US 12,323,454 B2
Fraud networks
Jacob M. Bellman, Fairfield, OH (US); Dan M. Hayden, Mesa, AZ (US); Abhishek Chambe Venkatesh Murthy, Chicago, IL (US); John M. Kohoutek, Chicago, IL (US); and Klementina Nikov, Des Plaines, IL (US)
Assigned to Early Warning Services, LLC, Scottsdale, AZ (US)
Filed by Early Warning Services, LLC, Scottsdale, AZ (US)
Filed on Jan. 24, 2023, as Appl. No. 18/100,982.
Application 18/100,982 is a continuation in part of application No. 17/824,688, filed on May 25, 2022.
Claims priority of provisional application 63/302,926, filed on Jan. 25, 2022.
Claims priority of provisional application 63/192,979, filed on May 25, 2021.
Prior Publication US 2023/0164169 A1, May 25, 2023
Int. Cl. H04L 29/06 (2006.01); H04L 9/40 (2022.01); H04L 41/16 (2022.01)
CPC H04L 63/1433 (2013.01) [H04L 41/16 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method of determining a fraud network using one or more processors comprising:
receiving labeled data including address information corresponding to a first address;
determining, using an address risk machine learning model, a first address risk score associated with the first address;
identifying a first entity associated with the first address based on the first address risk score being greater than a threshold value;
determining at least one of a second address or a second entity associated with the first entity;
generating a fraud network profile including the first address, and the at least one of the second address or second entity; and
transmitting a notification to user device associated with the generated fraud network profile.