Big or small, banks should turn data into valuable insights

by Sohini Bagchi    Jul 05, 2013

datasets

Big data is today’s panacea and enterprises are rushing to cash in on the opportunity. However, several banking CIOs and IT leaders believe that although ‘big data’ as a term is wonderful, it is also ‘Small data’ or the available information derived from day to day operations that can make a huge difference in the bank’s profitability if these data sets can be turned into actionable insights.

In order to leverage the varieties of data used in the day to day operation, banks should adopt a more branch-focused analysis approach, a concept which is often ignored, states William Weidman, Senior Vice President of Applied Predictive Technologies, a data analytics firm, in a recent blog post. He suggests the same rich data sets banks strive to analyze at the customer level should be applied at the branch level for branch-based decisions including operating hours, staffing levels, renovations and adding new technology, which is often complex and expensive. The branch-based analytics can include demographics of the surrounding area, competitor locations relative to each branch and the profile of the customers at that branch.

Weidman mentions, an understanding of which branches deserve reinvestment and how to roll out a customer program on a specific date, for example, can also make a huge difference in its profitability. “Improving analytics at the branch level can automatically have a positive impact on customer-focused strategies,” he states.

Leveraging just data

Many others in the banking industry believe that big data is an overused word that receives too much attention when it is essential to just utilize any data set properly. “The CIO of a bank worries about data quality, data categorization, and any structured and unstructured data, and handles these information with the help of BI or analytics tools,” says Shrawan Kumar, General Manager - IT at Allahabad Bank. He gives the example of a bank that decides to move entirely to separate systems to process unstructured data, such as the cloud, or rely on in-house development and customizing Hadoop or any other open-source tools. However, all this entirely depends on what kind of information the business is looking at and how to best leverage these data sets.

Kerry Lam, Partner McKinsey in a recent article points out the key to unlocking this value lies in leveraging the vast amount of customer data that banks now have at their fingertips. For example, pertinent data sets will more closely establish customer value to the bank, by customer type and segment; banks can then address their customer relationships with greater focus and relevance in products, pricing, and channel. He gives the example of right-sizing product portfolio, wherein banks can intensify or expand their relationships with high-potential customers, while effectively managing costs in lower-value segments.

As banks struggle to maintain their margins, retain customers as well as reach out to attract new customers, analyzing the right data sets in their day to day activities can help them optimize customer relationships, align channels, and energize the front line with the richest and most relevant customer knowledge. As Lam says, smart, targeted use of data can open pockets of growth across the bank. With the right orientation of both big and small data, banks can have the best chance of growing relationships to their full potential.