US 12,388,867 B2
Systems and methods for identifying electronic accounts based on near real time machine learning in an electronic network
Rajeev Bahl, Bear, DE (US)
Assigned to BANK OF AMERICA CORPORATION, Charlotte, NC (US)
Filed by BANK OF AMERICA CORPORATION, Charlotte, NC (US)
Filed on Aug. 9, 2023, as Appl. No. 18/231,962.
Prior Publication US 2025/0055878 A1, Feb. 13, 2025
Int. Cl. H04L 9/40 (2022.01)
CPC H04L 63/1483 (2013.01) [H04L 63/102 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system for identifying electronic accounts based on near real time machine learning in an electronic network, the system comprising:
a processing device;
a non-transitory storage device containing instructions when executed by the processing device, causes the processing device to perform the steps of:
identify at least one data storage component, wherein at least one data store component comprises data associated with an at least one application;
determine at least one current requirement of the data, wherein the at least one current requirement comprises at least one of an objective priority, a driver of propensity, or a progression requirement;
receive at least one data segment from the data storage component associated with the at least one application;
collect at least one current element from the at least one data segment;
reformat and aggregate the at least one current element and link the at least one current element to a unique entity identifier;
apply a trained machine learning model to the at least one current element;
generate, by the trained machine learning model a new data segment, wherein the new data segment is based on the at least one current element of the new data segment; and
generate a propensity score based on at least one of the unique entity identifier, the at least one current element, or the at least one new data segment,
wherein the propensity score is in relation to at least one the objective priority, the driver of propensity, or the progression requirement, and
wherein the propensity score is based on the at least one data segment associated with the unique entity identifier and the at least one new data segment.