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

Claim 0:
1. A system, comprising:
a data store server comprising:
a candidate data store that includes candidate data corresponding to a candidate;
a test center data store that includes test center data corresponding to a test center;
an exam data store that includes exam data corresponding to an exam;
an exam registration event data store that includes exam registration event data related to an exam registration event during which the candidate registered to take the exam at the test center;
a proctor data store that includes proctor data corresponding to a proctor; and
an exam delivery event data store that includes exam delivery event data related to an exam delivery event during which the candidate has taken the exam at the test center, exam delivery event being supervised by the proctor;

a model server connected to the data store server via an electronic communication network, the model server comprising:
a plurality of machine learning models comprising 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, a country machine learning model, and an aggregate machine learning model; and

a resource management server comprising a resource management processor and being connected to the data store server and the model server via the electronic communication network, the resource management processor configured to execute second computer-readable instructions for:
receiving a notification via the electronic communication network that the exam delivery event has ended;
in response to the notification, identifying the candidate, the test center, the exam, the exam registration event, and the proctor as being associated with the exam delivery event;
causing the model server to retrieve the candidate data, the test center data, the exam data, the exam registration event data, the exam delivery event data, and the proctor data from the data server;
causing the candidate machine learning model of the model server to generate a candidate risk score based on the candidate data;
causing the test center machine learning model of the model server to generate a test center risk score based on the test center data;
causing the exam machine learning model to generate an exam risk score based on the exam data;
causing the exam registration event machine learning model to generate an exam registration event risk score based on the exam registration event data;
causing the exam delivery event machine learning model to generate an exam delivery event risk score based on the exam delivery event data;
causing the proctor machine learning model to generate a proctor risk score based on the proctor data;
causing the country machine learning model to generate a country risk score based on at least a portion of the candidate data and at least a portion of the test center data;
causing the aggregate machine learning model to generate an aggregate risk score based on inputs including the candidate risk score, the test center risk score, the exam risk score, the exam registration event risk score, the exam delivery event risk score, and the proctor risk score;
receiving the aggregate risk score from the model server via the electronic communication network;
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 entity selected from the group consisting of: the exam registration event, the exam delivery event, the test center, the proctor, and the candidate.