Banking on big data to usher in true transformation

New Update
Big Data

By: Ravikumar Sreedharan, Vice President, Application Services and Managing Director, Unisys India


In today’s digital era, customers have become highly sophisticated and accustomed to receiving seamless service and targeted offers across various touchpoints. To stay ahead of the competition, financial services institutions will need to leverage big data analytics to drive more customer-centric strategies that enable and enhance the omnichannel experience says Ravikumar Sreedharan, vice president, Application Services and managing director, Unisys India.

From researching new services, to opening an account, to checking balances, customers increasingly expect a seamless, consistent, and hassle free omnichannel experience from their banks. To remain competitive, the banking, financial services, and insurance (BFSI) industry, including traditional and newer players like payment banks, need to use big data analytics effectively to achieve their business goals by extraction of actionable insights to acquire and retain customers, while cross selling and upselling a range of personalized services and products.

However, given the deluge of both structured and unstructured data that financial services institutions are required to sift through to glean actionable insights, without the right technologies in place, they are often unable to leverage big data analytics to its true potential across their range of banking service channels. Gartner recently predicted, “Through 2017, 60 percent of big data projects will fail to go beyond piloting and experimentation and will be abandoned. This reflects the difficulty of generating value from existing customer, operational, and service data.


The BFSI industry could take a leaf out of the book of other sectors that are ahead of the game in leveraging the power of big data analytics. For instance, in the healthcare space, according to Hortonworks, medical information can now be collected and analyzed in almost real time, thereby helping doctors improve patient care in countries that have an e-health record system and allow sharing of this data. Further, nearly every major e-commerce player in India today crunches numbers and analyzes customer behavior to craft the best sales strategies and enable data-driven decision-making.

As the Indian economy continues to grow, and with government programs such as Digital India, the addressable market for the BFSI sector is increasing by the day. This sector needs big data analytics to not just drive customer-centric strategies, but also manage enterprise risk and combat the increasing incidence of fraud, which these organizations are more prone to primarily because of the massive amount of personal and financial data they generate.

In such a scenario, the key factors that need to be considered for an effective strategy are:


Clearly defined objectives: At the outset, organizations need to clearly define the objectives and results expected through the deployment of a big data analytics strategy, which could vary from improving customer acquisition and retention rates, to driving greater product usage, or even detecting and mitigating fraud.

Across the board: The big data analytics strategy needs to envelop the entire organization and not be implemented in silos. For instance, the insights gleaned from big data can not only be used to develop new products and services, it can also track adoption patterns across channels once the product is launched in the market.

Sifting through the noise: BFSI institutions need to identify the right internal and external data sources, keeping in mind their business objectives, for the most accurate and insightful approach. Not all data will be useful. Data also needs to be filtered, compiled, and stored in a manner that aids in deriving actionable intelligence.


    Proactive security: Organizations must factor security into every individual identity, transaction, and device that connects to their network instead of bolting it on as an afterthought, in order to protect their most sensitive data and assets. They need to build and run security that works across all parts of their ecosystem (including suppliers, partners, personal devices, and clouds), not just their networks. Further, by using techniques such as micro-segmentation and cryptography, organizations can restrict even approved users (and all hackers) to access only the data and services for which they are authorized.

Right people for the job: Often even the most effective technologies fail because companies do not have people with the required skills or experience in handling, analyzing, and reporting on big data. The most forward thinking companies are investing in hiring and training employees with the curiosity to ask the right questions and the ability to quickly and effectively synthesize actionable insights from big data.

Right platforms: Finally, it’s important to select the right platform that is robust, flexible, rapidly deployable, and secure, to provide decision makers with real-time actionable data, in an easily digestible format.

BFSI organizations inherently have a larger customer base than perhaps any other industry and therefore have access to a rich goldmine of data. Organizing, categorizing, and analyzing this data to derive actionable insights is no easy task; however, with the right enterprise strategy in place, the benefits of the precise application of insights culled from data are manifold.

BFSI organizations need to leverage big data analytics to not only improve the customer experience, but also minimize the incidence of fraud, drive new revenue streams, and increase profit margins. In other words, these players must deploy big data analytics to not just remain competitive, but to truly bring in transformation.