US 12,314,352 B2
Using machine learning for collision detection to prevent unauthorized access
Vijaya L. Vemireddy, Plano, TX (US); Mark Odiorne, Waxhaw, NC (US); and David Smiddy, Chadds Ford, PA (US)
Assigned to Bank of America Corporation, Charlotte, NC (US)
Filed by Bank of America Corporation, Charlotte, NC (US)
Filed on Jun. 22, 2023, as Appl. No. 18/212,859.
Prior Publication US 2024/0427856 A1, Dec. 26, 2024
Int. Cl. G06F 21/30 (2013.01)
CPC G06F 21/30 (2013.01) 18 Claims
OG exemplary drawing
 
1. A computing platform comprising:
at least one processor;
a communication interface communicatively coupled to the at least one processor; and
memory storing computer-readable instructions that, when executed by the at least one processor, cause the computing platform to:
train a synthetic identity detection model, wherein training the synthetic identity detection model configures the synthetic identity detection model to detect synthetic identity information;
receive identity information corresponding to an identity generation request;
input, into the synthetic identity detection model, the identity information, wherein inputting the identity information into the synthetic identity detection model causes the synthetic identity detection model to:
identify at least one collision between the received identity information and stored identity information, and
generate, based on the at least one collision, a synthetic identity score indicating a likelihood that the received identity information corresponds to a request to generate a synthetic identity;
compare the synthetic identity score to at least one synthetic identity detection threshold;
based on detecting that the synthetic identity score meets or exceeds a first synthetic identity detection threshold of the at least one synthetic identity detection thresholds, send, to a client device with a known association to a legitimate user corresponding to the identity information, a prompt for identity confirmation information, wherein the identity confirmation information comprises biometric information for the legitimate user;
receive the identity confirmation information;
update, using the synthetic identity detection model and based on the identity confirmation information, the synthetic identity score; and
based on identifying that the synthetic identity score meets or exceeds the at least one synthetic identity detection threshold, execute one or more security actions.