Article2004

Artificial neural networks in analytical review procedures

80 citations0/0 files storedManagerial Auditing Journal

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Auditing, Earnings Management, Governance Forecasting Techniques and Applications Robotic Process Automation Applications

Abstract

This article gives an overview of artificial neural network (ANN) studies conducted in the auditing field. The review pays attention to application domains, data and sample sets, ANN‐architectures and learning parameters. The article argues that these auditing ANN‐applications could serve the analytical review (AR) process. The summary of the findings pays attention to whether authors state that ANNs have potential to improve analytical review (AR) procedures. Furthermore, the article evaluates which are the most influential contributions and which are open ends in the field. The article makes some practical suggestions to motivate academics and practitioners to collaborate in further exploration of the potential of ANNs.

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References

1998Forecasting with artificial neural networks:1992Managerial Applications of Neural Networks: The Case of Bank Failure Predictions 2014AUDITING AND ASSURANCE SERVICES : AN INTEGRATED APPROACH 2002Why good accountants do bad audits.1997Assessing the Risk of Management Fraud Through Neural Network Technology.2002A roadmap for future neural networks research in auditing and risk assessment 1995The Application of Neural Networks and a Qualitative Response Model to the Auditor's Going Concern Uncertainty Decision*1996A SURVEY OF TIME BUDGET PRESSURE AND IRREGULAR AUDITING PRACTICES AMONG NEWLY QUALIFIED UK CHARTERED ACCOUNTANTS

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