Jumio Corporation

Attila Balogh

Thomas Krump

Daryl Huff

Stuart Wells

Anshuman Vikram Singh

Reinhard Hochrieser

Philipp Pointner

Lukas Bayer

Ronald Streicher

Labhesh Patel

Lukas Danzer-Stauffer

Alix Melchy

Radu Rogojanu

Thomas Pasterk

Jeetendra Kaul

A multi-modal verification and authentication system can be used for customer onboarding and repeat customer access/interactions. The multi-modal verification and authentication system provides very low friction, highly secure, verification and authentication system. The multi-modal verification and authentication system is scalable and adaptable to perform serval types of identity verification which results in a high degree of certainty and accuracy for identification and authorization. The multi-modal verification and authentication system includes a multi-modal biometric identifier, a multiple multi-modal liveness detector and a multi-modal anti-spoofing detector used in user registration authentication processes.

Multi-modal verification and authentication system and methods

The disclosure includes a system and method for obtaining a document specification in an electronic format, wherein the document specification is associated with a first document, and describes features present in valid instances of the first document; determining a set of labels describing the first document from the document specification; obtaining one or more digital images of at least one valid instance of the first document from the document specification; obtaining information describing a set of bounding boxes resulting from application, to the one or more images of the least one valid instance of the first document, of one or more of optical character recognition and object detection; generating a set of derived checks based on the set of bounding boxes; and generating a document assembly object describing valid instances of the document and the set of derived checks usable to determine validity of a document under test.

Generating a document assembly object and derived checks

The disclosure includes a system and method to obtain at least one image of a document under test, wherein valid instances of the document under test include at least one perforation-based three-dimensional security feature; obtain a first image snippet from the document under test, the first image snippet corresponding to at least a first portion of the perforation-based three-dimensional security feature present in the valid instances of the document; analyze the perforation-based three-dimensional security feature for one or more characteristics; and modify a likelihood that the document under test is accepted as valid, or rejected as invalid, based on a presence, or an absence, of the one or more characteristics.

Evaluating perforations on document images

The disclosure includes a system and method for obtaining, using one or more processors, at least one image of a document under test; obtaining, using the one or more processors, an edge domain representation of a first portion of the document under test; comparing, using the one or more processors, the edge domain representation of the first portion of the document under test to an edge domain representation of a corresponding portion of one or more valid document instances; and modifying, using one or more processors, a likelihood that the document under test is accepted as valid, or rejected as invalid, based on the comparison of the edge domain representations associated with the document under test and corresponding portion associated with one or more valid document instances.

Document boundary analysis

The disclosure includes a system and method for obtaining at least one image of a document under test, wherein valid instances of the document under test include at least one three-dimensional security feature; obtaining a first image snippet from the document under test, the first image snippet corresponding to at least a first portion of the three-dimensional security feature present in the valid instances of the document; deriving first dimensional data associated with the first image snippet; analyzing the first dimensional data to determine one or more of: whether the first dimensional data is consistent with a presence of the three-dimensional security feature, and whether the first dimensional data is consistent with second dimensional data; and modifying a likelihood that the document under test is accepted as valid, or rejected as invalid, based on the analysis of the first dimensional data.

Evaluating three-dimensional security features on document images

Computer systems and methods are provided for determining authenticity of a document. A computer system receives first image data from a remote third party. The first image data includes a first image of a document. The computer system generates an image hash based on at least a portion of the received image data. The computer system compares the generated image hash with a stored image hash to determine whether the generated image hash meets image matching criteria. The stored image hash is associated with a first predetermined authentication decision. In accordance with a determination that the generated image hash meets the image matching criteria, the computer system transmits the first predetermined authentication decision to the remote third party.

Identification document database

Computer systems and methods are provided for receiving a first authentication request that includes an image of an identification document. A risk value is determined using one or more information factors that correspond to the authentication request. A validation user interface that includes the image of the identification document is displayed. A risk category that corresponds to the risk value is determined using at least a first risk threshold. In accordance with a determination that the risk value corresponds to a first risk category, a visual indication that corresponds to the first risk category is displayed. In accordance with a determination that the risk value corresponds to a second risk category, a visual indication that corresponds to the second risk category is displayed.

Triage engine for document authentication

Computer systems and methods are provided for using a machine learning system to analyze authentication information. First authentication information for a first transaction includes at least a first image that corresponds to a first identification document is received. First validation information that corresponds to a first validation fault is received from a validation system. Data storage of a machine learning system stores the first validation information. Second authentication information for a second transaction includes a second image that corresponds to a second image is received. The machine learning system determines a first validation value that corresponds to a probability that the second image includes the first validation fault. The first validation value is used to determine whether fault review criteria are met. In accordance with a determination that the fault review criteria are met, the second image is transmitted to the validation system.

Growing community of inventors

Vienna, Austria

Attila Balogh