April 19 2013: The Reserve Bank of India (RBI), has announced guidelines allowing corporations to enter the banking sector. Forrester Research's India Country Manager Manish Bahl , believes that new entrants will primarily target the same urban and semi-urban customers that existing banks target as these are the most profitable customers.
What does the increased competition mean for Indian Banking CIOs? CIOs need to leverage big data to grow their businesses or prepare to be left behind, he suggests. In particular, he recommends CIOs:
Adopt an incremental open source big data approach to free up money for new technology development and product/service innovation
Embrace the big data-as-a-service model to address the skills gap
And Leverage mobile as big data delivery mechanism to improve customer loyalty
We bring you Manish’s blog where he expands his suggestions:
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.
Big Data explained
Measured in terms of volume, velocity, and variety, big data represents a major disruption in the business intelligence and data management landscape, upending fundamental notions about governance and IT delivery. With traditional solutions becoming too expensive to scale or adapt to rapidly evolving conditions, companies are scrambling to find affordable technologies that will help them store, process, and query all of their data. Innovative solutions will enable companies to extract maximum … (More)value from big data and create differentiated, more personal customer experiences. (http://www.forrester.com/Big-Data#)