Paper 2023/400

Prime Match: A Privacy-Preserving Inventory Matching System

Antigoni Polychroniadou, J.P. Morgan AI Research
Gilad Asharov, Bar-Ilan University
Benjamin Diamond
Tucker Balch, J.P. Morgan AI Research
Hans Buehler
Richard Hua, J.P. Morgan
Suwen Gu, J.P. Morgan
Greg Gimler
Manuela Veloso, J.P. Morgan AI Research

Inventory matching is a standard mechanism for trading financial stocks by which buyers and sellers can be paired. In the financial world, banks often undertake the task of finding such matches between their clients. The related stocks can be traded without adversely impacting the market price for either client. If matches between clients are found, the bank can offer the trade at advantageous rates. If no match is found, the parties have to buy or sell the stock in the public market, which introduces additional costs. A problem with the process as it is presently conducted is that the involved parties must share their order to buy or sell a particular stock, along with the intended quantity (number of shares), to the bank. Clients worry that if this information were to “leak” somehow, then other market participants would become aware of their intentions and thus cause the price to move adversely against them before their transaction finalizes. We provide a solution, Prime Match, that enables clients to match their orders efficiently with reduced market impact while maintaining privacy. In the case where there are no matches, no information is revealed. Our main cryptographic innovation is a two-round secure linear comparison protocol for computing the minimum between two quantities without preprocessing and with malicious security, which can be of independent interest. We report benchmarks of our Prime Match system, which runs in production and is adopted by a large bank in the US -- J.P. Morgan. The system is designed utilizing a star topology network, which provides clients with a centralized node (the bank) as an alternative to the idealized assumption of point-to-point connections, which would be impractical and undesired for the clients to implement in reality. Prime Match is the first secure multiparty computation solution running live in the traditional financial world.

Note: This is the full version of the USENIX Security '23 paper v2: fixed reference from the main body to Appendix I

Available format(s)
Cryptographic protocols
Publication info
Published elsewhere. USENIX Security Symposium 2023
MPCsecure comparisonauctionsapplicationfinance
Contact author(s)
antigonipoly @ gmail com
Gilad Asharov @ biu ac il
tucker balch @ jpmchase com
2023-04-06: revised
2023-03-21: received
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      author = {Antigoni Polychroniadou and Gilad Asharov and Benjamin Diamond and Tucker Balch and Hans Buehler and Richard Hua and Suwen Gu and Greg Gimler and Manuela Veloso},
      title = {Prime Match: A Privacy-Preserving Inventory Matching System},
      howpublished = {Cryptology ePrint Archive, Paper 2023/400},
      year = {2023},
      note = {\url{}},
      url = {}
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