公开(公告)号：US20240195677A1

公开(公告)日：2024-06-13

申请号：US18415258

申请日：2024-01-17

申请人： EQUIFAX INC.

发明人： Xiao HUANG ,  Yan WANG

IPC分类号： H04L41/0631 ,  H04L41/16 ,  H04L43/04 ,  H04L43/067

CPC分类号： H04L41/064 ,  H04L41/16 ,  H04L43/04 ,  H04L43/067

摘要： Various aspects involve a lagged prediction model trained for risk assessment or other purposes. For instance, a risk assessment computing system receives a risk assessment query for a target entity and provides an input predictor record for the target entity to a lagged prediction model. The input predictor record includes a first group of lagged values from a first time-series attribute associated with the target entity. The lagged prediction model is trained by implementing a group feature selection technique configured to select the first time-series attribute as input and to deselect a second time-series attribute associated with the target entity. The risk assessment computing system computes an output risk indicator from the input predictor record and transmits the output risk indicator to a remote computing system. The output risk indicator can be used to control access by the target entity to one or more interactive computing environments.

公开(公告)号：US20220321394A1

公开(公告)日：2022-10-06

申请号：US17218161

申请日：2021-03-31

申请人： EQUIFAX INC.

发明人： Xiao HUANG ,  Yan WANG

IPC分类号： H04L12/24 ,  H04L12/26

摘要： Various aspects involve a lagged prediction model trained for risk assessment or other purposes. For instance, a risk assessment computing system receives a risk assessment query for a target entity and provides an input predictor record for the target entity to a lagged prediction model. The input predictor record includes a first group of lagged values from a first time-series attribute associated with the target entity. The lagged prediction model is trained by implementing a group feature selection technique configured to select the first time-series attribute as input and to deselect a second time-series attribute associated with the target entity. The risk assessment computing system computes an output risk indicator from the input predictor record and transmits the output risk indicator to a remote computing system. The output risk indicator can be used to control access by the target entity to one or more interactive computing environments.