Class Overview
Why is this important?
Artificial Intelligence models are a potentially useful modern assistant to the audit. We will examine what the risk-scoring AI model flags as part of an audit, consider false positives/negatives, and consider the benefits of AI over a traditional audit sampling would have performed in the same scenario.
What will we do?
Audit firms today increasingly expect new professionals not only to understand accounting and auditing theory but also to be comfortable working with data analytics and AI tools. By engaging with the MindBridge AI platform, students gain direct experience with next-generation audit software, which enhances their job-readiness, supports better coverage of transaction populations, and helps them shift from sampling to full-data analysis.
How this relates to other classes:
These two classes build on transaction analysis undertaken in the PCard and Helix/PeachState cases. In those cases we examined transaction data using traditional data analytics tools (Alteryx and Tableau). In these classes we extend our transaction analysis to include the use of AI-assisted audit tools, specifically Mindbridge AI.
Materials and Preparation
Class Materials
- Case:
- Link: Mindbridge AI Platform (the software platform where you load the data and perform the audit).
- Link: Mindbridge University Platform (where you get the data and case material).
- No slides are available for this class.
- Analytics Tools: Mindbridge AI
- Automation Tools: Ensemble AI
- Suggested in-class seating: discussion teams
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Suggested Pre-Class Preparation
- This class continues the work in the prior class and does not require any additional preparation.
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Class Plan
- Students will continue to work in discussion teams to complete the MindBridge AI Case studies.