Not So Fuzzy Auditing Analytics

In light of the increased emphasis on data analytics by accounting practitioners and accreditation bodies, the objective of this paper is to present a case that will help increase students' understanding of textual analytics, which is an under-researched area of data analytics (Fisher 2018). Specifically, students will use both conditional formatting and the fuzzy lookup tool to examine a dataset for possible instances of fictitious vendor fraud, a common and often costly type of fraud. The case takes students through the comprehensive data analytics cycle. First, students are instructed how to test for fictitious vendors by using data analytic techniques. Students will then rely on the underlying data to analyze potential relationships and trends. In the final step, students will communicate results via a memorandum.