The Battle For The Indian Banking Industry Will Soon Intensify, And Big Data Will Decide Who Wins


On February 22, the Reserve Bank of India (RBI), an institution that supervises and regulates India’s financial sector, announced guidelines allowing corporations to enter the banking sector. Private companies, public-sector groups, and nonbanking financial firms will all be eligible to apply for a banking license. We expect RBI to start issuing new bank licenses by early 2014.

RBI guidelines state that companies receiving a banking license must open at least 25% of their branches in rural areas. Despite this guideline, I believe that new entrants will primarily target the same urban and semi-urban customers that existing banks target. The reason is simple: These are the most profitable customers. This helps explain why 85% of rural bank branches in India belong to public banks; it’s simply not an attractive market for private banks.

What it means for current Indian banking CIOs: Leverage big data to grow your business or prepare to be left behind.

As competition increases, businesses will expect new IT capabilities to understand and respond to customer needs better, faster, and cheaper. Banking CIOs who embrace this change will adopt big data technologies and become true business partners. The ones who don’t will be bypassed by new entrants (when they come to play) using big data approaches and internal data from whatever market they’re currently in to analyze the banking market. These new entrants will likely influence customer preferences, question existing assumptions, and look for ways to disrupt the market. I recommend that current Indian banking CIOs:

Adopt an incremental open source big data approach to free up money for new technology development and product/service innovation. The evolving open source big data ecosystem around technologies such as Hadoop, Cassandra, and Solr and platforms like Cloudera and Hortonworks is an increasingly attractive option for banking CIOs to reduce their costs significantly. Banks should develop an incremental open source big data road map that aims to reduce IT operational costs, freeing up money for new initiatives that will respond to frequently changing customer needs.

- Embrace the big data-as-a-service model to address the skills gap. The biggest obstacle that enterprises face today is finding big data expertise (engineers, developers, and data scientists); even when such specialists can be found, they come at premium. To counter this, banks can explore a cloud-based model for faster business results from their big data investments. For example, Tresata, a software company focused on big data in financial services, offers a cloud-based platform to process and analyze large volumes of customer financial data, including integration with third-party data from sources such as the stock market.

- Leverage mobile as big data delivery mechanism to improve customer loyalty. Today, mobile devices are transferring power to individuals in their moments of action. Banks can influence the behavior of their customers by delivering products and services on mobile devices based on their online behavior, user sentiment, and even physical movement patterns to improve their engagement with their customers.

CIOs and banks that start their big data journey now will be in a better position to compete when new entrants come to play in 2014. I will be publishing a report on big data trends, challenges, and opportunities for CIOs in India in Q3 2013. If you (whether you are a vendor or an end user organization) are interested in participating and getting a complimentary copy of the report, please send an email to