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Using Artificial Intelligence and Metaverse Techniques to Reduce Earning Management

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Beyond Reality: Navigating the Power of Metaverse and Its Applications (IMDC-IST 2024)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 895))

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Abstract

This study aims to demonstrate the role of artificial intelligence and metaverse techniques, mainly logistical Regression, in reducing earnings management in Iraqi private banks. Synthetic intelligence approaches have shown the capability to detect irregularities in financial statements and mitigate the practice of earnings management. In contrast, many privately owned banks in Iraq historically relied on manual processes involving pen and paper for recording and posting financial information in their accounting records. However, the banking sector in Iraq has undergone technological advancements, leading to the Automation of most banking operations. Conventional audit techniques have become outdated due to factors such as the accuracy of data, cost savings, and the pace of business completion. Therefore, relying on auditing a large volume of financial data is insufficient. The Metaverse is a novel technological advancement seeking to fundamentally transform corporate operations and interpersonal interactions. Metaverse has implications for auditing and accounting practices, particularly concerning a company’s operational and financial aspects. Economic units have begun to switch from traditional methods of registration and posting to using software for financial operations to limit earnings management. Therefore, this research proposes applying one of the Data Mining techniques, namely the logistical regression technique, to reduce earning management in a sample of Iraqi private banks, including (11) banks. Accounting ratios were employed, followed by Logistic Regression, to achieve earnings management within the proportions.

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Authors and Affiliations

  1. Department of Accounting, University of Baghdad, Baghdad, Iraq

    Yahia Ali Kadhim & Safaa Ahmed Mohammed Al Ani

Authors
  1. Yahia Ali Kadhim
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  2. Safaa Ahmed Mohammed Al Ani
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Correspondence to Yahia Ali Kadhim .

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Editors and Affiliations

  1. The British University in Dubai, Dubai, United Arab Emirates

    Mostafa Al-Emran

  2. Southern Technical University, Basrah, Iraq

    Jaber H. Ali

  3. Faculty of Economics, University Niccolò Cusano, Rome, Italy

    Marco Valeri

  4. Southern Technical University, Basrah, Iraq

    Alhamzah Alnoor

  5. Southern Technical University, Basrah, Iraq

    Zaid Alaa Hussien

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Kadhim, Y.A., Al Ani, S.A.M. (2023). Using Artificial Intelligence and Metaverse Techniques to Reduce Earning Management. In: Al-Emran, M., Ali, J.H., Valeri, M., Alnoor, A., Hussien, Z.A. (eds) Beyond Reality: Navigating the Power of Metaverse and Its Applications. IMDC-IST 2024. Lecture Notes in Networks and Systems, vol 895. Springer, Cham. https://doi.org/10.1007/978-3-031-51716-7_12

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