Systems and methods for identity document fraud detection

A non-transitory computer readable storage medium storing instructions, which when executed by a computer processing system, causes the computer processing system to perform operations for fraudulent identity document detection using document images that depict identity documents, the operations comprising:

• receiving, by a server computer system, a document image for detecting whether an identity document depicted within the document image is fraudulent;
• extracting, by one or more data extractors and decoders of the server computer system, data associated with the document image to generate extracted data comprising image data extracted from the document image, image file data extracted from an image file for the document image, or a combination thereof;
• processing, by a set of machine learning models of the server computer system, corresponding subsets of the extracted data used as input to each machine learning model of the set of machine learning models, where each machine learning model in the set is trained to generate an initial score indicative of whether a subset of the extracted image data input into said each machine learning model is associated with a fraudulent identity document;
• processing, by a second machine learning model that generates a final score indicative of whether the document image depicts a fraudulent identity document, at least one or more initial scores generated by each of the set of machine learning models to generate the final score, wherein the second machine learning model is trained to generate the final score based, at least in part, on the initial scores generated by the set of machine learning models used as input to the second machine learning model;
• and
• when the final score satisfies a fraudulent document detection threshold, determining, by the server computer system, that the document image depicts a fraudulent identity document.

A server computer system for fraudulent identity document detection using document images that depict identity documents, the system comprising:

• a memory;
• and
• one or more processors coupled with the memory configured to perform operations, comprising:
• receiving a document image for detecting whether an identity document depicted within the document image is fraudulent;
• extracting, by one or more data extractors and decoders, data associated with the document image to generate extracted data comprising image data extracted from the document image, image file data extracted from an image file for the document image, or a combination thereof;
• processing, by a set of machine learning models, corresponding subsets of the extracted data used as input to each machine learning model of the set of machine learning models, where each machine learning model in the set is trained to generate an initial score indicative of whether a subset of the extracted image data input into said each machine learning model is associated with a fraudulent identity document;
• processing, by a second machine learning model that generates a final score indicative of whether the document image depicts a fraudulent identity document, at least one or more initial scores generated by each of the set of machine learning models to generate the final score, wherein the second machine learning model is trained to generate the final score based, at least in part, on the initial scores generated by the set of machine learning models used as input to the second machine learning model;
• and
• when the final score satisfies a fraudulent document detection threshold, determining that the document image depicts a fraudulent identity document.