Data visualization: a different perspective

Abstract

Data visualization is one of many ways to detect potential financial fraud. It can be used to detect outliers by changing the visual representation of a dataset, which is generated from a company’s IT systems. This research tries to take a different perspective on data visualization by conducting an experiment at accounting students to test whether graphical and photographical forms are more efficient and effective for detecting potential fraud than tabular forms. To measure efficiency, time is tracked to measure how fast respondents answer each question. To measure effectiveness, the accuracy of answering questions correctly is measured. As the differences between three representations are partly normal distributed, both Wilcoxon paired signed rank tests and paired t-tests are used to find whether the median or mean of differences between the pairs of observations are zero or not. Both significant and insignificant results are found. The most important finding is that the use of both graphical forms and photographical forms lead to quicker fraud identification processes. However, the time it took to create these data representations is not considered. It would highly depend on the skills of the investigator to realize time gain. More research in the field of data visualization is necessary to find differences between different forms of data visualization.