Collaborative Detection of Malicious Clients for Financial Institutions using Multi-Party Computation

Abstract

Financial institutions have a large responsibility when it comes to detecting and preventing financial crime. However, dedicated tools to aid in financial crime detection have more demand than supply. The combination of regulatory restrictions with regards to sharing client information between financial institutions and a lack of dedicated tools for financial crime detection results in a flawed system that allows criminals to evade detection and easily continue their activities by moving between institutions. This paper answers the question: How can privacy-preserving data sharing methods enable collaborative detection of malicious clients among financial institutions? Multi-Party Private Set Intersection (MPSI) allows multiple parties to intersect their respective datasets, without revealing any data to the other parties that are not in the intersection. A special case of MPSI is Threshold Multi-Party Private Set Intersection (T-MPSI), where given a threshold T, an item is only included if T or more parties hold that item. This paper implements a new version, Flagged Threshold Private Set Intersection (FT-MPSI), that adds a label to each item, where the label indicates if the client has been flagged as malicious - accused or convicted of financial crime. To be included in the intersection, the item must now also be identified by at least one party as malicious. The final result of the intersection is revealed to the computing party and can be shared with the parties holding the original items while no other information is leaked. The runtime performance of the FT-MPSI protocol is compared to that of the T-MPSI protocol. FT-MPSI is slower by a constant factor of approximately 2, compared to T-MPSI, it scales linearly to the number of parties and size of the sets of the input. FT-MPSI is a practical solution for financial institutions to use in financial crime detection.