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 single machine learning model of the server computer system, a subset the extracted data used as an input to a set of machine learning model backbones of the single machine learning model, wherein each of the set of machine learning model backbones is associated with a machine learning model head, each machine learning model backbone generating a set of intermediate signals, and each machine learning model head receiving a set of intermediate signals generated by a corresponding machine learning model backbone and generating an intermediate fraud score indicative of whether the extracted data is associated with a fraudulent identity document;
• generating, by an identity fraud head of the single machine learning model, a final score indicative of whether the document image depicts a fraudulent identity document, the final score generated by the identity fraud head processing the sets of intermediate signals generated by the machine learning model backbones;
• 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 single machine learning model, a subset the decoded image data used as an input to a set of machine learning model backbones of the single machine learning model, wherein each of the set of machine learning model backbones is associated with a machine learning model head, each machine learning model backbone generating a set of intermediate signals, and each machine learning model head receiving a set of intermediate signals generated by a corresponding machine learning model backbone and generating an intermediate fraud score indicative of whether the extracted data is associated with a fraudulent identity document;
• generating, by an identity fraud head of the single machine learning model, a final score indicative of whether the document image depicts a fraudulent identity document, the final score generated by the identity fraud head processing the sets of intermediate signals generated by the machine learning model backbones;
• and
• when the final score satisfies a fraudulent document detection threshold, determining that the document image depicts a fraudulent identity document.