Sunday, June 9, 2013

Banking Industry Taking Small Steps With Big Data

As was discussed in the first of my series on Big Data in Banking, the financial services industry has a vast reservoir of data on their customers, but is in the infancy stage of utilizing this data for financial or competitive gain. 

A new study published by the IBM Institute for Business Value confirms that while the majority of financial firms believe data can create a competitive advantage, the scope of data used and the analytic capabilities lag behind other industries.

Second in a series on Big Data and Banking

In a study published by the IBM Institute for Business Value in conjunction with the Said Business School at the University of Oxford entitled, "Analytics: The Real World Use of Big Data in Financial Services," it was found that 71 percent of banking and financial firms globally believe that the use of insight and analytics creates a competitive advantage, compared with 63 percent of cross-industry respondents. This compares with only 36% reporting this advantage in 2010, representing a 97 percent increase in just two years.

Pragmatic Customer-Centric Strategy

Not surprisingly, the IBM research found that most 'big data' strategies being implemented by the financial services industry begin by initially identifying business requirements, then leveraging existing infrastructure, data sources and analytic capabilities before incrementally expanding sources of data, technology and analytic capabilities. This 'slow to go' progression is actually on par with the global cross-industry counterparts reviewed.

It should be noted that the progress with almost any data initiative in the financial services industry is directly correlated to the size of organization due to the investment required and current infrastructure of the organization. I was reminded of this very important distinction by James Robert Lay, credit union industry thought leader and CEO of PTP New Media in a Twitter response to my big data post last week.

Despite the size of organization surveyed, and reinforced by the Celent research reviewed in my previous post, customer-centric objectives dominate the focus of most data activities in the banking industry. In fact, 55 percent of active data efforts revolved around customer outcomes in the IBM study.

As mentioned in my previous post on big data and banking, focusing on the customer is increasingly important as channels for transacting and communicating continue to increase, developing new segments of customers based on the ways(s) they want to perform transactions and hear from their bank and credit union. Through this customer-centric focus, the customer experience should improve as financial institutions can better anticipate customer needs in a multichannel environment.

Second in importance for financial organization use of data was for fraud and risk mitigation and achieving regulatory and compliance objectives (23%). This focus was significantly higher than the cross-industry sample in the study.

The study also found that, while the majority of institutions surveyed said they had much of the infrastructure in place to manage the increasing flow of data (87 percent), only slightly more than half reported that their data was integrated across silos. This continues to be a challenge as customer expect their financial organization to understand their entire relationship when working with their bank or credit union. This challenge is obviously exacerbated with smaller organizations who may not even have a CRM system in place.

Focus on Internal Data Opportunities

Despite industry and solution provider hype, most early big data initiatives are focusing on analyzing the tremendous amount of untapped opportunity that still resides within most financial institutions. More than 4 out of 5 financial organizations surveyed in the IBM study are analyzing transaction and log data that has been collected for years, yet not analyzed due to system constraints.

Where banks and credit unions lag their cross-industry peers is in using more varied data that requires more sophisticated (and expensive) technology. For instance, while call centers are still very important to financial institutions, only 21% of larger banks analyze this data (compared with 38% on non-financial organizations). Financial institutions also significantly lag their cross-industry counterparts in evaluating social data (27 percent for banks compared to 43 percent for non-banks).

Analytic Capabilities Lag Non-Bank Counterparts

Consistent with my review of recent Celent research in the post entitled, "Customer Analytics is Key To Growth In Banking", data mining of structured internal data such as basic inquiries, predictive modeling, etc. is on par with other industries. There is a significant drop off in capabilities, however, when financial institutions are asked about the ability to analyze unstructured data such as voice and social streams.

While the investment in these types of analysis should lag the basic capabilities described earlier (analyzing internal, structured sources), the growth and power of advanced analytics that includes unstructured data needs to be tested by banks to determine monetization opportunities (ROI).

Go Forward Recommendations

Advancing technology in combination with vastly expanded data sources are combining to provide the foundation for tremendous advancements in the application of big data insights within the financial services industry. Despite this potential, however, even the most advanced organizations are following a very structured path of integrating data analytics and insights within the organization.

In writing and speaking on the subject of big data for more than two years globally, I have found that much of the hype surrounding 'big data' has significantly preceded the proven financial benefits of using all of the data available to banks and credit unions. Unfortunately, many organizations still believe they are required to play 'catch up' to the minority of organizations that have the resources and talent to conduct an expansive test and learn process around unstructured data.

Without regard to resource availability, here are some foundational common sense steps that the IBM study, Celent research, other studies in the financial services industry (and myself) believe should be taken before expanding capabilities around big data.

      • Begin with initiatives that will have a proven financial impact of increased revenues and/or decreased costs (increased sales, lower cost delivery, enhanced service, reduced risk)
      • Build a blueprint that aligns business needs with IT capabilities (and resource requirements)
      • Engage all impacted parties (executive level buy-in is required)
      • Start with internal data sources (logical, cost effective and with great upside potential)
      • Apply a test and learn process for all initiatives with measurement applied against preset objectives
Big data provides the potential for big opportunities for banks and credit unions. But the definition and application of 'big data' should begin with small steps applied against internal data that is readily available. As successes are achieved, the financial and operational benefits and learnings can be applied towards more ambitious projects that are deemed to be financially viable.

Additional Resources

Analytics: The Real World Use of Big Data in Financial Services - IBM Institute for Business Value (May 2013)

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  1. Great insight and thoughts on this Jim. What if banks and credit unions started with "small data" instead of "big data". Big data, by its very name, can be scary and intimidating for many executives who are not completely comfortable with how technology is changing the biz model of financial services.

    It's the "small data" that can help your bank or credit union get quick wins and further internal buy in to bring marketing, sales, IT and operations to the same table.

    For example, banks and credit unions have the birthdays of their customers and members. But what are they doing with this "small data". For many... nothing. However, if we look outside at the general retail world, how many others are using birthdays to engage with consumers.

    So to get a quick win with "small data", create a road map that engages with customers and members during their birthday month via digital and offline channels. You may hit them with 1-2 punch of an automatic email marketing campaign followed by a customized direct mail piece.

    Both communication touch points would be highly customized and may even cross-sale a product/service depending on what a person already has with a "birthday offer". The offer may be .25% off an auto loan or .25% more on a 6-month CD.
    A simple litmus test with birthdays can the be reviewed and refined overtime.

    Never the less, using the "small data" banks and credit unions already have can create some quick wins to further the cause for investing in "big data" analysis because at the end of the day... all roads lead to digital:

    1. I can't agree more. The money left 'on the table' by banks and credit unions of all sizes is amazing and relatively easy to capture. Beyond your birthday program (which I love) is making the first good impression when a customer opens a new account. I have used this blog to promote the potential of a strong, multichannel welcome program since the blog was started. Still, the vast majority don't take advantage of this opportunity when the chance for improved engagement, increased cross-sell and lowered retention is greatest. The business case for onboarding was discussed here (

      Another 'small data' opportunity includes monitoring an institution's customer file for loan inquiries (indicating a large purchase or refinance). Loan triggers are another 'easy win' since credit bureaus or tri-bureau providers can provide daily or weekly lists of customers who are shopping. I covered this opportunity in a post here (

      Finally, there are also many ways to use simple digital tools like retargeting that may not have the volume, but are very reasonable in cost and easy to implement. We can no longer let people who visit our websites leave without being recontacted.

      I discussed 'quick wins' like the above and others in this previous post (

      Please continue to 'keep me honest' with your thoughts around how credit unions and banks outside the top 100 can leverage ideas I discuss. I appreciate your input.