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Design Expert System for Auditing Financial Accounts

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  • Khalid Al-Bakoaa, Abdul Rahman

Abstract

This paper presents an account audition system based on (Expert System), an artificial intelligence technique. This paper presents an account audition system based on (Expert System), an artificial intelligence technique. Since the limited studies dealt with using artificial intelligence in a general and expert system in auditing accounts in Iraq (within the researcher's knowledge limits), the researcher tried to tackle these two subjects in his current study to apply them in reality. The expert system that is designed within rules and facts of knowledge base analyzes, audits, and extracts data from financial tables within accounting distributions consist included such as names of accounts and their numbers whose values are represented within cost centers represented by certain symbolic numbers that differ from one institution to another and obtaining the required results by using an applicable knowledge base. The Proposed system approach offers a practical method of auditing and distributing the required data by using the expert systems manually by many auditors. Using the expert system led to lessening time and effort taken to make audits and the accuracy of obtaining results.

Suggested Citation

  • Khalid Al-Bakoaa, Abdul Rahman, 2022. "Design Expert System for Auditing Financial Accounts," Technium Business and Management, Technium Science, vol. 2(1), pages 45-53.
    • Handle: RePEc:tec:busine:v:2:y:2022:i:1:p:45-53
    DOI: 10.47577/business.v2i1.6141
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    References listed on IDEAS

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    1. Gray, Glen L. & Chiu, Victoria & Liu, Qi & Li, Pei, 2014. "The expert systems life cycle in AIS research: What does it mean for future AIS research?," International Journal of Accounting Information Systems, Elsevier, vol. 15(4), pages 423-451.
    2. Ivy Munoko & Helen L. Brown-Liburd & Miklos Vasarhelyi, 2020. "The Ethical Implications of Using Artificial Intelligence in Auditing," Journal of Business Ethics, Springer, vol. 167(2), pages 209-234, November.
    3. Ricardo Carreño & Verónica Aguilar & Daniel Pacheco & Marco Antonio Acevedo & Wen Yu & María Elena Acevedo, 2019. "An IoT Expert System Shell in Block-Chain Technology with ELM as Inference Engine," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(01), pages 87-104, January.
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    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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