The Use of the Ant Algorithm in the Audit Planning of Multi-Branch Organizations
Open Access
- 1 January 2021
- journal article
- research article
- Published by Scientific Research Publishing, Inc. in iBusiness
- Vol. 13 (04), 187-209
- https://doi.org/10.4236/ib.2021.134012
Abstract
The study aims to define the important variables to be considered by auditors during the planning phase in multi-branch organizations. The objective of the research determines the possibility of using the ant algorithm as an AI tool suited to plan the audit and identify the audit schedule. The data is based on a survey to collect data to explore the most important factors that influence audit planning. The findings of the study indicate that: 1) the most important variables in audit planning in multi-branch organizations are risk and materiality; 2) the application of AI methods helps reduce bias and judgment of auditors.Keywords
This publication has 10 references indexed in Scilit:
- Codification of Statements on Auditing StandardsPublished by Wiley ,2019
- Research Ideas for Artificial Intelligence in Auditing: The Formalization of Audit and Workforce SupplementationJournal of Emerging Technologies in Accounting, 2016
- Improved Ant Colony Clustering Algorithm and Its Performance StudyComputational Intelligence and Neuroscience, 2015
- The Relationship between Planning of Audit Process and Total Quality ManagementInternational Journal of Business and Management, 2014
- Ant-based Clustering Algorithms: A Brief SurveyInternational Journal of Computer Theory and Engineering, 2010
- Risk Management in Client Acceptance DecisionsThe Accounting Review, 2003
- Audit system: Concepts and practicesTotal Quality Management, 2001
- The Effects of Industry Specialization on Auditors' Inherent Risk Assessments and Confidence Judgements*Contemporary Accounting Research, 2000
- Ant colony system: a cooperative learning approach to the traveling salesman problemIEEE Transactions on Evolutionary Computation, 1997
- The Effect of Industry Experience on Hypothesis Generation and Audit Planning DecisionsSSRN Electronic Journal, 1997