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International Journal of Data Science and Analytics
Article . 2021 . Peer-reviewed
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SSRN Electronic Journal
Article . 2021 . Peer-reviewed
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Article . 2020
License: arXiv Non-Exclusive Distribution
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Article . 2021
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Data science and AI in FinTech: An overview

Authors: Longbing Cao; Qiang Yang 0001; Philip S. Yu;

Data science and AI in FinTech: An overview

Abstract

Financial technology (FinTech) has been playing an increasingly critical role in driving modern economies, society, technology, and many other areas. Smart FinTech is the new-generation FinTech, largely inspired and empowered by data science and new-generation AI and (DSAI) techniques. Smart FinTech synthesizes broad DSAI and transforms finance and economies to drive intelligent, automated, whole-of-business and personalized economic and financial businesses, services and systems. The research on data science and AI in FinTech involves many latest progress made in smart FinTech for BankingTech, TradeTech, LendTech, InsurTech, WealthTech, PayTech, RiskTech, cryptocurrencies, and blockchain, and the DSAI techniques including complex system methods, quantitative methods, intelligent interactions, recognition and responses, data analytics, deep learning, federated learning, privacy-preserving processing, augmentation, optimization, and system intelligence enhancement. Here, we present a highly dense research overview of smart financial businesses and their challenges, the smart FinTech ecosystem, the DSAI techniques to enable smart FinTech, and some research directions of smart FinTech futures to the DSAI communities.

Country
China (People's Republic of)
Keywords

FOS: Computer and information sciences, Economics, Computer Science - Artificial Intelligence, Federated learning, Artificial intelligence (AI), Data science, FinTech, FOS: Economics and business, Blockchain, Privacy-preserving, Machine learning, Intelligent systems, Ethics, Financial service, Statistics, Modeling, Deep learning, Artificial Intelligence (cs.AI), Financial technology, Smart FinTech, Quantitative Finance - General Finance, General Finance (q-fin.GN), Finance, Mathematics

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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    162
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 1%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
162
Top 1%
Top 1%
Top 1%
Green
bronze