Big data has big appeal for financial services companies, but the industry is still grappling with how to get the most out of the technology.
In a talk entitled “How the Financial Services Industry Can Unlock the Value of Big Data,” Julient Courbe, the financial services technology leader at PricewaterhouseCoopers (PwC), told an audience of industry professionals that big data “is an innovation that delivers business insights and opportunities.”
Speaking at this week’s SIFMATech 2013 conference in New York, Courbe said that two-thirds of the industry’s IT executives surveyed by PwC see big data as an enormous opportunity. He backed that up by pointing to another survey result: the financial services industry is spending more of its technology dollars on managing unstructured data than any other technology-based initiative and, per the survey, this spend is expected to rise another 9 percent this year.
Since big data is seen as both the biggest driver and prime beneficiary of the growing effort to manage unstructured data. By some estimates, 80 percent of an organization's data is non-numeric, but it still must be included in analyses and decision making.
According to Courbe, big data has three key characteristics that differentiate it from ordinary data or “little data”:
- The growing volume of data: resulting from the ever-increasing number of data-based transactions that are recorded, including text data constantly streaming in from social media and other sources. The growing volume of data generated by mobile devices is another huge contributor.
- The increased variety of data: from traditional databases to hierarchical data stores created by end users and online analytical processing systems, to text documents, email, video, audio, stock ticker data and financial transactions.
- The accelerating velocity of data: meaning both how fast data is being produced and how rapidly it must be processed.
Financial firms, Courbe said, which are looking to transform their organizational culture to foster innovation while remaining cost competitive, need to manage the exponential growth of both structured and unstructured data. But “big data is not a technical problem,” he emphasized. Where companies have fallen short, he said, was not because they couldn’t find a way to manage all their data, but because they failed to see the value of doing so.
The industry can extract value from big data, Courbe said, in three key ways:
- Deciphering customer behavior and identifying opportunities for growth by extracting unstructured information from customer-service systems and performing predictive analytics on payment and statement information to forecast buying patterns.
- Reducing risk and better managing investments by developing models that continually incorporate data throughout the investment’s lifecycle, from purchase to sale or origination to close.
- Reducing risk and complying with regulations and reporting requirements by integrating structured and unstructured data from both firm-wide and external sources of market data.
The biggest barriers to big data adoption, Courbe said, include confusion over which problem a big data project is intended to solve, uncertainty over how to measure and quantify the value of a project once it’s implemented, and failing to recognize the need to drive a shift in the organization’s mindset in order to promote acceptance and use of the new analytical tools that the big data project has made available.
This story originally appeared at Securities Technology Monitor.
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