Article by Ying-Choong Lee, September 03, 2019. Ying-Choong Lee, CISA, is head of IT Audit and Data Analytics, at GIC Private Ltd., in Singapore.
By inferring from past examples, artificial intelligence tools can generate useful, real-world audit insights.
Machine learning (ML) algorithms represent a natural evolution beyond rule-based analysis. Internal audit functions that incorporate ML beyond their existing toolkit can expect to develop new capabilities to predict potential outcomes, identify patterns within data, and generate insight difficult to achieve through rudimentary data analysis. Those looking to get started should first understand common ML concepts, how ML can be applied to audit work, and the challenges likely to arise along the way.