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Transformational application of Artificial Intelligence and Machine learning in Financial Technologies and Financial services: A bibliometric review

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arxiv 2401.15710 v1 pith:AEL2XQ4B submitted 2024-01-28 cs.CE

classification cs.CE
keywords researchfinancialpublicationscientometricacademicactivityanalysisapplication
verification ladder T0 review T1 audit T2 compute T3 formal
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In this study, I employ a multifaceted comprehensive scientometric approach to explore the intellectual underpinnings of AI and ML in financial research by examining the publication patterns of articles, journals, authors, institutions, and nations by leveraging quantitative techniques, that transcend conventional systematic literature reviews, enabling the effective analysis of vast scientometric and bibliographic data. By applying these approaches, I identify influential works, seminal contributions, thought leaders, topical clusters, research streams, and new research frontiers, ultimately fostering a deeper understanding of the knowledge structure in AI and ML finance research by considering publication records from 2010 to 2022 from several search engines and database sources. The present study finds a marked increase in publications from 2017 to 2022, which highlights a growing interest and expanding research activity in the field, indicating its potential significance and relevance in the contemporary academic landscape.

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  1. Agentic AI Systems Applied to tasks in Financial Services: Modeling and model risk management crews

    cs.AI 2025-02 conditional novelty 4.0 of 10

    A CrewAI-based multi-agent system with human oversight built financial models and carried out model risk management checks on three public credit datasets, with results comparable to AutoML and Kaggle baselines.

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