Big Data: Profitability, Potential and Problems in Banking

By The Financial Brand

60% of financial institutions in North America believe that big data analytics offers a significant competitive advantage and 90% think that successful big data initiatives will define the winners in the future.

More than 70% of banking executives worldwide say customer centricity is important to them1. However, achieving greater customer centricity requires a deeper understanding of customer needs. Research from Capgemini indicates that only 37% of customers believe that banks understand their needs and preferences adequately.

The truth is that financial institutions are struggling to profit from ever-increasing volumes of data. Banks are only using a small portion of this data to generate insights that enhance the customer experience. For instance, research reveals that less than half of banks analyze customers’ external data, such as social media activities and online behavior. And only 29% analyze customers’ share of wallet, one of the key measures of a bank’s relationship with its customers.

Only 37% of banks have hands-on experience with live big data implementations, while the majority of banks are still focusing on pilots and experiments. Capgemini research shows that organizational silos are the single biggest barrier to success with big data. A dearth of analytics talent, high cost of data management, and a lack of strategic focus on big data are also major stumbling blocks.

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Customer data typically resides in silos across lines of business or is distributed across systems focused on specific functions such as CRM, portfolio management and loan servicing. As such, banks lack a seamless 360-degree view of the customer. Further, many banks have inflexible legacy systems that impede data integration and prevent them from generating a single view of the customer.