Inferred Social Networks: A Case Study

The behavior, environment, and characteristics of clients form a crucial source of information for various businesses. There exists a number of supervised as well as unsupervised data mining or other approaches that allow analyzing the respective data. In our ongoing project, focusing primarily on the financial sector, we suggest an innovative strategy that will overcome persisting shortcomings of the state-of-the-art methods using an analysis of a social network of clients. In addition, we do not assume the existence of such a network, but from a given set of client financial activities, we are able to infer a social network representing their relationships and behavior. Using real-world data and selected use cases from our domain, we show (a part of) the process of construction of an inferred social network, i.e., what kind of "hidden" information can, for example, be found and exploited.