"Online Fraudsters Can Be Identified by Their Mouse Movements"

By attempting to perpetrate fraud, online fraudsters can be identified. An international research team led by Professor Markus Weinmann of the Cologne Institute for Information Systems (CIIS) at the University of Cologne conducted the study. The researchers discovered that, on average, the mouse movements of fraudsters were longer and slower than those of honest individuals. The chance of fraud can thus be calculated as users enter data. Since the costs of online fraud are often passed on to all consumers, detecting fraudulent users early on can result in lower insurance premiums for honest users. The study, titled "The path of the righteous: using trace data to understand fraud decisions in real time," was published in the journal MIS Quarterly by Markus Weinmann (University of Cologne), Joe Valacich (University of Arizona), Christoph Schneider (IESE Business School), Jeff Jenkins (Brigham Young University), and Martin Hibbeln (University of Duisburg-Essen). The team studied whether online fraudsters could be differentiated from honest users based on trace data, which is real-time data such as mouse movements or click-streams. Professor Weinmann mentioned that they have been working on trace data and consumer behavior for ten years. An earlier study examined the relationship between mouse cursor motions and emotion recognition. The scientists analyzed the behavior of fraudsters by examining trace data, conducting two controlled experiments in which participants performed various tasks. Participants were permitted to commit fraud for monetary benefit. While doing the tasks, the team documented the mouse movements. The results indicate that, on average, dishonest participants were substantially slower and had greater variations in their mouse movements than honest users. According to Weinmann, greater fraud increases movement deviations and decreases movement speed. The studies concluded that fraudsters deviated 20-42 percent more and moved the mouse 15-26 percent more slowly than honest users. This article continues to discuss the study on identifying online fraudsters based on their mouse movements.

The University of Cologne reports "Online Fraudsters Can Be Identified by Their Mouse Movements"