Navigating the frontier of finance: a scoping review of generative AI applications and implications

Ahmad Haidar and Ahmad Abbass
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Ahmad Haidar: LITEM - Laboratoire en Innovation, Technologies, Economie et Management (EA 7363) - UEVE - Université d'Évry-Val-d'Essonne - Université Paris-Saclay - IMT-BS - Institut Mines-Télécom Business School - IMT - Institut Mines-Télécom [Paris], IMT-BS - MMS - Département Management, Marketing et Stratégie - TEM - Télécom Ecole de Management - IMT - Institut Mines-Télécom [Paris] - IMT-BS - Institut Mines-Télécom Business School - IMT - Institut Mines-Télécom [Paris]
Ahmad Abbass: MU - Al Maaref University [Liban]

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Abstract: Recent technological advancements and intense competitive pressures have spurred the rapid integration of artificial intelligence (AI) into the financial sector. This trend is further amplified with the advent of generative AI (GAI), representing a significant advancement in AI technology with its wide-ranging applications in finance. This scoping review chapter delves into the evolution of GAI and its burgeoning role in financial analysis, management, and strategy. While GAI offers significant opportunities for business and financial entities, it also entails inherent risks that necessitate prudent consideration. These risks encompass embedded biases, outcome opacity, privacy concerns, performance robustness, unique cybersecurity threats, and the potential to create novel sources and transmission channels of systemic risks, which could impact financial sector stability. The chapter explores regulatory, ethical, and user-centric perspectives in AI-driven finance alongside technological innovations and applications. Methodologically, this review employs a structured approach to identify relevant studies, chart data, and collate, summarize, and report results. The findings highlight the critical balance between leveraging GAI for its benefits and mitigating its risks to ensure responsible use in the financial realm by adhering to ethical principles such as public participation, regulatory compliance, and a user-centric approach. This chapter offers valuable insights for policymakers, financial professionals, AI developers, and academics, guiding them in understanding the complexities of GAI in finance and informing strategies for responsible implementation.

Keywords: Finance; Financial analysis; Generative AI; Risk mitigation; Scoping review (search for similar items in EconPapers)
Date: 2025-01-21
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Published in Pethuru Raj Chelliah; Pushan Kumar Dutta; Abhishek Kumar; Ernesto D.R. Santibanez Gonzalez; Mohit Mittal; Sachin Gupta. Generative Artificial Intelligence in Finance: Large Language Models, Interfaces, and Industry Use Cases to Transform Accounting and Finance Processes, Scrivener Publishing ; Wiley, pp.215-252, 2025, Fintech in Sustainable Digital Society, 978-1-394-27104-7. ⟨10.1002/9781394271078.ch12⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04969000

DOI: 10.1002/9781394271078.ch12

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