Visualization of ATM usage patterns to detect counterfeit cards usage

People relish the flexibility of being able access their monetary assets when and where they need them. The abundance of cards able to withdraw funds from Automatic Teller Machines (ATMs) has not gone unnoticed by the cybercriminal element. Means for skimming and cloning cards exist and the market continues to grow. While the methods for obtaining access to another's funds vary greatly, there are cases in which visualization of a class of card-present fraud can combine the visualization with the powerful abductive reasoning capabilities of the human mind to help identify the threat. As part of a defense-in-depth strategy, this can contribute to the evolution and refinement of rule sets that facilitate the detection of the crime prior to the cash-out phase of the illegal operation. This paper discusses cardpresent fraud and provides an example of how visualization techniques, coupled with human abductive reasoning, can be used to guide the evolution of analytical tools to help protect our digital assets.