Banks have always been big data businesses. They have traditionally gathered large amounts of information on their customers and used it to make decisions about lending, investment and other financial services. In recent years, however, the advent of big data analytics has taken this to a whole new level. Banks are now able to gather and process vast amounts of data from a wide range of sources, including social media, retail transactions and financial markets. This allows them to gain a far deeper understanding of their customers and their needs.
This article in BBN Times identifies how banks utilize big data to segment and market to its customers, improve products and increase operational efficiencies, and better manage risk and mitigate fraud. Each solution described here is already available through dedicated 3rd party products and pre-integrated into the offerings of most well established 3rd party processors. If your financial institution hasn’t already selected big data solutions to deploy then it is well behind the deployment curve. This article begins with an introduction that explains the importance of big data analytics in the financial services market:
“Throughout years, the banking industry has improved its service delivery thanks to technological innovation. Services are critical components in daily activities as most transactions are undertaken through the banking sector. The number of customers served in the banking sector has increased exponentially. Each transaction in the banking sector amounts to data creation and collection. The banking industry produces a large volume of data on a day to day activities. The adoption of big data analytics will revolutionise banking at present and in the future.”
It continues with a small drill down for Customer Segmentation, Improvement of Products and Services, Operational Efficiency, Risk Management and then how all of these will impact the Future of Banking.
Overview by Tim Sloane, VP, Payments Innovation at Mercator Advisory Group
Read the full story here
