Review of Data Science and AI in Finance

Abstract

According to Business Insider, computerized reasoning software would save banks and financial institutions $447 billion by 2023. According to Forbes, 70% of financial firms are using AI to predict revenue events, adjust financial evaluations, and detect extortion. According to Forbes, 54 percent of financial aid organizations with 5,000 or more employees use artificial intelligence. The recent FinTech surge shows the years of important breakthroughs and potentials of AI in creating a finance and society system that makes sense. In AI, data technology, economics, finance, and other relevant research processes and commercial domain names, AI-empowered economy and finance has been a suggested and area that is becoming increasingly vital. The new-generation AI, Data Machine, and technology learning, which are fundamentally and seamlessly transforming the eyesight, Missions, Objectives, paradigms, theories, approaches, tools, and social areas of economics and driving and finance smart FinTech, are adding to this long history of finance. AI continues to authorize more complicated mechanisms, such as economic financial products, replicas, facilities, organizations, and applications that are more complex than customized and enhanced, safe and fresher normal and other mechanisms. This review highlights the long-term study of AI in finance and focuses on establishing a complete, multidimensional, and problem-driven economic-financial research linked with the roles and research instructions of both classic and modern AI in finance.