Exploring Use Cases of Generative AI and Metaverse in Financial Analytics: Unveiling the Synergies of Advanced Technologies

Rangapriya Saivasan () and Madhavi Lokhande ()
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Rangapriya Saivasan: Affiliated with the University of Mysore
Madhavi Lokhande: Affiliated with the University of Mysore

International Journal of Global Business and Competitiveness, 2023, vol. 18, issue 1, No 7, 77-86

Abstract: Abstract Generative AI (GAI) refers to a branch of artificial intelligence (AI) that can enable machines to generate original content by learning patterns from existing data. The metaverse conjoins augmented, virtual and physical reality, enabling immersive interactions and vast possibilities within various ecosystems. Financial analytics encompasses many activities, including risk evaluation, financial modeling, performance evaluation, portfolio optimisation, decision support, etc. The intersection of these three phenomena can open up a slew of possibilities that hold the key to enriched data-driven experiences. This is an exploratory analysis, that uses qualitative research to unravel the potential of GAI and metaverse in financial analytics. The findings indicate that there is potential to revolutionize various aspects of financial analytics, including fraud detection, risk management, predictive analytics, and behavioral analysis. This is a pioneering effort to study the undercurrents of three very powerful technologies and the possible use cases within the finance industry. The insights from the study are used to evolve high-impact future research topics that can help companies to build a competitive edge. The intertwining of these technologies paves the way for a new era in the financial ecosystem where data-driven insights and immersive capabilities interact; this will unlock unparalleled opportunities for financial modernization and transformation for competitiveness.

Keywords: Generative AI; Metaverse; Financial analytics; Advanced technologies (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s42943-023-00082-2

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