Blogs

Analytics: The Real-world Use of Big Data in Financial Services

Global Banking Industry Marketing, Big Data, IBM

This first posting of a seven-part blog series is my attempt to present, in small, easily consumable bites, findings from IBM Institute for Business Value and University of Oxford’s study and excerpts from a white paper, Analytics: the real world use of big data in financial services.”

In the paper, my colleagues David Turner, Michael Schroeck and Rebecca Shockley find that executives are recognizing the opportunities associated with big data[1], and that data is no longer confined to technology. It is now a business imperative that is providing solutions to long-standing business challenges for banking and financial markets companies around the world. Financial services firms are leveraging big data to transform their processes, their organizations and soon, the entire industry.

But it can be difficult to find in-depth information on what financial services firms are really doing. In this industry-specific paper, the authors examine how financial services firms view big data – and to what extent they are currently using it to benefit their businesses. The IBM Institute for Business Value partnered with the Saïd Business School at the University of Oxford to conduct the 2012 Big Data @ Work Survey, the basis for the research study, surveying 1144 business and IT professionals in 95 countries, including 124 respondents from the banking and financial markets industries, or 11 percent of the global respondent pool.

Big data is especially promising and differentiating for financial services companies. With no physical products to manufacture, data – the source of information – is arguably one of their most important assets. Banking and financial management are rife with transactions, with hundreds of millions conducted daily, each adding another row to the industry’s immense and growing ocean of data. So the question for many of these firms is how to harvest and leverage this information to gain a competitive advantage?

The study finds that 71 percent of these banking and financial markets firms report that the use of information (including big data) and analytics is creating a competitive advantage for their organizations, compared with 63 percent of cross-industry respondents. Compared to 36 percent of banking and financial markets companies that reported an advantage in the IBM 2010 New Intelligent Enterprise Global Executive Study and Research Collaboration, this is a 97 percent increase in just two years (see Figure 1).[2]

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At the same time, these firms are dealing with a very diverse and demanding customer base that insists on communicating and transacting business in new and varied ways, any time of the day or night. While the banking industry’s structured customer data is growing in size and scope, it is the world of unstructured data that is emerging as an even larger and more important source of customer insight. Investment bankers, financial advisors, relationship managers, loan officers and countless other front-office employees must have ready access to detailed product and customer information in order to make better and more informed decisions, while also supporting regulatory and compliance reporting requirements.

The banking and financial industries are not immune to the growth of social media as their reputations and brands are discussed by customers within their large personal networks. The creation of useful data now stretches well beyond the bank’s control.

Further, the study found that banking and financial services organizations are taking a business-driven and pragmatic approach to big data. The most effective big data strategies identify business requirements first, and then leverage the existing infrastructure, data sources and analytics to support the business opportunity. These organizations are extracting new insights from existing and newly available internal sources of information, defining a big data technology strategy and then incrementally extending the sources of data and infrastructures over time.

The Big Data @ Work survey confirms that most organizations are currently in the early stages of big data planning and development efforts. Banking and financial markets companies are on par with the global pool of cross-industry counterparts. While 26 percent of banking and financial markets companies are focused on understanding the concepts (compared with 24 percent of global organizations), the majority are either: defining a roadmap related to big data (47 percent) or already conducting big data pilots and implementations (27 percent, see Figure 2).

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In this global study, the authors identified the following key findings that reflect how financial services organizations are approaching big data:

  1. Customer analytics are driving big data initiatives
  2. Big data is dependent upon a scalable and extensible information foundation
  3. Initial big data efforts are focused on gaining insights from existing and new sources of internal data
  4. Big data requires strong analytics capabilities

In subsequent blogs, we will examine the maturity of banking and financial markets organizations with respective to these key findings. We will also share top-level recommendations directed at the needs of banking and financial markets companies.

Read "Analytics: the real world use of big data in financial services"


[1] Schroeck, Michael; Rebecca Shockley, Dr. Janet Smart, Professor Dolores Romero-Morales and Professor Peter Tufano. “Analytics: The real-world use of big data. How innovative organizations are extracting value from uncertain data.” IBM Institute for Business Value in collaborations with the Saïd Business School, University of Oxford, October 2012. ©2012 IBM.

[2] LaValle, Steve, Michael Hopkins, Eric Lesser, Rebecca Shockley and Nina Kruschwitz. “Analytics: The new path to value: How the smartest organizations are embedding analytics to transform insights into action.” IBM Institute for Business Value in collaboration with MIT Sloan Management Review. October 2010.  ©2010 Massachusetts Institute for Technology.