Capital One Services, LLC

Other

Abdelkader M'Hamed Benkreira

Joshua S Edwards

Michael Bakr Mossoba

Adam Vukich

Tyler Maiman

David Gabriele

Vu Nguyen

Jonatan Yucra Rodriguez

Brendan Way

Mykhaylo Bulgakov

Alexandra Colevas

Sophie Bermudez

Colin Hart

Kaitlin J Newman

Latika Gulati

Daniel John Marsch

Ljubica Chatman

Andrea Montealegre

Jeffrey Rule

Wayne David Lutz

Sarah Jane Cunningham

William Carroll

Taurean Butler

Lara Mossler

Charles Nathan Crank

Kimberly Haynes

Andrew Cogswell

Carrie Norman

Salik Shah

George Bergeron

Kaylyn S Gibilterra

Austen Novis

Nimma Bhusri

Rajko Ilincic

Jude Pierre Anasta

Kevin Patrick Kelly

Bryant Alan Yee

Max Miracolo

Steven Quadros

Adnan Malik

James Zarakas

Lukiih Cuan

Viraj Chaudhary

Phoebe Atkins

Kevan Emmott

Jennifer Kwok

Matthew Carson

Eric Medin

Jonathan Bodner

Robert T Perry

Kyle Rankin Johnson

Jessica Greenberg

Matthew Horton

Imren Johar

Negar Kalbasi

William C Prior

Natasha Mitchko

Nagaraju Gaddigopula

Noel Lyles

Various embodiments described herein are generally directed to techniques for managing fraud rules and generating authentication directions according to location data from one or more client devices. Embodiments may include using a payment server informed by a client device application to manage and/or apply fraud rules for transactions. In embodiments, fraud rules may be managed based on location data provided by a client device application and/or location data associated with at least one transaction system. In some embodiments, fraud rules may be managed based on location data provided by multiple client device applications and/or location data associated with at least one transaction system. In some embodiments, rules may be managed for an individual authorization request according to information from at least one client device application and location data for a transaction system associated with the authorization request.

Methods for enhancing transaction authorizations with device location data

Methods, systems, and apparatuses are described herein for improving computer authentication processes through computer-based authentication in a manner that uses knowledge of former devices. A computing device may train a machine learning model to output an indication of device reliability data associated with a particular device. The computing device may receive a request for access to an account from a user. The computing device may receive account data and provide the account data to the trained machine learning model. The computing device may receive data indicating device reliability for a set of devices from the machine learning model. The computing device may generate a modified set of device choices for the user by excluding devices having reliability levels below a threshold value. An authentication question may be generated, and access to the account may be provided based on a response to the authentication question.

Computer authentication using knowledge of former devices

In some embodiments, a queue may be monitored to perform an automated adjustment related to a data item in the queue. In some embodiments, the data item may be associated with a product or service and include a code related to an access to the product or service. Based on the code, configuration information related to the product or service may be obtained. Based on a detected change related to the product or service, an indication of a set of self-support actions may be sent to a user device. One or more self-support actions (performed via the user device) may be determined, and an adjustment related to the access to the product or service may be performed based on the determined self-support actions. In some embodiments, the adjustment may include modifying a configuration of the access to the product or service based on the determined self-support actions.

Utilizing machine learning with self-support actions

Various embodiments are directed to a method and system for provisioning a merchant-specific payment apparatus, such as a temporary payment card, via a computing device, such as an automated teller machine (ATM). A user, such as a customer, may specify a merchant. A record of known payment acceptance types at that merchant may be returned, which may be used to determine what type of temporary payment card gets issued to the user.

Method for provisioning merchant-specific payment apparatus

In some implementations, a device may utilize a machine learning model to determine a set of candidate manufacturing entities associated with an exchange of an item. The device may cause a first automated action to be performed. The first automated action may include providing information identifying the set of candidate manufacturing entities to a device of a user that is associated with the exchange. The device may receive a response indicating the manufacturing entity associated with item. The device may identify a block in a blockchain associated with the manufacturing entity. The device may map the exchange information to the block to enable the item information associated with the item to be associated with the exchange.

Database management for digitally storing item information

Provided, in an aspect, is a method for performing an online transaction using a graphical construct. The method can include receiving, by a client device, inputs to generate the graphical construct; transmitting to a server in communication with the client device, a request to generate the graphical construct; receiving, by the client device, the generated graphical construct and a summary information from the server; displaying, through a user interface of the client device, a summary screen including the generated graphical construct and the summary information; embedding, by the client device, the generated graphical construct on a third-party application running on the client device; sending, by the client device, a transaction request to perform the online transaction using the generated graphical construct; and presenting for display, through the user interface of the client device, a notification including a status of the online transaction.

Generation of a combinatorial payment QR code

Disclosed embodiments accelerate web form completion based on email address analytics. An email address can be input with respect to a web form and identified. The email address can be parsed into a username and a domain name and analyzed. A value of a web form field can be determined based on data extracted from the username, domain name, or both. The determined value can then be employed to automatically complete a corresponding web form field Values for additional fields can be computed based on the determined value alone or combined with data from other sources. User input and interaction with a web form can be monitored and used as a basis to dynamically complete additional fields, alter fields, or clear field values.

Accelerated form completion with email address analytics

Systems and methods are provided for group bill payment comprising creating a secure group bill payment account associated with a plurality of group members. The group bill payment account may be configured to receive information via a network from the plurality of group members; permit a group member to manage the group bill payment account following an authentication process; and transmit a group payment to a provider. Systems and methods may further comprise receiving instructions from a group member to create a rule for requesting payment, the bill being from a provider and associated with group members; receiving the bill issued by the provider; determining a charge based on the bill and the rule; sending a payment request based on the charge; receiving a deposit into the group bill payment account; transmitting a group payment; and sending a notification.

Systems and methods for real-time, distributed processing of group bill payments

A user assistance device aids validation of transactions on payment terminals. A payment terminal that accepts a payment card at a point of sale can be detected. A transaction amount for validation can be determined from the payment terminal. Subsequently, audio of the transaction amount can be generated. Playing of the audio on a user assistance device can then be triggered, allowing a user to hear the transaction amount before accepting or rejecting the transaction. Further, transaction information can be analyzed and used to suggest whether a customer should accept or reject the transaction.

Audible transaction verification with an assistance device

In some implementations, a system may receive a request to facilitate a service interaction involving a user. The system may determine, based on receiving the request, a priority factor associated with facilitating the service interaction for the user. The priority factor may be determined based on account activity information associated with a user account of the user. The system may determine, based on the priority factor and service information, a priority score associated with facilitating the service interaction. The system may select, based on the priority score, a queue location of a queue. The queue may be associated with a provider system that is configured to facilitate the service interaction. The system may perform an action associated with causing the provider system to facilitate the service interaction according to the queue location.

Service management system for processing a request

Perceptive scaling of computing resources is disclosed. News sources can be analyzed to identify a future event as well as an occurrence date and type of the event. A computing resource affected by the event can be determined based on the type of event. A scaling strategy can be formulated for the computing resource, such as scaling up or out, to address resource load introduced by the event. The extent of scaling can be determined based on the predicted impact of the event on the computing resource. Subsequently, the scaling strategy can be scheduled for execution before the occurrence date. The scaling strategy can later be terminated or deactivated after the event terminates.

Perceptive scaling of computing resources

In some implementations, a processing device may receive, from an optical sensor, a plurality of frames encoding images of an environment of a door. The processing device may estimate, using the plurality of frames, a direction and a speed associated with at least one person included in the plurality of frames. Accordingly, the processing device may transmit a command to a controller associated with the door based on the direction and the speed.

More efficient automatic door sensing

Transaction card

In some implementations, a device may receive information indicating that an instrument has been provided by a user to a recipient. The instrument may be associated with a value, and the instrument may be designated for the recipient. The device may determine, using the machine learning model, a prediction of a time of an event associated with the instrument based on the recipient. The event associated with the instrument may result in a reduction of a balance of an account of the user. The device may transmit to another device of the user, a notification indicating the prediction of the time of the event associated with the instrument.

Predicting a time of an event associated with an instrument using a machine learning model

In some implementations, a system may receive a notification related to a battery life of a battery of a user device. The system may determine, based on the notification, a battery level of the battery of the user device. The system may select based on the battery level of the battery of the user device, a particular communication scheme, of a plurality of communication schemes, for communicating with a user of the user device. The system may transmit at least one message according to the particular communication scheme.

System for monitoring battery life of a battery of a user device to facilitate selection of communication schemes

Growing community of inventors

Washington, DC, United States of America

Abdelkader M'Hamed Benkreira