Verint Americas Inc.

Vercrio, Inc.

Victrio, Inc.

Anthony Rajakumar

Lisa Guerra

Richard Gutierrez

David Hartig

Vipul Vyas

Torsten Zeppenfeld

Andrew S Efron

N Nikki Mirghafori

A process of confirming an originator of an electronic mail (email) includes receiving a request for verification of the identity of an alleged originator of the email, which may be sent from the actual originator of the email or a recipient of the email. The alleged originator of the email may be determined, e.g., by parsing the email to determine the name of the sender in the email. Verification is obtained from a biometric-enabled client that is associated with the send whether the email was in fact sent by the sender as well as confirmation of the identity of the sender based on a previously stored identity-proofed biometric.

Automated scalable identity-proofing and authentication process

An automated process is disclosed for improving the functionality of computer systems and electronic commerce in user identity-proofing. Steps include verifying that a user who is electronically seeking identity proofing is on an electronic directory of persons eligible for such identity proofing; creating an attest list for the user that includes associates who can vouch for his or her identity; collecting a video or other data from the user; sending the video or data to the associates and asking them for a confirmation or a disavowal of the identity of the user; deriving a biometric from the video or data upon receiving the confirmation; and saving the biometric as an identity-proofed biometric.

An automated process is disclosed for improving the functionality of computer systems and electronic commerce in user identity-proofing. Steps include verifying that a user who is electronically seeking identity proofing is on an electronic directory of persons eligible for such identity proofing; creating an attest list for the user that includes associates who can vouch for his or her identity; collecting a video or other data from the user; sending the video or data to the associates and asking them for a confirmation or a disavowal of the identity of the user; deriving a biometric from the video or data upon receiving the confirmation; and saving the biometric as an identify-proofed biometric.

Enhanced diarization systems and methods of use are provided herein. Some exemplary methods may include applying one or more rules that affect separation of the call audio data into segments, the rules being associated with the at least one call schema, separating the call audio data into segments according to the one or more rules, grouping segments of call audio data associated with a speaker, and storing in a storage media an identifier and the grouped segments for the speaker.

Enhanced diarization systems, media and methods of use

Systems, methods, and media for analyzing fraud patterns and creating fraud behavioral models are provided herein. In some embodiments, methods for analyzing call data associated with fraudsters may include executing instructions stored in memory to compare the call data to a corpus of fraud data to determine one or more unique fraudsters associated with the call data, associate the call data with one or more unique fraudsters based upon the comparison, generate one or more voiceprints for each of the one or more identified unique fraudsters from the call data, and store the one or more voiceprints in a database.

Systems, methods, and media for determining fraud patterns and creating fraud behavioral models

Systems, methods, and media for disambiguating call data are provided herein. Some exemplary methods include receiving, via a fraud notification system, notification of a fraud event associated with a customer account, the fraud event comprising a time stamp, determining, via a call selection module, unique voice samples or models from call events obtained within a time frame that is temporally proximate the fraud event, and generating a timeline presentation that includes each unique voice sample or model identified in the call events based upon a time stamp associated with the call events.

Systems, methods, and media for disambiguating call data to determine fraud

Disclosed is a method for generating a fraud risk score representing a fraud risk associated with an individual, the method comprising: a) determining a telephony channel risk score from at least one of audio channel data and non-audio channel data of the individual; and b) generating the fraud risk score based on at least one of the telephony channel risk score, the audio channel data, and the non-audio channel data.

Method and system for generating a fraud risk score using telephony channel based audio and non-audio data

According to one aspect of the invention there is provided a method, comprising collecting voiceprints of callers; identifying which of the collected voiceprints are associated with fraud; and generating a whitelist comprising voiceprints corresponding to the collected voiceprints not identified as associated with fraud.

Building whitelists comprising voiceprints not associated with fraud and screening calls using a combination of a whitelist and blacklist

Systems, methods, and media for generating fused risk scores for determining fraud in call data are provided herein. Some exemplary methods include generating a fused risk score used to determine fraud from call data by generating a fused risk score for a leg of call data, via a fuser module of an analysis system, the fused risk score being generated by fusing together two or more uniquely calculated fraud risk scores, each of the uniquely calculated fraud risk scores being generated by a sub-module of the analysis system; and storing the fused risk score in a storage device that is communicatively couplable with the fuser module.

Systems, methods, and media for generating hierarchical fused risk scores

Disclosed is a method for enrolling a voiceprint in a fraudster database, the method comprising: a) defining a fraud model comprising at least one hypothesis indicative of a fraudulent transaction; b) processing audio data based on the fraud model to identify at least one suspect voiceprint in the audio data suspected of belonging to a fraudster; and c) enrolling the at least one suspect voiceprint in the fraudster database.

Method and system for enrolling a voiceprint in a fraudster database

In one embodiment, the invention provides a method, comprising: (a) maintaining a database of known fraudsters, wherein each fraudster has a voice signature and metadata associated therewith; (b) performing a screening operation to match a candidate with a fraudster in the database based on matching a voice signature and metadata for the candidate with a voice signature and metadata for the fraudster in the database.

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Fremont, CA, United States of America

Anthony Rajakumar