A Study on Search and Filtering Analysis of Unstructured Text in Financial Service Industry

Management of unstructured data is viewed as one of the major unsolved problems. Nearly eighty percentage of enterprise data resided in unstructured formats such as text files, email, customer profile information, external information, video documents and audio samples in various fields including search, prediction, business intelligence, financial service industry – FSI and in sematic web, which aims at converting web of unstructured data into a “web of data that can be processed directly and indirectly by machines.” The reason behind is that the tools and techniques that have proved so successful in transforming structured and unstructured data in FSI and actionable information to resolve increasing complexity for the transacting database information. With the newly launched FSI regulations, the issue has drawn close attention from governments, financial institutions and research scholars. A few fundamental and important questions confront us in resolving the ever increasing complexities in this issue. However in FSI, there exists, many issues in the Suspicious Activity Report – SARs such as large value reporting, delivering, analysing processes and traditional investigations consuming large volume of man-hours.