Systems and processes for bias removal in a predictive performance model

A method, comprising:

• receiving, via one or more of at least one hardware processor, a set of input data individually describing a particular asset associated with an entity;
• receiving, via one or more of the at least one hardware processor, a set of inputs individually responsive to a respective subset of a plurality of queries for a particular user;
• generating, via one or more of the at least one hardware processor, a predictive model based on the set of input data;
• calculating, via one or more of the at least one hardware processor, a predictive outcome for the particular user by applying the predictive model to the set of inputs;
• identifying, via one or more of the at least one hardware processor, a target score impacting the predictive outcome for the particular user;
• and
• assigning, via one or more of the at least one hardware processor, a training program to the particular user corresponding to the target score.

A non-transitory computer-readable medium embodying a program that, when executed by at least one hardware processor, causes the at least one hardware processor to:

• receive a set of input data individually describing a particular asset associated with an entity;
• receive a set of inputs individually responsive to a respective subset of a plurality of queries for a particular user;
• generate a predictive model based on the set of input data;
• calculate a predictive outcome for the particular user by applying the predictive model to the set of inputs;
• identify a target score impacting the predictive outcome for the particular user;
• and
• assign a training program to the particular user corresponding to the target score.