Semantic Scholar Open Access 2021 381 sitasi

AI in Finance: Challenges, Techniques, and Opportunities

Longbing Cao

Abstrak

AI in finance refers to the applications of AI techniques in financial businesses. This area has attracted attention for decades, with both classic and modern AI techniques applied to increasingly broader areas of finance, economy, and society. In contrast to reviews on discussing the problems, aspects, and opportunities of finance benefited from specific or some new-generation AI and data science (AIDS) techniques or the progress of applying specific techniques to resolving certain financial problems, this review offers a comprehensive and dense landscape of the overwhelming challenges, techniques, and opportunities of AIDS research in finance over the past decades. The challenges of financial businesses and data are first outlined, followed by a comprehensive categorization and a dense overview of the decades of AIDS research in finance. We then structure and illustrate the data-driven analytics and learning of financial businesses and data. A comparison, criticism, and discussion of classic versus modern AIDS techniques for finance follows. Finally, the open issues and opportunities to address future AIDS-empowered finance and finance-motivated AIDS research are discussed.

Penulis (1)

L

Longbing Cao

Format Sitasi

Cao, L. (2021). AI in Finance: Challenges, Techniques, and Opportunities. https://doi.org/10.1145/3502289

Akses Cepat

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Informasi Jurnal
Tahun Terbit
2021
Bahasa
en
Total Sitasi
381×
Sumber Database
Semantic Scholar
DOI
10.1145/3502289
Akses
Open Access ✓