EUROPEAN JOURNAL OF ACCOUNTING, FINANCE & BUSINESS

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ISSN: 2344 - 102X

ISSN-L: 2344 - 102X



 

Article from Volume 11, Number 3, Year 2023

ACCOUNTING FRAUD - A BIBLIOMETRIC ANALYSIS
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Author(s): Alexandru Anichiti
DOI: 10.4316/EJAFB.2023.11321
Abstract: Accounting fraud is a big problem globally. Countries lose significant amounts of tax money because companies do no show their real profits and investors lose significant amounts of money when companies overstate their financials. New technologies, such as machine learning, artificial intelligence (AI), blockchain and the automation of the accounting process will help governments to prevent and discover accounting fraud more easily. This study is a bibliometric analysis on accounting fraud that can offer insights into how accounting fraud is perceived globally, what countries take it more seriously, and how could accounting fraud be prevented or more easily discovered when it occurs.
Keywords: Accounting Fraud; Bibliometric Analysis, Fraud Detection; Economic Crime; Financial Records.
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