How To Use Big Data In Financial Services

data visualization

Second of a three-part series revolving around #Data and its impact on the Financial Services Industry.

Disclaimer: The technology leveraged in years past will likely not be suitable for data transformation in 2020.

As mentioned in the first article in the series, data is only growing in measure and importance.  Every day, over 2.5 quintillion bytes of data are produced organically.  The biggest companies in the world are evaluating options underground, in the sea and in outer space to store data.  Some are calling data the most important commodity any company can have, replacing oil and gold.However, due to its ‘pie in the sky’ perception, its important to outline how financial services institutions can use Big Data to stage a greater experience for their consumers, agnostic of the consumer’s channel of choice.  To do so, let’s look at three areas where big data can add value, and three hurdles that need to be addressed.



  1. Eagle Eye Visibility: analyzing external market information against internal performance allows bankers to benchmark their organization against their market/state/national peer group, etc. Leadership can look at their whole company or drill down to employee specific metrics. With this information, executives can efficiently share resources (cash, employees, management) in a much more agile fashion than with traditional lagging data.

  2. Create efficiencies / Reduce Inefficiencies: if there are departments with overlapping tasks, or if there are glaring risk items detected through data collection, corrective actions can be taken. This is especially beneficial for institutions directly after a merger or acquisition.

  3. Next Generation Leadership: this is one of the most unaddressed advantages. Too often, the mentality of outgoing leadership is, “well that’s ‘their’ problem”. When executives in their final years of tenure take significant steps to move their institution forward, their roles are desired instead of despised. Generation X is already starting to succeed their Baby Boomer mentors in key executive roles. They are much more technologically connected and understand the value of creating more customized consumer/employee experiences using big data.




  1. Legacy Systems: as mentioned in the introductory disclaimer, the technology stacks and legacy systems that have served financial institutions well will likely not be able to keep up with a big data transformation.

  2. Legacy Mindsets: those that were reluctant to embrace online/mobile/app banking will likely not grasp the value that gathering, analyzing, storing, visualizing and acting on big data can have.

  3. Data: in and of itself, data is a hurdle. It is big today, and only getting bigger and faster. It will be important for the institution to evaluate all their different data inputs and score them on their degree of importance. This will allow the Analytics and IT team(s) to appropriate the budget and resources necessary to steward their role in the transformation.



The utilization of big data should be a focus area for all financial institutions.  The rewards are far greater than the initial investment, and the consequence for delay will only compound as each year passes.  In the final part of the series, we will explore how data visualization can transform the banking industry.