Capital One Services, LLC

Lin Ni Lisa Cheng

Tyler Maiman

Joshua S Edwards

Asher Smith-Rose

Shabnam Kousha

Cruz Vargas

Phoebe Atkins

Kevin Grant Osborn

Salik Shah

Rajko Ilincic

David Gabriele

Max Miracolo

Alexander Lin

Brian McClanahan

Wayne David Lutz

Saleem Ahmed Sangi

Daniel John Marsch

Michael Saia

Daniel Herrington

Xiaoguang Zhu

Deny Daniel

Adrian Garner

Suzanne Parker

Vyjayanthi Vadrevu

Rocky Guo

Angelina Wu

Matthew Peroni

John Fields

Kyle Rankin Johnson

Leeyat Bracha Tessler

Elisa-Michelle Rodriguez

Matt J Oliver

Michael Bakr Mossoba

Latika Gulati

Dwij Trivedi

Ljubica Chatman

Kathryn Tikoian

Ryan M Parker

Shaun Webb

Chris Demchalk

Purva Shanker

Louis Buell

Paul Cho

Michael Wolf

Seth Wilton Cottle

Marcelo Jabif Epsztejn

Alexander Mireles

Gary B Williams

Piper Alexandra Coble

Matthew Kevin Sullivan

Wade Rance

Alexis Howard

Yichen Zhang

Tasneem Adamjee

Eric Campbell

Sergey Petrunin

Natalie Kuhn

Glenn Bewley

Evans Yeung

Sara Margaret Hughes

Allison Trager

A system may transmit an MLM to one or more entities. The system may receive, from the one or more entities, data associated with a plurality of customers, the data generated by the MLM. The system may train a federated deep NN based on the data. The system may receive, from a user, a first request for a loan. The system may generate, using the federated deep NN, a risk score associated with the user, wherein the risk score comprises a likelihood the user will satisfy condition(s) of the loan. The system may transmit, to lender(s), the risk score and a second request for loan option(s) for backing the first request for the loan. The system may receive, from the first lender(s), the loan option(s) for backing the first request for the loan, and may transmit the loan option(s) to the user.

Systems and methods for exchanging user data

Methods and systems are described herein for manipulating a communication acceptance screen, manipulating an interactive communication acceptance icon, and restricting access to accounts based on voice communication parameters. In particular, when a communication is detected from one device to another device, that communication may be risky. Thus, the risk is mitigated by giving a user information about the source of the communication to give a user a chance to reject the communication. In addition, in instances where the user accepts the communication, the system enables monitoring the communication and restricting any accounts that are disclosed within the communication.

Restricting access based on voice communication parameters

Example embodiments of systems and methods for card production are provided. A card may include processing circuitry including a chip and memory. The card may include one or more antennas in communication with the chip. The card may include a first layer of material aligned within a perimeter of the card via laminate encapsulation. The first layer of material may comprise a non-rectangular shape. The first layer of material may be offset with a shape of the card. The first layer of material may be in communication with the chip. The first layer of material may comprise at least one selected from the group of steel, tungsten, titanium, or any combination thereof. The card may be compliant with one or more form factors.

Systems and methods for producing non-standard shaped cards

Disclosed embodiments may include systems and methods for providing modified order recommendations. Line item data from a set of transactions associated with a vendor can be collected. The line item includes transactional data such as price, quantity, and frequency. The set of transactions are associated with a plurality of customers of the vendor. Correlations between line item data can be determined via one or more machine learning techniques to train a recommendation model. An order recommendation to a customer can be determine based on the correlations of the recommendation model. An order of the customer can be modified according to the order recommendation.

Modified ordering recommendations

Systems and methods of the present disclosure enable database search. The systems and/or methods may include receiving a search query that includes an input document having text. Word embeddings are generated within the input document, where the word embeddings include vector representations of words in the text of the input document. An average input document word embedding vector is determined for the word embeddings of the input document. A set of stored documents is accessed, where each stored document includes a stored text has a particular average stored document word embedding vector. A similarity model is used to determine a similarity metric measuring the similarity between the input document and each stored document based on the average input document word embedding vector and the particular average stored document word embedding vector of each stored document.

Systems for database searching and database schemas management and methods of use thereof

In some embodiments, the present disclosure provides an exemplary method that may include steps of obtaining a permission from the user to monitor a plurality of activities executed within the computing device; continually monitoring the plurality of activities executed within the computing device for a predetermined period of time; identifying an indication of an incoming interaction session within the predetermined period of time; verifying at least one session interaction parameter associated with the incoming interaction session to identify the incoming interaction session as a repeat interaction session; dynamically retrieving at least one relation-specific notation from a plurality of relation-specific notations to display; instructing an input GUI element to display input data associated with the repeat interaction; automatically updating the plurality of relation-specific notations associated with the historical data relationship; and instructing at least one programmable output GUI to display a notification identifying the update of the plurality of relation-specific notations.

Computer-based platforms and systems configured to enhance a call screen with user-controlled notes associated with the call and methods of use thereof

Systems and methods of caller identification differentiation via machine learning techniques are disclosed. In one embodiment, an exemplary computer-implemented method may include: receiving a permission indicator identifying a permission by the user to detect calls being received by a computing device; receiving an indication of a current call being received; utilizing a trained call differentiation machine learning model to determine a likelihood that the current call is of a first call type or a second call type, where the first call type is associated with a first type of activity and the second call type is associated with a second type of activity.

Computer-based systems configured for caller identification differentiation and methods of use thereof

Generating a screening interface for communications

Systems and methods of the present disclosure enable intelligent dynamic caching of data by accessing an activity history of historical electronic activity data entries associated with a user account, and utilizing a trained entity relevancy machine learning model to predict a degree of relevance of each entity associated with the historical electronic activity data entries in the activity history based at least in part on model parameters and activity attributes of each electronic activity data entry. A set of relevant entities are determined based at least in part on the degree of relevance of each entity. Pre-cached entities are identified based on pre-cached entity data records cached on the user device, and un-cached relevant entities from the set of relevant entities are identified based on the pre-cached entities. The cache on the user device is updated to cache the un-cached entity data records associated with the un-cached relevant entities.

Automated predictive caching of cloud-sourced data and methods of use thereof

In some embodiments, the present disclosure provides an exemplary method that may include steps of obtaining a trained spam upsurge detection machine learning model that determines when a current frequency associated with spam communications received by a current user exceeds a baseline frequency associated with the current user; receiving a permission indicator identifying a permission by the user to detect communications being received by the computing device; receiving an indication of at least one communication being received; determining the at least one communication as a particular spam communication; updating a frequency at which spam communications have been received by the user based at least in part on the particular spam communication; utilizing the trained spam upsurge detection machine learning model to determine that the frequency exceeds a baseline frequency associated with the user; and initiating a scan of one or more dark web resources.

Computer based systems configured to adjust frequency scanning of the dark web in search of information and method of use thereof

Systems and methods of the present disclosure enable virtual tokens for dynamically mapping virtual account numbers to actual accounts. The systems and methods include receiving an electronic data modification instruction of a virtual record modification to cause at least one data modification to at least one attribute of a virtual record data structure associated with the actual account. A user record associated with the virtual record is determined, and a record modification preference associated with the user record is determined based on the modification condition. An authorization instruction is generated to authorize the electronic data modification instruction to cause the modification by instructing at least one database management system to modify the user record according to the record-specific modification.

Computer-based systems configured for authenticating based on generated virtual tokens and methods of use thereof

An automated method is provided for initiating a transaction function in a transaction processing device. The method comprises establishing near field communication between the transaction processing device and an NFC transmitting device having an associated tag identifier and receiving NFC information including the tag identifier. The transaction processing device transmits the NFC information to a merchant processor and receives from the merchant processor a tag rule communication including an instruction to carry out a transaction function associated with the tag identifier or a request to associate a new transaction function with the tag identifier. Responsive to receiving an instruction to carry out a transaction function associated with the tag identifier, the transaction processing device executes the transaction function. Responsive to receiving a request to associate a new transaction function with the tag identifier, the transaction processing device transmits a request response to the merchant processor.

System and method for varying a function triggered by near field communication

Disclosed embodiments may include a system for generating aggregate records. The system may retrieve data corresponding to a first user. The system may receive, from the first user, first sharing preference(s) associated with a second user. The system may extract first data subset(s) from the data based on the first sharing preference(s). The system may generate block(s) of a blockchain ledger. The system may append the first data subset(s) to at least a first block of the block(s) of the blockchain ledger. The system may provide the second user with access to the first data subset(s) on the at least first block.

Systems and methods for generating aggregate records

Disclosed herein are system, method, and computer program product embodiments for providing secure access to a locker of a locker system based on a token that includes token data and a message authentication code (MAC) to authenticate the token data. The token data includes at least the unique locker identifier for the locker. The MAC can be generated using a secret key. The secret key can be obtained based on a unique derivation key associated with a master key. The locker system can determine whether the token is valid based on the token data, the MAC, and the secret key. In response to a determination that the token is valid, the locker system can send a signal to unlock the locker.

Token based secure access to a locker system

Systems and methods of the present disclosure enable split communication routing. A communication request associated with an electronic activity is received, the communication request specifying a virtual token and a data content, where the virtual token is a proxy for multiple actual data source profiles. A split rule defining a proportion of the data content to be attributed to each actual data source profile is determined. A security score is determined based on each actual data source profile and each proportion of the data content. The communication request is authorized based on the security score exceeding a threshold security score and access to the proportion of the data content in each actual data source profile is enabled. Each proportion of the data content is consolidated into a single response, and the electronic activity is executed with the single response.

Computer-based systems configured for efficient and secure multi-user electronic activities and methods of use thereof

Growing community of inventors

Fresh Meadows, NY, United States of America

Lin Ni Lisa Cheng