Improving operational efficiencies using Big Data for Financial Services

Abstract

Financial services organizations around the world are experiencing drastic change. Financial services firms are turning to big data technologies and Hadoop to reduce risk, analyze fraud patterns. Ability of Big Data platforms to process and analyze unstructured data efficiently unlike current platforms that are limited to handling structured data. This flexibility makes it possible to gain insights from different variety of data. Big data can be analyzed for insights that lead to better decisions and strategic business moves. For most organizations, big data is the reality of doing business. It's the proliferation of structured and unstructured data that floods your organization on a daily basis - and if managed well, it can deliver powerful insights. Big data analytics is the process of examining large data sets containing a variety of data types -- i.e., big data -- to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful business information. The analytical findings can lead to more effective marketing, new revenue opportunities, better customer service, improved operational efficiency, competitive advantages over rival organizations and other business benefits. Keywords: Big data analytics, Fraud Detection, Hadoop Clusters, Tools