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A multi-objective optimization approach for integrated risk-based internal audit planning

Annual audit planning is a multi-criteria decision-making problem faced by internal audit departments of all organizations. Due to the constrained audit resources, the planning process primarily involves the analysis and evaluation of complex factors for selecting auditable units that maximize the f...

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Autores principales: Wang, Xiong, Ferreira, Fernando A. F., Yan, Pengyu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9925941/
https://www.ncbi.nlm.nih.gov/pubmed/36818190
http://dx.doi.org/10.1007/s10479-023-05228-2
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author Wang, Xiong
Ferreira, Fernando A. F.
Yan, Pengyu
author_facet Wang, Xiong
Ferreira, Fernando A. F.
Yan, Pengyu
author_sort Wang, Xiong
collection PubMed
description Annual audit planning is a multi-criteria decision-making problem faced by internal audit departments of all organizations. Due to the constrained audit resources, the planning process primarily involves the analysis and evaluation of complex factors for selecting auditable units that maximize the full potential of internal audit. Previous research on internal audit planning only focused on the goal of risk minimization and applied ranking methods to prioritize alternatives. In order to enable internal audit activities to add more value to the organization, the integrated risk-based internal audit planning is proposed to assist audit department in achieving multiple objectives in addition to risk management. Meanwhile, a multi-stage framework is proposed to support the development of such value-added internal audit plan. The new framework integrates the risk assessment of auditable units with the selection of audit activities and resource allocation through a combined analytic hierarchy process (AHP), fuzzy comprehensive evaluation (FCE) and weighted multi-choice goal programming (WMCGP) approach. The model considers both qualitative and quantitative decision criteria. A real-life case study of the development of an integrated risk-based annual audit plan is presented, and sensitivity analysis is performed to illustrate the validity of the proposed approach. The results indicate that the proposed framework is a useful tool for internal audit planning and the implications of the study can be extended to various selection and allocation problems.
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spelling pubmed-99259412023-02-14 A multi-objective optimization approach for integrated risk-based internal audit planning Wang, Xiong Ferreira, Fernando A. F. Yan, Pengyu Ann Oper Res Original Research Annual audit planning is a multi-criteria decision-making problem faced by internal audit departments of all organizations. Due to the constrained audit resources, the planning process primarily involves the analysis and evaluation of complex factors for selecting auditable units that maximize the full potential of internal audit. Previous research on internal audit planning only focused on the goal of risk minimization and applied ranking methods to prioritize alternatives. In order to enable internal audit activities to add more value to the organization, the integrated risk-based internal audit planning is proposed to assist audit department in achieving multiple objectives in addition to risk management. Meanwhile, a multi-stage framework is proposed to support the development of such value-added internal audit plan. The new framework integrates the risk assessment of auditable units with the selection of audit activities and resource allocation through a combined analytic hierarchy process (AHP), fuzzy comprehensive evaluation (FCE) and weighted multi-choice goal programming (WMCGP) approach. The model considers both qualitative and quantitative decision criteria. A real-life case study of the development of an integrated risk-based annual audit plan is presented, and sensitivity analysis is performed to illustrate the validity of the proposed approach. The results indicate that the proposed framework is a useful tool for internal audit planning and the implications of the study can be extended to various selection and allocation problems. Springer US 2023-02-14 /pmc/articles/PMC9925941/ /pubmed/36818190 http://dx.doi.org/10.1007/s10479-023-05228-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Research
Wang, Xiong
Ferreira, Fernando A. F.
Yan, Pengyu
A multi-objective optimization approach for integrated risk-based internal audit planning
title A multi-objective optimization approach for integrated risk-based internal audit planning
title_full A multi-objective optimization approach for integrated risk-based internal audit planning
title_fullStr A multi-objective optimization approach for integrated risk-based internal audit planning
title_full_unstemmed A multi-objective optimization approach for integrated risk-based internal audit planning
title_short A multi-objective optimization approach for integrated risk-based internal audit planning
title_sort multi-objective optimization approach for integrated risk-based internal audit planning
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9925941/
https://www.ncbi.nlm.nih.gov/pubmed/36818190
http://dx.doi.org/10.1007/s10479-023-05228-2
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