ABSTRACT: This case is designed to impart practical skills in data analysis techniques aimed at fraud examination. Instructors could employ any one of widely available tools such as ACL, IDEA, Microsoft Access, or Picalo, which is an open-source data analysis tool. Couched in the context of a manufacturer of electronic components in the southeastern United States, the case involves the identification of potentially fraudulent travel expense reimbursements. In the case scenario, traveling salespersons submit expense reimbursement claims, which are subject to a number of business rules. Using data analysis techniques, students are required to identify potentially fraudulent travel expense reimbursements. The data analysis techniques covered in the case include basic features such as identifying duplicates and gaps to more advanced features like joining tables, finding unmatched records, filtering data based on various criteria, and classifying and summarizing data. The degree of structure provided to students is within the control of the instructor, with less structure making for a more realistic and challenging assignment. Spreadsheet files containing the travel expense data are designed to facilitate easy changing of numbers between semesters.

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