Year: 2018
Type: article
Abstract: While the massive volume of text documents from multiple sources inside and outside of the company provides more information for auditors, the lack of efficient and effective technology solutions hampers the full use of text data.Powered by the emerging data analytics technology of deep learning, the value of the text can be better explored to deliver a higher quality of audit evidence and more relevant business insights.This research analyzes the usefulness of the information provided by various textual data in auditing and introduces deep learning, an evolving Artificial Intelligence approach.Furthermore, it provides a guide for auditors to implement deep learning techniques with predeveloped tools and open-source libraries.
Authors: Ting Sun, Miklos Vasarhelyi
Institution: Rutgers, The State University of New Jersey
Language: English
Subfield: General Social Sciences
Field: Social Sciences
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W2800991460