Capital One Services, LLC

Sarah Jane Cunningham

Sophie Bermudez

Michael Bakr Mossoba

Colin Hart

Kaitlin J Newman

Wayne David Lutz

Latika Gulati

Jeffrey Rule

Lara Mossler

Charles Nathan Crank

Kimberly Haynes

Andrew Cogswell

Abdelkader M'Hamed Benkreira

Salik Shah

Alexandra Colevas

Michael Saia

Kaylyn S Gibilterra

Mark Rothbaum

Joshua S Edwards

Kevin Grant Osborn

James M Ashfield

Melissa Yoemans Heng

Tyler Maiman

Adam Vukich

Abdelkader Benkreira

Leeyat Bracha Tessler

Bryant Alan Yee

George Bergeron

James Zarakas

Rajko Ilincic

Mykhaylo Bulgakov

William Carroll

Gaurang J Bhatt

Jennifer Kwok

Rocky Guo

John Jones

Mario Munoz

James Holt Crews, Jr

Zachary Benjamin Toal

Jesse Do

Catherine Sun

Albert Hergenroeder

Christopher R Carter

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

The disclosed technology relates to assessing and securing credit risk using credit worthiness tokens issued in a blockchain network responsive to particular financial events. An exemplary blockchain node device may store an issuance smart contract associated with an identity and including a first wallet address and allocation parameters. An event query may be sent to an oracle device external to the blockchain network. The event query may include the identity. Event data associated with the identity may then be received from the oracle device in response to the event query. A number of credit worthiness tokens is determined based on an application of the allocation parameters to the event data. The determined number of credit worthiness tokens is then allocated to the identity via the first wallet address. Thereafter, the credit worthiness tokens can be transferred or collateralized, e.g., and can represent credit worthiness for the identity across financial institutions.

Systems and methods for managing metrics in blockchain networks

A computer-implemented method for determining alternative plans for a user may include: determining an event status of an event based on one or more parameters, wherein the event status comprises a target event indicator, wherein the one or more parameters comprise event population; obtaining event data of a target event; obtaining transactional data of the user, wherein the transactional data includes transaction time and transaction location; determining, via one or more processors, a likelihood of a potential transaction of the user associated with the target event by processing the transactional data and the event data using a trained machine learning model; and transmitting, to the user, a notification based on the determined likelihood of the potential transaction, wherein the notification includes a suggestion for alternative travel plans of the user.

Methods and systems for determining alternative plans

A computer-implemented method of fraud protection is described. A server may receive one or more keywords and a likelihood of fraud from an external source. The server may receive an image of a document from a user device, wherein the document comprises at least one of a written communication or a printed communication. The server may extract text from the image of the document, compare the extracted text to the one or more stored keywords, and calculate a confidence level of fraud. The server may send an indication of the confidence level of fraud to the user device.

Systems and methods of photo-based fraud protection

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

A device may configure a browser to permit cash payments for online transactions. The device may monitor a browser session of the browser. The device may detect, during the browser session, navigation of the browser to a transaction page of a website. The transaction page may be configured to facilitate an online transaction with the website. The device may determine, based on detecting the navigation of the browser to the transaction page, that a cash payment is to be provided. The device may cause a validation code to be generated. The device may cause, based on the validation code being processed, a virtual transaction card to be generated. The device may facilitate, using virtual card information associated with the virtual transaction card, execution of the online transaction.

Transaction platform that permits cash payments for online transactions

Systems and methods for user information management using contactless cards

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 aspects, a computing system may use machine learning to determine whether a control is faulty or generate recommendations to make a modification to a control. may identify a portion of problematic computer code that implements the faulty control through the use of machine learning. A computing system may use machine learning to generate embeddings that map incident data and control data (e.g., computer-readable code of a control) to the same vector space. Further, a computing system may use a weighting mechanism that may be used to weight each sample used to train a machine learning model, which may allow a model to train more efficiently.

Machine learning for detecting and modifying faulty controls

Growing community of inventors

Arlington, VA, United States of America

Sarah Jane Cunningham