US 2026/0100084 A1 · DOCUMENT FRAUD PREVENTION SYSTEM

Abstract

Disclosed are various embodiments for verification of legitimate documents and identification of fraudulent documents using machine learning and artificial intelligence. A computing device can identify with a machine learning algorithm one or more fields from within an unverified document associated with an entity. The computing device can identify a verified document corresponding to the unverified document based at least in part on the entity. Then, the computing device can compare the one or more unverified fields of the unverified document to one or more verified fields of the verified document. Finally, the computing device can determine whether the unverified document is fraudulent based at least in part on the comparison of the one or more unverified fields to the one or more verified fields.

Claims20

Dependent claims

A system, comprising:

a computing device comprising a processor and a memory;
and
machine-readable instructions stored in the memory that, when executed by the processor, cause the computing device to at least:
identify with a machine learning algorithm one or more unverified fields from within an unverified document associated with an entity;
identify a verified document corresponding to the unverified document based at least in part on the entity;
compare the one or more unverified fields of the unverified document to one or more verified fields of the verified document;
and
determine whether the unverified document is fraudulent based at least in part on a comparison of the one or more unverified fields to the one or more verified fields.

5 more elements

A method, comprising:

performing, by a machine learning algorithm on a computing device, a metadata analysis of an unverified document associated with an entity, the metadata analysis identifying a first number of fraud indicators;
identifying, by the machine learning algorithm, a verified document associated with the entity, the verified document corresponding to the unverified document;
identifying, by the machine learning algorithm, a second number of fraud indicators from within the unverified document based at least in part on a comparison of the unverified document to the verified document;
and
flagging, by the machine learning algorithm, the unverified document as fraudulent based at least in part on the first number of fraud indicators and the second number of fraud indicators exceeding a threshold.

2 more elements

A non-transitory, computer-readable medium, comprising machine-readable instructions that, when executed by a processor of a computing device, cause the computing device to at least:

perform a metadata analysis of an unverified document associated with an entity, the metadata analysis identifying a first number of fraud indicators;
identify a verified document associated with the entity, the verified document corresponding to the unverified document;
identify a second number of fraud indicators from within the unverified document based at least in part on a comparison of the unverified document to the verified document;
and
flag the unverified document as fraudulent based at least in part on the first number of fraud indicators and the second number of fraud indicators exceeding a threshold.

2 more elements

Dependencies are inferred from the claim text.

Document fraud prevention system

Life of this patent

Document fraud prevention system

Life of this patent

Abstract

Claims20