US 12,248,580 B2
Detecting synthetic user accounts using synthetic patterns learned via machine learning
Peter Zawadzki, San Mateo, CA (US); and Jiby Babu, Austin, TX (US)
Assigned to Chime Financial, Inc., San Francisco, CA (US)
Filed by Chime Financial, Inc., San Francisco, CA (US)
Filed on Feb. 16, 2022, as Appl. No. 17/651,390.
Prior Publication US 2023/0259631 A1, Aug. 17, 2023
Int. Cl. G06F 21/57 (2013.01); G06F 21/31 (2013.01); G06F 21/55 (2013.01); G06N 5/025 (2023.01); G06N 20/00 (2019.01)
CPC G06F 21/577 (2013.01) [G06F 21/316 (2013.01); G06F 21/554 (2013.01); G06N 5/025 (2013.01); G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
determining a plurality of account features related to a user account of a digital system;
generating, utilizing a synthetic account detection machine learning model trained using known synthetic user accounts and additional user accounts that are suspected to be synthetic user accounts based on one or more associations with the known synthetic user accounts, an indication that the user account is synthetic based on the plurality of account features; and
disabling the user account to prevent one or more actions of the user account on the digital system based on the indication that the user account is synthetic.