This case can focus on generative AI and Alteryx as technologies, but the primary focus is the critical thinking involved in thinking about fraudulent data. In Part 1, students take on the role of the client and generate a fake data set. In Part 2, students are asked to design audit tests to determine if the data is real. The process of generating fake data presents a unique avenue for students to learn. Having students generate their own data set is meant to help them see patterns that exist in data and the difficulty in fully creating fake data. As students think through various testing procedures to discern between real and fake data, they will enhance their problem-solving and analytical thinking skills. This exercise not only sharpens their ability to design robust processes, but also fosters a heightened awareness of potential vulnerabilities and controls in processes and systems.

This case is highly flexible. The user guide provides four different examples of how this case could be taught. Suitable courses include forensics, audit or data analytics classes.

NOTE: We recommend you introduce students to prompt engineering case prior to covering this case.

Suitable courses: Forensics, Audit, Data Analytics Link to download files (requires login)

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