American Banker  |  Thursday, November 8, 2007

By Jeanne Capachin

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The amount of data that financial institutions store from their lines of business continues to grow exponentially. Customers, employees, and business partners are interacting more frequently, and in additional ways. As a result, institutions have a mountain of information on their hands.

But this data is not just a management issue. It also is a source of competitive knowledge that can be used to improve business results. At most banks, this remains a goal they have not reached, but they are now investing to get there.

The cast of companies that serve our industry includes both pure-play analytic vendors such as Cognos and Business Objects and companies such as Equifax, Experian, Fair Isaac, and TransUnion that use analytics and data to help solve thorny business problems.

Analytics have been used in credit and risk applications for decades, but the real value now is in getting strong analytic applications into the hands of more employees, thereby improving decision-making at all levels of the bank. Particularly in rocky times, institutions are trying to predict outcomes, and analytic data is a tool they draw upon.

Financial Insights' Top Trends research conducted this July and August identified predictive analytics to support performance management as the top line of business initiatives getting funded for 2008. And for those banks that were not expecting their predictive analytics investments to get financial support, this initiative was ranked almost at the top of things they would have liked to accomplish for next year. In view of all the attention paid to such ideas as mobile banking, corporate portals, and new card programs, it is interesting that this back-office initiative tops the list.

However, it also indicates that banks still do not feel that they have access to sufficient data and analytic tools to drive their businesses and make the best decisions. This is leading to an upsurge in interest in analytical applications and improved data management. Banks are expected to increase spending globally on analytics software at a compound annual growth rate of 11.4% during the next five years, compared to 7% growth in technology spending for the global banking industry as a whole. Analytics remains a strong area of investment by financial services institutions, and vendors that supply these technologies are growing rapidly.

Business analytics is a broadly defined technology that has moved into maturity in the last 10 years. Three basic categories of analytics exist: core, predictive, and information management.

Core analytics is the most mature segment and is the area where banks have already made significant investments. Examples include dashboards, reporting and market segmentation tools, and profitability reporting. One reason core analytics is so important to banks is that it can let a bank cross internal barriers and open up access to information that was trapped in applications. Predictive analytics is a more nascent form of business analytics, building on the capabilities of the core version by including more complex calculations. Predictive analytics tools offer decision support rather than just information delivery. These applications are common in risk management, credit decisions, and fraud detection, where a diverse set of inputs can be used to develop very rich models delivering reliable, and predictive results.

Both core and predictive analytics must be underpinned by accurate, consistent data that is often derived from a variety of sources. Untrustworthy or incomplete data is the most common reason business analytics implementations do not reach their potential. The best tools will fail if the underlying data is not well managed. Information management now includes many components, and it goes well beyond the enterprise data warehouse that many view as synonymous with information management. Many of the big failed CRM projects of the late 1990s and the early part of this decade were failures as the analytic solutions were put ahead of strong information management. Institutions were "drinking the CRM Kool-Aid" and making enormous investments to quickly move from product-centric to customer-centric organizations. These projects spanned years, consumed millions of dollars in investment, and almost never delivered value as expected. Institutions were sold on the promised benefits of improved reporting and customer information management, without understanding the complexity of the underlying data sources.

But in general, these factors have contributed to the lack of success with business analytics: poor underlying data management and overly ambitions projects.

Another factor, a lack of mature technology solutions, was inherent in the last decade, but business analytic software and information management tools have become more sophisticated and usable, so a lack of maturity is no longer an issue.

Although institutions have been investing in business analytics over the last decade and before, results have not always been as expected. An IDC study earlier this year found that only 17.2% of financial institutions considered their packaged CRM application implementations successful, while 32% replied that they needed improvement.

Similarly, financial institutions reported that only 31.8% of data warehousing implementations were successful, compared to 62% that needed improvement. Despite this lack of success, almost 80% of the institutions surveyed plan to increase spending on business intelligence and analytic applications over the next 12 months.

There are clearly challenges that must be overcome for institutions to realize the value of their investment in analytics, but the path is fairly clear now, and institutions are moving ahead at a fast pace.

Ms. Capachin is research vice president for global banking at Financial Insights.

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