Visualization-Driven Approach to Fraud Detection in the Mobile Money Transfer Services

Abstract

Mobile money transfer services (MMTS) are widely spread in the countries lacking conventional financial institutions. Like traditional financial systems they can be used to implement financial frauds. The chapter presents a novel visualization-driven approach to detection of the fraudulent activity in the MMTS. It consists in usage of a set of interactive visualization models supported by outlier detection techniques allowing to construct comprehensive view on the MMTS subscriber behavior according to his/her transaction activity. The key element of the approach is the RadViz visualization that helps to identify groups with similar behavior and outliers. The scatter plot visualization of the time intervals with transaction activity supported by the heat map visualization of the historical activity of the MMTS subscriber is used to conduct analysis of how the MMTS users' transaction activity changes over time and detect sudden changes in it. The results of the efficiency evaluation of the developed visualization-driven approach are discussed.