System and method of knowledge graph based ID anomaly detection in order to determine if the anomaly is associated with ID fraud

A method of performing identification document (ID) anomaly detection using a knowledge graph, comprising:

• generating a hierarchical multidimensional view of identification documents based at least in part on human curated expert knowledge;
• and
• providing a knowledge graph base having a knowledge graph schema to define, for each ID type of a plurality of ID types, node labels for image fragments, features of image fragments, relationships between nodes, and select an execution workflow for creating fragments of images, assigning fragment processing functions to the image fragments, and assigning evaluation functions for processed image fragments;
• receiving an image of an ID and a class label for the ID associated with an ID type;
• initiating a workflow for a received ID, the workflow selected based on a least one attribute of the ID;
• performing a fragment creation process to break down the image of the received ID under test into a set of image fragments according to the workflow;
• processing features of the image fragments according to fragment processing functions assigned to the image fragments according to the workflow;
• evaluating results of the processed image fragments based on the evaluation functions assigned to the processed image fragments according to the workflow;
• and
• reporting whether the ID has an anomaly associated with ID fraud, wherein a decision includes comparing the evaluation functions against a gold standard of a valid image.