# Data science and AI in FinTech: An overview

**Authors:** Longbing Cao, Qiang Yang, Philip S. Yu  
**arXiv:** [2007.12681](https://arxiv.org/abs/2007.12681)  
**Date:** 2020-07-10  
**Summary page:** https://www.summarizepaper.com/en/paper/2007.12681v2/

## Key points

- Financial technology (FinTech) is a cornerstone of modern economies, society, and technology
- Smart FinTech harnesses data science and advanced artificial intelligence techniques to revolutionize financial services
- Led by prominent researchers Longbing Cao, Qiang Yang, and Philip S. Yu
- Smart FinTech leverages DSAI to create intelligent, automated solutions for individualized economic and financial needs
- Progress made in applying smart FinTech across key areas such as BankingTech, TradeTech, LendTech, InsurTech, WealthTech, PayTech, RiskTech, cryptocurrencies, and blockchain
- Utilizes complex system methods and quantitative analysis tools along with intelligent interactions and recognition algorithms
- Data analytics frameworks like deep learning and federated learning models are used for privacy-preserving processing
- Smart FinTech paves the way for enhanced optimization and system intelligence
- Addresses challenges in the dynamic FinTech ecosystem and emphasizes the role of DSAI techniques in enabling efficient solutions
- Outlines future research directions for smart FinTech to integrate cutting-edge DSAI methodologies into financial systems

## Summary

Financial technology (FinTech) has become a cornerstone of modern economies, society, and technology. It is driving innovation and transformation across various sectors. Smart FinTech represents the next evolution in this field by harnessing the power of data science and advanced artificial intelligence (DSAI) techniques to revolutionize financial services. Led by prominent researchers Longbing Cao, Qiang Yang, and Philip S. Yu, this study delves into the realm of smart FinTech. It explores how it leverages DSAI to create intelligent, automated solutions that cater to individualized economic and financial needs. The research highlights significant progress made in applying smart FinTech across key areas such as BankingTech, TradeTech, LendTech, InsurTech, WealthTech, PayTech, RiskTech, cryptocurrencies, and blockchain. By utilizing complex system methods and quantitative analysis tools along with intelligent interactions and recognition algorithms; data analytics frameworks like deep learning and federated learning models for privacy-preserving processing; smart FinTech is paving the way for enhanced optimization and system intelligence. The authors present a comprehensive overview of smart financial businesses within the dynamic FinTech ecosystem. They also address associated challenges and emphasize the critical role played by DSAI techniques in enabling efficient and personalized solutions that meet diverse consumer demands. Furthermore, they outline future research directions for smart FinTech that aim to further integrate cutting-edge DSAI methodologies into financial systems. Overall, It underscores the importance of continuous innovation in this space to drive sustainable growth and efficiency in financial services while ensuring enhanced customer experiences in an increasingly digital world.