K. Deniswara, M. Jonathan, Archie Nathanael Mulyawan, Irvan Santoso
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Analysis on The Effectiveness of Augmented Artificial Intelligence Implementation in Preventing Fraudulent Financial Statement by Utilizing Beneish M-Score Model
This study aims to analyze the effectiveness of augmented artificial intelligence implementation, which is PwC's GL.ai, in preventing fraudulent financial statement by utilizing Beneish M-Score model. The population of this study is all PwC Indonesia's clients that are listed in Indonesia Stock Exchange for the period of 2017-2021. Purposive sampling is used as sampling procedure and paired sample t-test, effect size statistic, along with statistic descriptive test are applied as the data analysis methods of this study, By utilizing Beneish M-Score model as a proxy to calculate the likelihood of manipulation in companies’ financial statements, this study concludes that the implementation of augmented artificial intelligence, namely PwC's GL.ai is an effective treatment to prevent the probability of fraudulent financial statement from occurring.
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