Capital One Services, LLC

Societe Des Produits Nestle S.a.

Tyler Maiman

Joshua S Edwards

Viraj Chaudhary

Samuel Rapowitz

David Septimus

Stephen Robert Schneider

Lin Ni Lisa Cheng

Bryant Alan Yee

Daniel Herrington

Abdelkader M'Hamed Benkreira

Jenny Melendez

Asher Smith-Rose

Michael Bakr Mossoba

Kevin Grant Osborn

Brendan Way

Shabnam Kousha

Daniel Miller

Kathryn Tikoian

Vyjayanthi Vadrevu

Salik Shah

Daniel E Miller

Phoebe Atkins

Aysu Ezen Can

Ljubica Chatman

Alexander Lin

Mia Rodriguez

Feng Qiu

Guadalupe Bonilla

Meredith Leigh Critzer

David Gabriele

Leeyat Bracha Tessler

Jude Pierre Anasta

Vahid Khanagha

Wayne David Lutz

Saleem Ahmed Sangi

Daniel John Marsch

Abdelkader Benkreira

Michael Saia

Max Miracolo

Nimma Bhusri

Sarah Jane Cunningham

Cruz Vargas

Charles Moore

Shannon Yogerst

Adam Vukich

Timothy W James

Erik Neighbour

Smeeta Khetarpaul

Ashley Dakota Ross

Andrius Dapkus

Laetitia Allexant

Matthew Gorman

Sophie Bermudez

Lea Cody

Dwij Trivedi

Andrea Montealegre

Gaurang J Bhatt

Jennifer Kwok

Abdelkadar M'Hamed Benkreira

Abdelkader M'hamed Benkreira

Matthew Horton

Negar Kalbasi

Imren Johar

Armando Martinez Stone

Haytham Yaghi

Kimberly Stockley

Jose Vazquez

Mary Sweeney

Samuel Yip

Justin Anthony Bowers

Dexter Ferguson

Juwan Byrd

Yichen Zhang

Albert Hergenroeder

Tasneem Adamjee

Elaine Markey

Jerry Wu

Claire M Rowlett

Robert Mays

Anantha Swarna Kavi

Elaina Teramoto

In some embodiments, the present disclosure provides an exemplary method that may include steps of receiving input data from at least one external data aggregator; utilizing a trained machine learning algorithm to generate a database of known queries; receiving subsequent input data from the at least one external aggregator; automatically updating the database of known queries associated with the plurality of users; utilizing the trained machine learning algorithm to perform a cross-reference analysis to determine a presence of a data record within the database of known queries; dynamically removing the data record from the database of known queries; utilizing the trained machine learning algorithm to predict a trigger associated with the presence of the at least one data record; and instructing a computing device to initiate a verification of the presence of the at least one data record.

Computer-based systems configured for automatically updating a database based on an initiation of a dynamic machine-learning verification and methods of use thereof

In some embodiments, the present disclosure provides an exemplary method that may include steps of obtaining a permission from a user to monitor a plurality of activities; receiving monitoring data of the plurality of activities for a first period of time; verifying at least one common session parameter to identify an incoming interaction sessions; utilizing a software application to access an interaction session database; identifying an interruption associated with the software application for a second period of time; utilizing a machine learning algorithm to verify the interruption; determining a plurality of authentication rules; adjusting the plurality of authentication rules, receiving a response to an interactive communication; and updating the database of known session interaction parameters.

Computer-based systems configured to dynamically verify a plurality of interaction sessions associated with an interaction session data source and methods of use thereof

Aspects described herein may provide techniques for authenticating a user using transaction-based authentication questions that are generated based on item-level purchase data. The item-level purchase data of a transaction may include specific details of a transaction such as identification of each item purchased and corresponding prices paid for each item. Transaction-based authentication questions for a financial account may be generated based on the item-level purchase data that an authorized user of the financial account is likely to remember and that a malicious actor is unlikely to correctly guess. As a result, the authorized user of the account is likely to be correctly authenticated while the malicious actor is likely to answer the transaction-based authentication question incorrectly. Authentication can therefore effectively block malicious actors without overly burdening actual authorized users during the authentication process.

Transaction based authentication with item-level data

Systems and methods are described herein for novel uses and/or improvements to artificial intelligence applications. As one example, systems and methods are described for the use of an artificial intelligence-based solution in identifying fraudulent documents and/or other content. In particular, the systems and methods adapt the artificial intelligence-based solution to overcome the technical problem of insufficient training data and/or solutions that are commensurate with the time frame and resources available.

Systems and methods for determining document authenticity based on weighted analysis of categorical content attributes

Methods, systems, and apparatuses are described herein for improving computer authentication processes through excluding fraudulent transactions in transaction-based authentication. A computing device may receive a request for access to an account from a user. The computing device may provide transaction data to a machine learning model. The computing device may receive data indicating a confidence threshold associated with the user from the machine learning model. The computing device may generate a modified set of merchant choices for the user by excluding merchants related to potentially fraudulent transactions within a predetermined time period. An authentication question may be generated, and access to the account may be provided based on a response to the authentication question.

Excluding fraudulent transactions in transaction based authentication

Example embodiments of systems and methods for a cryptographic bypass system, comprising: a contactless card; and a server, wherein the server is configured to: receive a cryptogram and location data after a tap of the contactless card to a client device, identify a first merchant based on the location data, set a flag associated with the first merchant and the contactless card, receive a transaction request from a merchant payment system of the first merchant associated with the contactless card, wherein the transaction request indicates a transaction amount, and approve the transaction request when the transaction amount exceeds a first transaction limit when the flag is set.

Systems and methods for bypassing contactless payment transaction limit

In some implementations, a transaction card may include a card body having a first surface and a second surface opposite the first surface. The transaction card may include an integrated circuit (IC) chip embedded in the card body, and a plurality of first electrical contact sets electrically accessible from the first surface of the card body, where the plurality of first electrical contact sets have electrical connections to the IC chip. The transaction card may include a plurality of first magnetic stripe areas readable from the first surface of the card body. The transaction card may include a plurality of second electrical contact sets electrically accessible from the second surface of the card body, where the plurality of second electrical contact sets have electrical connections to the IC chip. The transaction card may include a plurality of second magnetic stripe areas readable from the second surface of the card body.

Transaction card with multiple orientations

Embodiments are generally directed systems, devices, methods, and techniques to detect vehicle service events in transactions, and to store the vehicle service events in a data store.

Systems and techniques to automatically maintain accurate vehicle service events for vehicles

Systems and methods are disclosed herein for real-time digital authorization. According to some embodiments, a method includes receiving, from a user device, user information comprising one or more categories. The method further includes transferring an amount corresponding to the user information. The method also includes obtaining, from a location sensor of the user device, location data including a global position system (GPS) location for the user device and identifying one or more entities based on a correlation between the location data and a parameter defining locations of the one or more entities. The method further includes performing a mapping operation between the one or more entities and the user information and receiving a request from an entity device. The method further includes transmitting a message to the entity device indicating an operation status.

Systems and methods for providing real-time digital authorization and management

Systems and methods for improvements to multifactor authentication (MFA) techniques are described herein. The improved and enhanced MFA techniques can leverage user interaction data to predict an entity-issued user-specific identification document that an authorized user of an authorized user account is most likely to carry on their person. Upon a request to access an authorized user account being received, the improved and enhanced MFA techniques can request that the user capture, in real-time, an image depicting the predicted identification document. Using additional artificial intelligence, a determination may be made as to whether the image depicts a real instance of the entity-issued user-specific identification document. This determination may result in access to the authorized user account being provided or denied.

Identification card based multi-factor authentication

A system may include processor(s), and memory in communication with the processor(s) and storing instructions configured to cause the system to correct ASR errors. The system may receive a transcription comprising transcribed word(s) and may determine whether the transcribed word(s) exceed associated predefined confidence level(s). Responsive to determining a transcribed word does not exceed a predefined confidence level, the system may generate a predicted word. The system may calculate a distance between numerical representations of the transcribed word and the predicted word and may determine whether the distance exceeds a predefined threshold. Responsive to determining the distance exceeds the predefined threshold, the system may determine whether at least one red flag word of a list of red flag words corresponds to a context of the transcription, and, responsive to making that determination, may classify the transcription as associated with a first category.

Systems and methods for correcting automatic speech recognition errors

Example embodiments of systems and methods for preventing chip fraud are provided. A chip fraud prevention system may comprise a device including a chip, wherein the chip is at least partially encompassed in a chip pocket. One or more connections may be communicatively coupled to one or more surfaces of the chip, and a capacitance member may be coupled to a surface of the chip. The capacitance member may comprise a known capacitance value and the chip may comprise a memory containing an applet, wherein the applet is configured to measure the capacitance value of the capacitance member.

Systems and methods for use of capacitive member to prevent chip fraud

In some implementations, a reliability modeler may receive a plurality of webpages associated with a first entity from an Internet scraping device. The reliability modeler may detect, within the plurality of webpages, at least one of a logo, a font, or a color. The reliability modeler may apply a model, trained on a set of guidelines associated with the first entity, to the logo, the font, or the color. Accordingly, the reliability modeler may determine, based on output from the model, that the plurality of webpages are unlikely to be authorized by the first entity. The reliability modeler may transmit, to a user device, an alert based on determining that the plurality of webpages are unlikely to be associated with the first entity.

Detecting reliability across the internet after scraping

Methods and systems are described herein for facilitating token use authentication using stochastic-model-derived images. The system may detect an authentication request to authenticate use of an access token and retrieve operation data associated with the access token. The system may determine, based on the operation data, source data associated with a source of a network operation and alternative source data associated with an alternative source. The system may provide, to a stochastic machine learning model, the source data to obtain a first image for the network operation and the alternative source data to obtain a second image for the network operation. The system may then generate, for display, the first image and the second image and may receive a selection of the first image. Based on the selection of the first image, the system may grant the authentication request.

Facilitating authentication using stochastic-model-derived images

Methods, systems, and apparatuses are described herein for improving the security of personal information by preventing attempts at gleaning personal information from authentication questions. A computing device may receive a request for access to an account associated with a user. The request may comprise candidate authentication information. Based on comparing the candidate authentication information with the account data, the computing device may generate a synthetic authentication question. The synthetic authentication question may be generated as if the candidate authentication information is valid. A response to the synthetic authentication question may be received, and the request for access to the account may be denied.

Preventing unauthorized access to personal data during authentication processes

Growing community of inventors

Melville, NY, United States of America

Tyler Maiman