Capital One Services, LLC

Sophie Bermudez

Salik Shah

Sarah Jane Cunningham

Michael Bakr Mossoba

Latika Gulati

Colin Hart

Kaitlin J Newman

Wayne David Lutz

Abdelkader M'Hamed Benkreira

Jeffrey Rule

Lara Mossler

Charles Nathan Crank

Kimberly Haynes

Andrew Cogswell

Michael Saia

Alexandra Colevas

Kaylyn S Gibilterra

Joshua S Edwards

Kevin Grant Osborn

James M Ashfield

Melissa Yoemans Heng

Austen Novis

Abdelkader Benkreira

Andrea Montealegre

Akbar Hosseinkhani

Omar Khan

Khosro Akhavan Astaneh

Daniel John Marsch

Cruz Vargas

William Carroll

Gaurang J Bhatt

Tyler Maiman

Timur Sherif

Lea Cody

Jose Vazquez

Abdelkadar M Hamed Benkreira

A system includes one or more memory devices storing instructions, and one or more processors configured to execute the instructions to perform steps of a method providing biometric detection of coercion of a user. The system may detect a trigger event associated with a potential transfer of funds and may receive user biometric data. The system may determine, based on stored user biometric data and the detected user biometric data, a confidence level that the stored user biometric data is indicative of biological information representative of a user being in a stressed state. The system may initiate one or more precautionary safety measures.

Systems for detecting biometric response to attempts at coercion

A processing platform may receive a plurality of images. The processing platform may determine respective asset types of the plurality of assets based on a computer vision technique. The processing platform may determine respective estimated values of the plurality of assets based on the respective asset types. The processing platform may provide information identifying the respective estimated values of the plurality of assets to two or more recipients. The processing platform may receive allocation information. The processing platform may determine a selected allocation of the plurality of assets for the two or more recipients based on the allocation information and using a second model. The processing platform may perform one or more actions based on the selected allocation.

Computer vision based asset evaluation

Example embodiments of systems and methods for data transmission system between transmitting and receiving devices are provided. In an embodiment, each of the transmitting and receiving devices can contain a master key. The transmitting device can generate a diversified key using the master key, protect a counter value and encrypt data prior to transmitting to the receiving device, which can generate the diversified key based on the master key and can decrypt the data and validate the protected counter value using the diversified key.

Systems and methods for message presentation using contactless cards

Systems and methods for user information management using contactless cards

A predictive model system may include an application comprising instructions for execution on a device including one or more processors coupled to memory, and one or more servers in data communication with the application. The one or more servers may be configured to receive a first set of data which may be updated to include transaction data and at least one selected from the group of mileage rental information; create a predictive model based on the first set of data; transmit, to the application, one or more requests including a second set of data, the second set of data comprising at least one selected from the group of location information, date, time, name, and age of a user; update the predictive model based on the received second set of data received; generate a dynamic rate based on the updated predictive model; and transmit, to the application, the dynamic rate.

Systems and methods for predictive model generation

Systems and methods for performing transactions with contactless cards

Systems and methods for user authorization and access to services using contactless cards

Systems and methods for cryptographic authentication of contactless cards

In some implementations, an identity verification device may receive a request to verify an identity associated with a user accessing a social media account to share information on a social media platform. The identity verification device may generate, based on the request, a virtual credential linked to a primary credential associated with a financial account belonging to a holder of the social media account. The virtual credential may be used in an identity verification transaction to prove that the user accessing the social media account has access to the financial account associated with the social media account holder. The identity verification device may store a record indicating that the virtual credential was used to conduct the identity verification transaction and may provide, to the social media platform, information to verify the identity associated with the user accessing the social media account based on the record.

Identity verification using a virtual credential

Example embodiments of systems, methods, and computer-accessible mediums for transaction authorization are provided. An exemplary system can comprise a card including an input device and a display device in data communication with a server. The server can generate an authorization passcode upon an initiation of a transaction session, and the card can receive an entered passcode through the input device, display the entered passcode on the display device, and transmit the entered passcode to the server for comparison to the authorization passcode. Upon a determination that the entered passcode is a match for the authorization passcode, the server can transmit a match notification indicating the transaction session is valid, and upon a determination that the entered passcode is a mismatch for the authorization passcode, the server can transmit a mismatch notification terminating the transaction session.

Systems and methods for card authorization

In a method of controlling account user access to transaction information for a joint account, a set of control criteria is stored in a control database. Information for a new transaction is received and stored in a transaction information database. An information limitation request to prevent access to the transaction information by a second account user for a withholding time interval is received from a first account user. An access limitation record including identification of the second account user and the withholding time interval is stored in the information control database. Upon receiving from a second account user a request for account information including the transaction information, a determination may be made as to whether the transaction information should be withheld from the second account user. Responsive to a determination that the transaction information should be withheld, a response excluding the transaction information is transmitted to the second user device.

System and method for controlling access to account transaction information

Various embodiments are generally directed to techniques to enable use of a transaction card of a user device to perform transactions. Embodiments may include method, techniques, and circuitry to cause a transaction card to extend from a user device to be used to perform the transactions. Further, the transaction card may retract into the housing the user device when not in use.

Techniques to provide physical transaction card capabilities for a device

Various embodiments are generally directed to method and devices to receive biometric data and transaction data relating to a transaction, apply a model to the biometric data and the transaction data to determine an emotional state of the user during the transaction, and determine an action associated for the transaction based on the emotional state of the user during the performance of the transaction. Embodiments further include causing performance of the action.

Techniques to process biometric and transaction data to determine an emotional state of a user while performing a transaction

A device may receive audio data based on a capturing of sounds associated with a structure. The device may obtain a model associated with the structure. The model may have been trained to receive the audio data as input, determine a score that identifies a likelihood that a sound is present in the audio data, and identify the sound based on the score. The device may determine at least one parameter associated with the sound. The device may generate a metric based on the at least one parameter associated with the sound, and perform an action based on the metric.

Listening devices for obtaining metrics from ambient noise

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Washington, DC, United States of America

Sophie Bermudez