On September 9, 2025, at 14:30 PM, the 49th Forum on Digital Technology and Economic Finance Frontiers was successfully held. The theme of the lecture was "Financial Data Analysis with Privacy Preservation", was successfully convened in Room 408, South Wenquan Building. The lecture was delivered by Professor Ning Cai, currently affiliated with The Hong Kong University of Science and Technology (Guangzhou). It was hosted by Professor Yongbin Lv, Vice Dean of the School of Finance at Zhongnan University of Economics and Law and Deputy Director of the Innovation and  Talent Base for Digital Technology and Finance. Over 30 faculty members and students from the School of Finance participated in the lecture in person.

The lecture officially commenced after a brief opening address by Professor Yongbin Lv. Starting with the increasingly prominent issue of data privacy in the era of big data, Professor Ning Cai pointed out that financial data, due to its high sensitivity, faces severe risks of privacy leakage during collection, processing, and modeling. He emphasized that privacy-preserving technologies are not only a regulatory compliance requirement but also a critical technical pillar for enhancing data trust and promoting the sustainable development of fintech.

Professor Ning Cai systematically introduced a series of privacy-preserving algorithms developed by his research team, covering key analytical stages such as data collection, statistical inference, and resampling. These algorithms, grounded in rigorously formalized privacy definitions, provide provable privacy guarantees at the theoretical level. He further demonstrated their practical applications in machine learning tasks, showing that high model prediction performance can be maintained while protecting user privacy.

Subsequently, Professor Ning Cai delved into the practical significance of privacy-preserving technologies for the financial industry. He noted that amid the rapid development of digital finance and FinTech, privacy computing not only helps institutions meet increasingly stringent data regulatory requirements but also reduces financial risks arising from data breaches and strengthens customer trust. In particular, privacy-preserving analysis holds broad application prospects in scenarios such as credit evaluation, anti-fraud, and federated modeling.

During the interactive Q&A session, faculty and students engaged in lively discussions on topics including the balance between privacy preservation and data utility, the design of noise mechanisms in differential privacy, and implementation pathways in emerging paradigms like federated learning. Participants expressed that the lecture deepened their understanding of the application of privacy computing in the financial sector, providing valuable insights for related research and policy design.

In closing, Professor Xianming Sun extended gratitude to Professor Ning Cai for his insightful sharing, emphasizing that privacy-preserving data analysis is an integral part of digital financial infrastructure. He added that efforts to advance research and collaboration in this field will continue. With this, the lecture concluded successfully.

Speaker Introduction

Ning Cai currently serves as Professor and Thrust Leader of the FinTech Thrust at The Hong Kong University of Science and Technology (Guangzhou), a National-Level High-Level Talent, and concurrently Director of the Guangzhou Key Laboratory of Cutting-Edge Research in Financial Technology. Previously, he served successively as Assistant Professor, Associate Professor, and Professor at The Hong Kong University of Science and Technology. He received his Ph.D. in Operations Research from Columbia University, and his Bachelor's and Master's degrees in Probability and Statistics from Peking University. His research interests mainly include financial technology, financial engineering, green finance, and stochastic modeling in finance and economics. He currently serves as the Area Editor for Financial Engineering of Operations Research Letters and previously served as an Associate Editor of Operations Research from 2015 to 2023. His research results have been published in several top academic journals, including Management Science, Operations Research, Mathematics of Operations Research, Mathematical Finance, and INFORMS Journal on Computing.

Frontier Forum for Digital Technology and Finance introduction

Recent years have witnessed a dramatic acceleration in a digital revolution in economic sectors and a rapid adoption of the new generation of information technologies, such as artificial intelligence, blockchain, cloud computing, big data, etc. These technologies effectively set off the digital economy. It has become a key driving force in creating global economic growth, improving the modernization level of governance capabilities, and promoting high-quality economic development in China. In particular, digital finance is the most important part of the digital economy. To explore the development direction of the cross-integration of digital technology and finance, the Innovation and Talent Base for Digital Technology and Finance is hosting the “Frontier Forum for Digital Technology and Finance”, in collaboration with the School of Finance, Wenlan School of Business, Economics School, School of Information and Safety Engineering, School of Statistics and Mathematics, School of Public Finance and Taxation of Zhongnan University of Economics and Law (ZUEL). This lecture series will invite the well-known scholars at home and abroad in digital technology, digital economy, digital finance, and other related fields as guest speakers, providing an open and cutting-edge academic exchange platform for interdisciplinary research on digital technology and finance.