公开(公告)号：WO2023044177A1

公开(公告)日：2023-03-23

申请号：PCT/US2022/071168

申请日：2022-03-15

Applicant: JPMORGAN CHASE BANK, N.A.

Inventor： UPADHYAY, Sudhir ,  BEHERA, Monik Raj ,  PATEL, Palka ,  LITTLETON, Alexander ,  WASSERMAN, Sophia ,  LEE, Ker Fran ,  ELHASSAN, Ahmed ,  NATHAN, Senthil ,  PRIYADARSHINI, Sudha ,  ACHARYA, Arjun

IPC: G06N20/20 ,  G06Q20/40

Abstract: Systems and methods for generating synthetic data using federated, collaborative, privacy preserving learning models are disclosed. In one embodiment, a method for generating synthetic data from real data for use in a federated learning network may include: (1) conducting, by a backend for a first institution of a plurality of institutions in a federated learning network, a transaction comprising transaction data; (2) generating, by the backend for the first institution, local synthetic data for the transaction data using a local synthetic data generating model; (3) sharing, by the backend for the first institution, the local synthetic data with a plurality of backends for other institutions; (4) receiving, by the backend for the first institution, global synthetic data from the plurality of backends for the other institutions; and (5) training, by the backend for the first institution, a local machine learning model with the global synthetic data.