Research Ideas for Artificial Intelligence in Auditing: The Formalization of Audit and Workforce Supplementation

Abstract

After decades of frustration with long “AI Winters,” various business industries are witnessing the arrival of AI's “Spring,” with its massive and compelling benefits. Auditing will also evolve with the application of AI. Recently, there has been a progressive evolution of technology aimed at creating “artificially intelligent” devices. Although this evolution has been permeated with false starts and exaggerated claims, there is some convergence on the fact that substantive progress has been obtained in the last few years with the adoption of deep learning in conjunction with much faster machines and dimensionally larger storage spaces (and samples). The area of auditing has lagged business adoption in the past (Oldhouser 2016), but is prime for partial automation due to its labor intensiveness and range of decision structures. Several accounting firms have disclosed substantive investments in the AI fields. This paper proposes various areas of AI-related research to examine where this emerging technology is most promising. Moreover, this paper raises a series of methodological and evolutionary research questions aiming to study the AI-driven transformation of today's world of audit into the assurance of the future.

Artificial Intelligence: Opportunities, Issues and Applications in Banking, Accounting, and Auditing in Nigeria

“…Auditors through AI assisted systems can ask better questions and interact better with stakeholders, including financial officers, audit committees and company boards, thus, adding value to the audit process. This findings is akin to Issa, Sun, and Vasarhely, [7] which found that through AI visual recognition techniques, auditors are able to "understand" the content of an image taken by a drone or video captured by surveillance cameras, automatically identify the object and subject (including human faces) in the image, and subsequently organize and classify each image into a predefined logical class. Such technique can facilitate the automation of assets and inventory checks and fraud detection.…”

“…This problem is exacerbated by the unstructured nature of Big Data and the high level of complexity and ill structureinvolved in certain audit tasks, such as the evaluation of internal controls. Hence the new methodologies can assist auditors inovercoming the aforementioned limitations.The increasing maturity of AI technologies, more specifically deep learning technology, such as visual recognition, textual analysis, natural language processing, and audio processing, provides unlimited potential and inspiration for its application to auditing [7].…”

“…These functions serve financial statement analysis, which is a comprehensive task. When auditors analyze financial reports, the machine scans and identifies each accountand its balance and links these numbers to the related supporting evidences automatically, thus enabling the detection of irregularities [7].…”

The Increasing Role of It Auditors in Financial Audit: Risks and Intelligent Answers

“…Big Four companies are Deloitte, PwC, KPMG and EY, the four largest auditors in the world (Statista, 2017b). As summarized by Issa, Ting, and Vasarhelyi (2017) Deloitte are introducing a contract analysis system which aims to help auditors analyse complex and long documentation provided by the audited company as audit evidence. It can be performed by text mining and natural language processing saving precious time since auditors don't necessarily have to go through each and every contract, statement and policy, the system is capable to extract the necessary information which can then be used for further investigation.…”

Autoencoder Neural Networks versus External Auditors: Detecting Unusual Journal Entries in Financial Statement Audits

“…which results in a high false positive rate. Besides, apart from the Big 4 audit firms, many auditors lack the necessary technical skills to perform such data-driven analyses on large datasets [6].…”