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An Oracle White Paper August 2012

“Know Your Customer”: Getting Serious about Unlocking Customer Insight

Know Your Customer: Getting Serious About Customer Insight

Executive Overview ........................................................................... 2 Introduction ....................................................................................... 2 Understanding Pain Points ................................................................ 4 Redefining the Customer Insight Vision ............................................. 7 Unlocking Insight ............................................................................... 7 Conclusion ........................................................................................ 9


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Executive Overview

Today’s financial services organizations covet customer insight and understanding like never before. It represents the key to growth and profitability in an industry increasingly saddled with a more stringent regulatory environment, as well as diminished product differentiation and more limited fee-based revenue opportunities. Financial services institutions (FSIs) have spent countless hours and millions, if not billions, of dollars attempting to attain a comprehensive view of the customer ― whether retail, commercial or institutional ― only to find that a single view on its own offers an absolutely necessary, but only partial solution.

The industry is now earnestly turning its attention to gaining the analytical capabilities that represent the final mile in the quest for an accurate and complete understanding of the customer and his or her total relationship with and value to the organization. Only then is the organization in a position to truly capitalize on its customer relationships to reduce risk, deliver outstanding service and grow profitably.

Introduction

The key to success in today’s financial services market can be summed up in three simple words…“Know your customer.” It is a perfect adage for today’s environment in which longstanding practices and realities are melting away to reveal a transformed landscape where opportunities are abundant, but often more obscured. In this new environment, customer insight is not only important, but imperative.

FSIs are being buffeted on many fronts. They face expanded and increasingly stringent regulatory requirements, as well as increased uncertainty, that are driving up compliance costs, and in many cases restricting fee-based revenue. Advances in technology enable FSIs to launch competing offers in a shorter timeframe, thereby curtailing product differentiation and eroding many institutions’ competitive edge. At the same time, traditional enterprises face competition from new and non-bank players, with alternate products, especially in the payments sector. The cost of doing business, and acquiring customers, is also escalating, spurring an unprecedented focus on customer relationship management (CRM) and retention…especially for the “right” customers. The challenge for many institutions is identifying those very customers.


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FSIs have been focused on achieving a 360-degree view of their customers from a CRM perspective for more than a decade. Typically this involved gaining visibility into the customer across various product lines. This understanding is essential, but it only goes part way, failing to deliver a comprehensive understanding of the customer in terms of:

• Engagement across channels and lines of business

• Profitability based on multiple dimensions, such as by product, industry, geography and other segmentations

• Expense

• Performance

• Growth potential

• Risk across many dimensions

Despite an amplified focus on the customer, many financial services organizations are struggling to extend customer insight. In most cases, it is not for a lack of data. In a recent Oracle study, “From Overload to Impact: An Industry Scorecard on Big Data Challenges1

1 “From Overload to Impact: An Industry Scorecard on Big Data Challenges, Oracle, July 2012.

,” C-level financial services executives said that their organizations were collecting, on average, 75 percent more data than they were just two years ago. As important, customer information was cited as the area of greatest growth over that time, and the executives said that they expect that trend to continue in the two years ahead.

http://www.oracle.com/us/industries/industry-scorecard-1683398.html

http://www.oracle.com/us/industries/industry-scorecard-1683398.html�


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Figure 1. Preparedness for Data Deluge – FSI Executive View

In the same study, financial services executives were surprisingly candid about their ability to deal with this data deluge. Twenty-five percent of financial services executives gave their organization a “D” or “F” in preparedness to manage the data deluge. Fifty-six percent gave their organization a “C” or below. Only 3 percent of executives gave their organization an “A” in preparedness (Figure 1). These figures are very telling when we consider that customer information was the greatest area of growth.

Understanding Pain Points

Financial institutions face multiple challenges in putting their customer information to work to build stronger relationships, improve return and reduce risk. Not all institutions face the same challenges, but, in general, five key hurdles appear consistently throughout the industry.

• Silos still proliferate. The industry has been battling siloed data for decades and the problem persists. In some cases, siloed environments preclude the creation of even a foundational aggregate customer view. The issue continues to proliferate with the emergence of new channels, as well as growth in cross-channel experiences. Just as vexing, disparate datasets can lead to multiple versions of the truth, depending on which department (finance, risk, line of business (product/marketing), etc.) is looking at the data and via which system. For example, the view of a customer from the CRM system would not typically incorporate a risk profile, performance history or regulatory data associated with Know Your Customer (KYC) requirements – yielding an incomplete, and possibly inaccurate view, of a customer. In such an environment, organizations cannot accurately assess and understand a customer and their relationship and/or potential for the institution, leading to sub-optimal decision-making.


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• Data is inconsistent. Expanding on the point of multiple versions of the truth, metrics across today’s financial institutions are rarely uniform. We frequently find that behaviors and performance are not always tracked across all channels, let alone tracked consistently across the enterprise – a situation that limits accurate insight. Disparate data sets that exist within the bank might not all be refreshed at the same frequency or using data from the same source systems. Some may completely ignore a few data sources leading to inconsistency at a given point in time. For example, finance may have an accurate cost of fund projections on a daily basis while the marketing system refreshes this information every month. The front office might be making decision based on stale data between the two refreshes, while the finance team is looking at these same decisions through a difference lens.


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• Analytic insight is not timely. In Oracle’s “From Overload to Impact” study, financial services executives said that, when it comes to data management challenges, the inability to get timely information to business managers is their greatest frustration. Data is flooding into the enterprise, and institutions are eager to leverage it. Doing so today, however, requires significant manual effort, placing growing strain on already overburdened analyst teams. The situation is about to grow more complicated. As data volume grows exponentially, so does the need for these skilled analysts. According to McKinsey & Company, by 2018, the U.S. could face a shortage of 140,000 to 190,000 people with deep analytical skills, as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions.2

The lack of analyst manpower and limited deployment of tools that put insight directly in the hands of those who need it are not the only reasons that FSIs cannot glean timely insight. Maintenance in the analytical environment can also present challenges – rules around scoring and modeling are hard to maintain and usually people dependent, and predictive models are not continually refreshed.

This becomes even more troubling when one considers that, in the Oracle study, financial services executives, more than executives in any other industry in the 11 industries studied, are most likely to say they are planning to expand their business analyst team but are having difficulties identifying candidates with the proper skill sets. The bottom line is that FSIs are eager to put critical and timely business insight directly into the hands of line of business managers.

• Business processes remain disconnected from analytical insight. Institutional and experiential knowledge – much like the data in today’s FSIs – is siloed in departments, such as finance, risk or the front-office. For example, many front-office business processes continue to be based on “old knowledge,” which refers back to the previous example in which the finance department is reviewing the same project as marketing but with different data. We see little to no integration to front-office and middle-office systems to provide the most recent knowledge to support credit, pricing and offer decisions at the point of customer interaction.

• Business effects are not timely. Many FSIs are focused on, and making some progress in, capturing customer interactions in a timely manner. The real hurdle lies in making these customer

2 McKinsey & Company, “Big data: The next frontier for innovation, competition, and productivity,” http://www.mckinsey.com/Insights/MGI/Research/Technology_and_Innovation/Big_data_The_next_frontier_for_innovation.

According to McKinsey & Company, by 2018, the U.S. could face a shortage of 140,000 to 190,000 people with deep analytical

skills, as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective

decisions.2

http://www.mckinsey.com/Insights/MGI/Research/Technology_and_Innovation/Big_data_The_next_frontier_for_innovation�

http://www.mckinsey.com/Insights/MGI/Research/Technology_and_Innovation/Big_data_The_next_frontier_for_innovation�


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interactions quickly known and understood across the enterprise, so they can be leveraged in operational decisions. For example, during the financial downturn in which conditions changed rapidly, managers in the front-office were often left to make critical decisions based on sheer experience and their gut instead of on insight based on science and data. The ability to translate timely insight into action within the enterprise could have yielded, in many cases, more informed, and arguably more effective, decisions around pricing, risk, products, marketing and other areas of the business. In many areas, this deficiency continues today. At the most basic level, transactional behavior and impact are not rapidly and widely disseminated to all decision points in most institutions today.

Redefining the Customer Insight Vision

Redefined, customer insight must encompass an understanding of an individual customer’s (retail, commercial or institutional) product relationships and profitability – current and potential – risk potential, as well as their demographic/sociographic profile, transactional behavior and channel preferences, which enable the most accurate decisions and proactive targeting regardless of customer touch points. To achieve this goal, organizations must be able to rapidly and effectively analyze the customer and associated data on myriad dimensions. As FSIs rethink their definition of and approach to customer insight, they must also revisit organizational roles and ownership of this important enterprisewide initiative. Traditionally, managing the customer view has been the domain of sales and marketing. Moving forward, many organizations are exploring new options as their approach to customer insight expands. For example, we are beginning to see a growing number of FSIs appoint chief customer officers, a relatively new addition to the C-suite. It is also essential that FSIs pay careful attention to socializing these changes and their new vision for customer insight across the enterprise, not just once, but consistently as the initiative progresses.

Unlocking Insight

The challenges are clear when it comes to a gaining a ubiquitous understanding of customers enterprisewide. FSIs face complex and most often incomplete data gathering and integration. Data is inconsistent and driven by organizational silos, and most products currently in the market are designed to meet the needs of only individual silos. And, analytic outputs are not always timely and are dependent on increasingly scarce data analyst resources.


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Since customer insight is a largely data-driven function, technology can and must play an essential role in the solution. Oracle’s “From Overload to Insight” study revealed that FSI C-level executives appear to know what they need to move forward to better leverage their rapidly growing data stores:

47% More customized systems/applications to meet the needs of their industry 38% Greater ability to translate information into actionable insight 38% Improved tools to collect more accurate information

These same requirements can be applied directly to customer insight initiatives.

Where should FSIs start in looking for a technology solution?

• Industry-specific and comprehensive data model. The first requirement is a comprehensive data model that is designed to accommodate all data sources within the bank, including customer, risk, performance, channel, and marketing. This enables institutions to pre-define critical relationships within the data model, allowing for intelligent rollups. In any business intelligence initiative, the data model can be one of the most expensive and time-consuming parts of the project, especially if built from the ground up. This need not be the case today. With commercial-off-the-shelf solutions, such as Oracle Financial Services Data Foundation, which includes a proven data model purpose-built for the industry, FSIs can accelerate time-to-value and reduce total cost of ownership, while benefitting from vast industry experience and knowledge.

• Unified analytical approach. FSIs require a unified analytical approach that provides the flexibility for custom solutions for individual subject areas without compromising data consistency enabled through data conformity. Analytical applications supporting finance, risk and marketing can co-exist within a unified model, leading to assured data consistency and a true single source of truth. Working with a unified data model also ensures insights from each of the subject areas are immediately available to other departments within the bank to leverage without the need for complex integration.

• Prebuilt and/or flexible integration. Integration issues continue to plague today’s FSIs and complicate customer insight objectives. As such, when considering customer insight solutions, FSIs should seek solutions with pre-built integrations, as well as a service-oriented architecture (SOA), that facilitate essential communication between enterprise performance management (EPM), enterprise risk management (ERM), CRM, compliance/governance and customer analytics solutions.

• Ready-to-use tools. FSIs seek to accelerate deployment and return as revenue is at risk. As such, pre-built and industry-specific reports and dashboards and analytic models that address critical strategic analytic needs across customers, performance, product and channels, not only jumpstart rollout, but also provide comprehensive and pre-tested templates built by domain experts. They are not left to go it alone. Essential tools should include pre-defined attrition, cross-sell, up-sell and propensity models, along with customer lifetime value predictions. Also important are performance reports across key dimensions, such as customer segments, products, time and organization; pre-


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built campaign response and performance monitoring capabilities; and channel performance analysis.

• Ability to operationalize and automate. The customer insight challenge involves not only defining processes and metrics but also measuring them. As such, FSIs require solutions that enable them to operationalize customer insight processes – defining them so as to make them distinguishable and measurable – and automate them to ensure rapid delivery of information when and where it is needed.

Conclusion

The financial services industry is evolving, and so are its customers. The key to providing better service to customers – ultimately ensuring profitability – lies in the ability to identify highly profitable and potentially profitable customers and understand the enablers of a profitable relationship. To succeed in this increasingly challenging marketplace, financial institutions must secure a comprehensive and consistent set of performance metrics, enabling them to better understand the value of customer relationships as well as gain insights into the changing profile and dynamics of customer interactions and profitability.

White Paper Know Your Customer: Getting Serious About Customer Insight August 2012

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