Banking on Big Data for new revenue streams

Big Data is being leveraged by a variety of industries to solve seemingly intractable problems, lowering operational costs, addressing regulatory scrutiny, and meeting emerging customer demands and wedging open new revenue opportunities. Banking industry is no exception to this trend. One of the important focus areas for banks is to up their game and offer new revenue generating services to their customers. For example, can a business loan be accompanied by advice on where to set up the business, how to target potential customers and ensure success?

Banks are sitting on massive stockpiles of customer data, ranging from their demographic details to their income and their spend patterns, from their preferences to their circle of friends and influence (based on social media analytics). This Big Data contains insights that can be valuable to the bank's customers - valuable enough to pay for. Banks are also being mandated by regulators to invest in data acquisition, storage, licenses, security, AMCs and people to manage data. There is money being put into Big Data technologies and analytics across the industry. While many see it as a liability - the fact is that the data can actually be turned into an asset.

Banks are privy to customer data coming in from IVR, web, mobile devices, ATMs, kiosks, CRM, surveys, social networks, partner services, syndicated sources and ERP. They are well positioned to solve complex business needs of their customers (this is in addition to personalizing services and acquiring new customers based on insights thrown up by the data). In other words, banks could offer Insights-as-a-Service, adding to non-interest income products.

The challenge is to leverage the data at the right time and from the right place. Traditionally, banks have allowed their data management systems to evolve in silos, based on products and LOBs. Today, structured and unstructured data is spread across numerous systems - some of which may not even be compatible with each other, making data exchange difficult.

The emerging trend is to unify the data that lies in the front office (channels/touchpoints) and back office (core systems) into a common repository that forms part of the middle office layer also referred by us as "Emerging Core". This then becomes the source of all data-led initiatives, delivering accuracy and speed. Consolidating data has become a critical goal of data managers in banking systems. Helping them achieve their goals are APIs and Open Source technologies along with new approaches like Emerging Core. In the months to come, expect several conversations in the industry to center around the task of Big Data management and leveraging it to create new revenue channels and growth.

About the Author

Sandeep Bhagat is a Big Data technology strategist, product and platform visionary at Wipro. Sandeep plays a vital role in business & practice management, solution conception to execution, innovative application & product development. He is a Data Science practitioner with over 18 years of experience He has extensive experience in Business-Technology alignment, technology strategy advisory, new service offerings launch, new revenue stream generation and capability building for niche skills such as performance engineering, Big Data & data science.

His core technology expertise includes Big Data & Analytics, Data Science, Machine Learning, Business Intelligence, Information Architecture, Designing & Architecting High Performance applications, Product Engineering, Performance Engineering and Cloud Computing. In his past working engagement outside Wipro, acting as the chief architect, he has developed an innovative big data management platform BigDataEdge™.

Sandeep holds a Master’s Degree in Computer Science from University of Pune & has undergone an Executive Program in Global Business Management from Indian Institute of Management Calcutta (IIM-C). Sandeep also has various industry certifications to his credit in Enterprise Architecture, Data Science, Data Management, High Performance Computing & Cloud Computing.

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