AI in Finance: A Systematic Literature Review

Research on Artificial Intelligence (AI) in finance has been growing significantly alongside its increasing implementation in the financial sector. This development raises questions about the specific financial areas and AI technology applications that are most frequently explored as research topics within AI in finance. This study aims to address these questions by employing a systematic literature review (SLR) method, analyzing journal articles indexed in Scopus (Q1–Q4) and published between 2020 and 2024. A search conducted using Publish or Perish on the Scopus database identified 496 records, which were subsequently filtered to 94 articles using the PRISMA protocol. The selected articles were examined through bibliometric analysis using VOSviewer, followed by content analysis. The findings reveal that fintech and risk management are the most frequently discussed financial areas in AI in finance research. Moreover, machine learning emerges as the most commonly addressed AI technology application in this domain. Notably, the combination of machine learning and risk management stands out as the most prominent research topic.

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Publication Details

Journal
Proceeding International Collaborative Conference on Multidisciplinary Science
Published
2024-12-05
DOI
https://doi.org/10.70062/iccms.v1i2.66
Primary Topic
Impact of AI and Big Data on Business and Society
Type
article
Field-Weighted Citation Impact
0.00
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article

AI in Finance: A Systematic Literature Review

Rustandi Rustandi, Andi Harmoko Arifin
Proceeding International Collaborative Conference on Multidisciplinary Science
Impact of AI and Big Data on Business and Society
article

AI in Finance: A Systematic Literature Review

Rustandi Rustandi, Andi Harmoko Arifin
article en

Abstract

Research on Artificial Intelligence (AI) in finance has been growing significantly alongside its increasing implementation in the financial sector. This development raises questions about the specific financial areas and AI technology applications that are most frequently explored as research topics within AI in finance. This study aims to address these questions by employing a systematic literature review (SLR) method, analyzing journal articles indexed in Scopus (Q1–Q4) and published between 2020 and 2024. A search conducted using Publish or Perish on the Scopus database identified 496 records, which were subsequently filtered to 94 articles using the PRISMA protocol. The selected articles were examined through bibliometric analysis using VOSviewer, followed by content analysis. The findings reveal that fintech and risk management are the most frequently discussed financial areas in AI in finance research. Moreover, machine learning emerges as the most commonly addressed AI technology application in this domain. Notably, the combination of machine learning and risk management stands out as the most prominent research topic.

Proceeding International Collaborative Conference on Multidisciplinary ScienceVol. 1(2)
Indonesia Open University (ID)
Openalex Percentile: Top 65%
Impact of AI and Big Data on Business and Society
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