The bank depends heavily on unstructured data (mainly world economy and industry reports) in monitoring and predicting risk. The previous process of gathering data was extremely manual, prone to errors and the analysis was often marred with disputes between different business units. As the analysis could not be relied on for accuracy or timeliness, further downstream delays especially when approving new business deals were a constant source of problem for the management.
KewMann helped to design a solution which uses robotic process automation to automate the process of acquiring unstructured data from various online sources. The unstructured data then get processed using semantic & sentiment analytics to generate a top level summary of the various reports and derive sentiment scores for topics of interests. The solution allows the bank to improve turnaround time by 66% and achieve 10x in resource optimization. The bank is now considering to implement the solution across the organization.
Solution: Data Acquisition and Robotic Process Automation, Semantic & Sentiment Analytics