Abstract: Private Set Intersection (PSI) is a research hotspot in the field of privacy-preserving computation. As a common pre-step for the data cooperation among different institutions or companies, it has highly practical value in the realistic scenarios. In this paper, we first introduce the classification and the relevant technologies of PSI. Secondly, we explain a comprehensive implementation process of PSI based on blind signature as an example. Then we present the use scenarios of PSI in finance industry, including financial joint modeling, financial joint statistics, financial joint marketing and financial joint operation analysis, etc. , for revealing the research and practical value of PSI. Finally, this paper analyzes and discusses the technical challenges and some research directions of current PSI technology.

Key words: private set intersection, secure multi-party computation, federated learning, privacy preserving computing, blind signature, oblivious transfer, homomorphic encryption