Data science and AI in FinTech: an overview

International Journal of Data Science and Analytics https://doi.org/10.1007/s41060-021-00278-w EDITORIAL Data science and AI in FinTech: an overview Longbing Cao1 · Qiang Yang2 · Philip S. Yu3 Received: 20 July 2021 / Accepted: 26 July 2021 © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2021 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 artificial intelligence (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. Keywords Financial technology · FinTech · Financial service · Smart FinTech · Finance · Economics · Blockchain · Data science · Artificial intelligence (AI) · Intelligent systems · Machine learning · Deep learning · Federated learning · Privacy-preserving · Modeling · Mathematics · Statistics · Ethics 1 Introduction In recent years, finance has become increasingly interactive with new-generation data science and artificial intelligence (DSAI) techniques [2,7,15,27,48,49]. In particular, FinTech (or Fintech) [13,44] is at the epicentre of synthesizing, innovating and transforming financial services, economy, technology, media, communication, and society broadly driven by DSAI techniques [8]. Here, DSAI broadly refers to (1) classic AI areas including logic, planning, knowledge representation, modeling, autonomous systems, multiagent systems, complexity science, expert system (ES), decision support system (DSS), optimization, simulation, pattern recognition, image processing, and natural language processing (NLP); (2) advanced DSAI areas including B Longbing Cao 1 University of Technology Sydney, Sydney, Australia 2 Hongkong University of Science and Technology, Hong Kong, China 3 University of Illinois at Chicago, Chicago, USA intelligent interactions and conversations, intelligent identification and authentication, privacy-preserving processing [19], advanced representation learning, advanced analytics and learning, knowledge discovery, computational intelligence, event and behavior analysis, social media/network analysis; and (3) more recent advances including deep learning [22], automated interactions, learning and responses, transfer learning [47], federated learning [56,57], humancentered computing, and brain and cognitive computing [42]. Other fundamental areas such as statistical modeling and mathematical modeling also play a critical role in enabling FinTech. In contrast, our reference to finance includes areas such as capital market, trading, banking, insurance, leading/loan, investment, wealth management, risk management, marketing, compliance and regulation, payment, contract, auditing, accounting, and digital currencies and their supporting infrastructure (including blockchain [45]), operations, services, management, security, and ethics. Economics and finance (EcoFin) are increasingly synergized with FinTech and DSAI. DSAI is the keystone enabler of the new generation of EcoFin and FinTech [15,28,35,39]. The new-generation 123 International Journal of Data Science and Analytics DSAI is reshaping or even redefining the concepts, objectives, content and tasks of EcoFin and FinTech. DSAI essentially and comprehensively transforms the way that modern economic and financial (economic-financial) businesses operate, transact, interact and collaborate with their participants (incl. consumers, markets, and regulators) and environments. DSAI nurtures new economic-financial mechanisms, models, products, services, and many tangible and intangible opportunities. As a result, DSAI not only strengthens the efficiency, cost-effectiveness, customer experience, risk mitigation, regulation, and security of existing economic-financial systems, it also innovates unprecedented and more intelligent, efficient, convenient, personalized, explainable, secure and proactive economic-financial products and services. The synthetic product of DSAI and EcoFin forms the new area of smart FinTech, as shown in Fig. 2 in [8], which presents a four-dimensional, systematic and interactive landscape of the synthesis between DSAI and EcoFin in forming smart FinTech. The landscape connects the main EcoFin businesses to the EcoFin data and repositories, the broad-based DSAI techniques, and the EcoFin business objectives. Accordingly, the family of FinTech has expanded from BankingTech, TradeTech, LendTech, InsurTech, WealthTech and PayTech to RiskTech, etc. In the rest of this paper, we discuss and summarize the main business domains and their challenges, the ecosystems of smart FinTech which substantially expand the above FinTech family, and the DSAI techniques driving smart EcoFin businesses and FinTech. A brief introduction to this selected topic on data science and AI in FinTech is then given, followed by discussion on future directions. 2 FinTech businesses and challenges Below, we briefly summarize the main businesses and challenges in smart FinTech.1 Typical applications of smart FinTech include Internet banking, mobile payments, online shopping, peer-to-peer leading, online crowdfunding projects, cryptocurrency, cross-market portfolio management, and global supply chain management. FinTech business areas: Building on DSAI techniques, these areas involve almost all aspects of an economicfinancial system and its environment and broadly all EcoFin businesses [2,8,9,39]. Here, we highlight the following major business areas in smart FinTech: – economic-financial innovations: e.g., new mechanisms and products; 1 Interested readers can refer to a comprehensive review on AI in finance in [8,9]. 123 – economic-financial markets: including products and services; – economic-financial participants: including individual and retail investors, institutions and regulators; – economic-financial behaviors: e.g., investor activities and company announcements; – economic-financial events: e.g., company mergers and financial crises; – economic-financ (...truncated)