AI in Finance: Challenges, Techniques and Opportunities
- URL: http://arxiv.org/abs/2107.09051v1
- Date: Tue, 20 Jul 2021 01:39:10 GMT
- Title: AI in Finance: Challenges, Techniques and Opportunities
- Authors: Longbing Cao
- Abstract summary: AI in finance broadly refers to the applications of AI techniques in financial businesses.
This review offers a comprehensive and dense roadmap of the overwhelming challenges, techniques and opportunities of AI research in finance.
- Score: 32.98512067306018
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: AI in finance broadly refers to the applications of AI techniques in
financial businesses. This area has been lasting for decades with both classic
and modern AI techniques applied to increasingly broader areas of finance,
economy and society. In contrast to either discussing the problems, aspects and
opportunities of finance that have benefited from specific AI techniques and in
particular some new-generation AI and data science (AIDS) areas or reviewing
the progress of applying specific techniques to resolving certain financial
problems, this review offers a comprehensive and dense roadmap of the
overwhelming challenges, techniques and opportunities of AI research in finance
over the past decades. The landscapes and challenges of financial businesses
and data are firstly outlined, followed by a comprehensive categorization and a
dense overview of the decades of AI research in finance. We then structure and
illustrate the data-driven analytics and learning of financial businesses and
data. The comparison, criticism and discussion of classic vs. modern AI
techniques for finance are followed. Lastly, open issues and opportunities
address future AI-empowered finance and finance-motivated AI research.
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