Misappropriation Asset In Banking Industry: A Bibliometric Analysis Approach

Riska Ayu Futika Hanum, Tarjo Tarjo, Rita Yuliana

Abstract


This research aims to examine asset misappropriation in the banking industry by using artificial intelligence to detect fraudulent acts. This research is a bibliometric-based Systematic Literature Review (SLR) related to asset misappropriation detection. The research sample consisted of 20 articles obtained from the Emerald Insight database for the period 2019 – 2024. The research results show that there is a lot of corruption in asset misappropriation in the banking industry and money laundering is the most popular asset misappropriation technique used by researchers. Then fraud mitigation and forensic accounting are popular steps taken to prevent asset misuse in the banking industry. The findings show that there are artificial intelligence tools in detecting acts of asset misappropriation in the banking industry, but it has not been explained whether these tools are able to reduce fraud, especially in asset misappropriation. This research provides novelty in the use of artificial intelligence in detecting asset misappropriation in the banking industry, as well as steps taken to prevent asset misappropriation.

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References


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