Degree Name
MS (Master of Science)
Program
Information Systems
Date of Award
5-2026
Committee Chair or Co-Chairs
Chelsie Dubay
Committee Members
Ahmad Al-Doulat, Emily Cokeley
Abstract
Financial auditors must manually review large volumes of unstructured text that may include contracts, internal policies, footnotes, and journal entry descriptions. This time-intensive process introduces risk of human error and inconsistency. Despite advances in automation, no systematic approach exists for applying Natural Language Processing (NLP) to this problem at scale. Using a design science approach, this study develops a framework that demonstrates how NLP techniques can be incorporated across key phases in the audit process, including planning, internal controls evaluation, evidence gathering, and reporting. Initial evaluation through expert feedback had a mix of responses. While some argued difficulty with data accessibility, others advocated its feasibility and highlighted its practicality for analyzing textual audit evidence while maintaining auditor judgement.
Document Type
Thesis - unrestricted
Recommended Citation
Amoatey, Dennis K., "The Application of Natural Language Processing Towards Auditing of Unstructured Data: A Design Science Approach" (2026). Electronic Theses and Dissertations. Paper 4686. https://dc.etsu.edu/etd/4686
Copyright
Copyright by the authors.
Included in
Accounting Commons, Artificial Intelligence and Robotics Commons, Databases and Information Systems Commons
