closer, more enduring, and more profitable customer relationships that are key to achieving high performance in a recovering global economy. 9

10 Why banks need to integrate analytics enterprise-wide Advanced analytics may start as pockets of expertise and activity in one part of a bank, but the sooner they spread across the entire enterprise, the better. That s because they enable all parts of the enterprise to work together to create maximum value while minimizing duplicative efforts and maximizing the consistency with which customers are engaged and treated. Integrating analytics across the organization enables banks to: 1. Create a complete customer profile to develop an end-to-end sales and service strategy for every individual. 2. Address customer needs either in direct response to an event or, through predictive analytics, in anticipation of a development. 3. Understand the precise price levers for every customer at every point of interaction. 4. Operate a clearinghouse of customer data to ensure that customers receive tailored, relevant and coordinated offers for new products and services. 5. Make optimal use of analytic resources by understanding where they deliver the highest value. 6. Maximize shareholder value by understanding the requirements of current and potential revenue streams alongside a detailed picture of the costs associated with acquiring, managing and losing those revenues. 10 Knowing the customer: this time it s personal

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12 Copyright 2011 Accenture All rights reserved. Accenture, its logo, and High Performance Delivered are trademarks of Accenture. About Accenture Analytics Accenture Analytics delivers the insights that organizations need to make better business decisions, faster. Our extensive capabilities range from accessing and reporting on data to predictive modeling, forecasting and sophisticated statistical analysis. We have more than 20,000 analyticsskilled people with deep functional, industry, business process and technology experience. At the intersection of business and technology, Accenture Analytics enables organizations to achieve the business outcomes that drive high performance. For more information about Accenture Analytics, visit About Accenture Accenture is a global management consulting, technology services and outsourcing company, with approximately 236,000 people serving clients in more than 120 countries. Combining unparalleled experience, comprehensive capabilities across all industries and business functions, and extensive research on the world s most successful companies, Accenture collaborates with clients to help them become high-performance businesses and governments. The company generated net revenues of US$25.5 billion for the fiscal year ended Aug. 31, Its home page is