  Occupational fraud affects many companies worldwide causing them economic
loss and liability issues towards their customers and other involved entities.
Detecting internal fraud in a company requires significant effort and,
unfortunately cannot be entirely prevented. The internal auditors have to
process a huge amount of data produced by diverse systems, which are in most
cases in textual form, with little automated support. In this paper, we exploit
the advantages of information visualization and present a system that aims to
detect occupational fraud in systems which involve a pair of entities (e.g., an
employee and a client) and periodic activity. The main visualization is based
on a spiral system on which the events are drawn appropriately according to
their time-stamp. Suspicious events are considered those which appear along the
same radius or on close radii of the spiral. Before producing the
visualization, the system ranks both involved entities according to the
specifications of the internal auditor and generates a video file of the
activity such that events with strong evidence of fraud appear first in the
video. The system is also equipped with several different visualizations and
mechanisms in order to meet the requirements of an internal fraud detection
system.
