Enhanced validity modeling using machine-learning techniques

Abstract

The present disclosure generally relates to a primary load management system configured to execute machine learning and artificial intelligence techniques to generate predictions of access-right requests that are or are likely to be invalid before the access-right requests are processed for assignment to users or user devices. More particularly, the present disclosure relates to systems and methods that collect a data set representing characteristics of user devices as the user devices interact with various systems of the primary load management system, train a machine-learning model to predict invalid access-right requests using the collected data set, and execute the trained machine-learning model to process new access-right requests to generate predictions as to whether or not the new access-right requests are invalid.