How an Evolving Technology Could Transform Auditing

This article provides an introduction to deep learning technology, a new type of artificial intelligence that can be taught to see patterns in enormous amounts of data that are incomprehensible to humans. This technology, which is still under development, offers a means of using big data to produce supplemental audit evidence that enhances the effectiveness and efficiency of audit automation and decision-making. The authors also cover how these methods might be used in auditing processes.

The creation of data-intensive technologies (such as ERP systems, sensors, cloud storage, and remote communication tools) in the current corporate environment makes it easier to produce and maintain vast amounts of data, which calls for a new data environment and drives the need for audit automation. The most advanced application of artificial intelligence, deep learning, has been used by top accounting companies to carry out audit tasks. For instance, KPMG uses the deep learning-powered systems of IBM Watson to examine the credit files of banks for portfolios of commercial mortgage loans, and Deloitte has partnered with Kira Systems to examine contracts, leases, bills, and tweets. It's true that deep learning usage in the accounting industry is still in its infancy.

By incorporating this technology's cognitive capabilities in the fields of textual analysis, speech recognition, image and video processing, and judgement support into the audit process, economies of scale can be achieved, accelerating the technology's widespread adoption. In order to facilitate audit automation and enhance decision-making, this article explains how the cognitive capabilities of deep learning could be used to various audit procedures.


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Adarsh R


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