Patent ID: 11875242
Assignee: NCS PEARSON, INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 4:
5. A system comprising:
a data store server comprising a plurality of data stores, the plurality of data stores configured to store sets of entity data corresponding to a plurality of entities related to an exam delivery event, wherein the plurality of entities includes at least one of a candidate, an exam, a test center, an exam registration event during which the candidate interacts with the system to register to take the exam at the test center, a proctor, or the exam delivery event during which the exam is administered to the candidate under supervision of the proctor;
a model server comprising a model memory storing a plurality of entity machine learning models and an aggregate machine learning model, wherein the plurality of entity machine learning models includes at least one of a candidate machine learning model, a test center machine learning model, an exam machine learning model, an exam registration event machine learning model, an exam delivery event machine learning model, a proctor machine learning model, or a country machine learning model; and
a resource management server comprising a resource management processor configured to execute computer-readable instructions for:
receiving a notification that the exam delivery event has ended;
in response to the notification, identifying at least three entities of the plurality of entities that are related to the exam delivery event;
determining, based on the notification, that risk analysis should be performed for the at least three entities;
causing the model server to retrieve at least three sets of entity data respectively corresponding to the at least three entities from the data store server;
causing at least three machine learning models of the plurality of entity machine learning models of the model server to generate entity risk scores corresponding to each of the at least three entities;
causing the aggregate machine learning model of the model server to generate an aggregate risk score based on the entity risk scores;
receiving the aggregate risk score from the model server;
determining that the aggregate risk score exceeds a predetermined threshold; and
modifying a database entry associated with the exam delivery event, in response to determining that the aggregate risk score exceeds the predetermined threshold, to trigger a fraud investigation of at least one of the at least three entities.