New and Refined Frontiers of Financial Services Analytics
April 16, 2010

The financial services industry has been at the forefront of the use of analytics for strategic and tactical purposes. Indeed, for decades, those needing to perform, say, credit and actuarial analytics have been at the forefront of using business computing to increase efficiency, deepen insight and improve decision making. So in some respects it may be tempting to think that, when it comes to analytics, the financial services industry has its bases covered. Although to some extent that may be case for well-established uses of analytics, there are at least five if not more areas where there is considerable room for improvement.

Take pricing. It's a mistake to think that most financial institutions that have a residual credit exposure are doing what they can when it comes to optimizing their risk-based pricing of their products. This is particularly true on the consumer side of the business, whether it's consumer loans, car leases or even mortgages. The issue dropped off the table at the start of the financial panic a year and a half ago and is subdued today because of the steepness of the yield curve and stringent credit screening policies. However, both of these factors will be reversing over the next 12-18 months and so I am certain price optimization will re-emerge as an important strategic issue as companies are forced to eke out additional basis points of margin while demonstrating to investors and regulators that they have a handle on risk and limiting adverse selection in their lending practices.

Customer profitability management has been a hot topic in financial services for the past 15 years. Banks were one of the first to focus on this issue as they discovered that they needed to develop short- and long-term strategies that enabled to lavish more attention on their more profitable accounts and minimize the cost of servicing the ones producing low contribution margins. Managing customer profitability is one of the trickier applications of analytics. If, for example, an analysis shows that 10 percent of your customers account for 150% of your profits (in round numbers, an oft-quoted statistic for consumer banks) then either the analysis is flawed or the result is not actionable. Most financial institutions face substantial measurement challenges. Allocating their considerable shared costs accurately and in a way that leads to better decision making is difficult. Moreover, a 20-something may be unprofitable today but may be hugely profitable in 10 or 15 years. Given most people's conservatism when it comes to money and long memories for bad service, it's not necessarily a good idea to try to lose a young customer if the objective is maximizing long-term value. But how do you identify the potential winners?

And how should a financial services company manage its sales and marketing programs to attract more of the more profitable customers? While a portion of the financial services business is institutional and wholesale in nature, the consumer segment is huge and requires the intelligent application of sales and marketing analytics to attract new customers. Here, too, analytics can address the gaps. You can read my colleague's perspectives on priorities for using information technology to advance sales and marketing effectiveness here.

Moreover, like many businesses, retaining customers and capturing a larger share-of-wallet (or piggy bank) is a key driver of market share and profitability. Managing customer interactions effectively, especially, again, in the consumer segment, is key. Yet our research finds that only a handful of companies in the financial services industry have matured their customer interaction processes and therefore risk losing customers or not earning a reputation for customer service that will win customers. My colleague recently laid out the priorities for addressing this issue.

One other area where financial services companies can apply analytics is in improving their ability to measure and manage their asset/liability risks. One reason for the 2008 financial panic was an overreliance on models that were too far removed from reality to be useful in a period of financial stress. New approaches to measuring and managing bank asset/liability risk are available (see "IT Empowers Financial Regulation to Mitigate Risk" that would enable management and regulators to have a clearer picture of their risk exposure.

If you are considering how to apply analytics in your financial services organization, I encourage you participate in our latest benchmark research on analytics. The research will assess the needs of financial services companies in the key business. The research should allow your organization to have a better understanding of where the application of analytics can help your competitive position.

Take Analytics Benchmark Survey for Financial Services

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Robert Kugel CFA - SVP of Research


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