Leveraging Unstructured Text Data for Banks

Banks have volumes of unstructured text data related to customers, businesses, processes and employee engagement which are a source of insights to generate more business, retain customers, improve productivity and enable effective decision making. This paper provides an imperative for adopting unstructured data mining by providing some use cases and examples. It delves into some unstructured data mining techniques that can be leveraged to address the bank’s business objectives. The Imperative for Mining Unstructured Data Analyst firm Gartner’s [1] report, CEO Survey 2012: Financial Services CEO Agenda, reveals that the global banking industry faces huge challenges in the form of dramatically reduced fee income and net interest income, with capital requirements increasing simultaneously. The report also predicts that in order to address these challenges, the prime focus of IT implementations should undergo a paradigm shift to ensure improved customer experience, build new revenue sources, enhance operational efficiency and predict and mitigate risk more efficiently. Unstructured text (data that does not necessarily fit into a single form, format or field) analytics can refocus IT implementations to help address these challenges -by offering insights to improve the three key functional areas of a bank i.e. performance management, risk management and customer relationship management. It can help identify opportunities for customer retention, business development and enhance efficiency of processes and employees. Unstructured Text Analysis – A Strategy Driven Analysis Banks have access to large volumes of unstructured text data from within organizational boundaries as well as the World Wide Web. This data relates to customers, employees, vendors, partners, processes and regulatory compliance. Advancements in Big Data technologies have now enabled banks to process vast amounts of unstructured text data to meet their various objectivesinsights from such data can be used to understand customers, employees and competitors, and to improve the efficiency of existing processes. Figure 1 gives an overview of the ways unstructured text data can be used for business development. A Point of View Figure 1: Text data sources and their possible use Achieve 360 Degree view of customers Listen to Voice of Customer (VoC) Listen to Voice of Employee (VoE) Spot Opportunities Customer Social Media Data  Examples: Facebook, Blogs, Twitter, Foursquare, Linkedin Customer Engagement Data  Examples: Call center logs, Customer care web chat, Customer complaints, Blogs, CRM Employee Engagement Data  Examples: Emails, Chat, Blogs, Work logs, Survey Web Data  Examples: News, Blogs, Online magazines