Capital One Services, LLC

Brice Elder

Aditya Pai

Allison Fenichel

Sarah Olsen

Varun Gupta

Julie Murakami

Niyati Shah

Marek Sedlacek

In some implementations, an automated information transfer system may receive an indication of a location of the user device. The automated information transfer system may identify an interacting entity associated with the automated information transfer that is associated with a physical location that is within a threshold proximity of the location of the user device. The automated information transfer system may receive item-specific data associated with the automated information transfer. The automated information transfer system may identify one or more interaction terminals at the physical location associated with the interacting entity. The automated information transfer system may receive authorization information associated with the automated information transfer. The automated information transfer system may perform an action based on whether the authorization information indicates that the automated information transfer is at least one of authorized, conditionally authorized, not authorized, or conditionally not authorized.

Using location-based mapping to enable automated information transfer at a user location

Systems, methods, apparatuses, and computer-readable media are provided for determining individual item-level details associated with a transaction. A plurality of purchase transactions associated with different merchants may be displayed via a user interface. Responsive to a user selection of a first transaction, of the plurality of transactions, a camera may capture an image of at least a portion of a user receipt associated with the first transaction. The image of the user receipt may be analyzed using one or more optical character recognition (OCR) algorithms to convert the image of the user receipt into textual data. One or more character strings associated with line item-level details may be extracted from the textual data associated with the first transaction. Additional information associated with the line item details may be determined and the line item details and the additional information may be displayed via a user interface.

Item level data determination device, method, and non-transitory computer-readable media

Systems as described herein may classify entities based on cleansed transactions. An entity classification server may obtain transaction data indicating an entity name and an entity code in a non-standardized format. A recommended entity code in a standardized format may be determined from a remote data store. The entity classification server may generate a score indicating a likelihood that the recommended entity code correctly identifies the entity indicated in the transaction data using a machine classifier. The entity classification server may update the entity code in the transaction data with the recommended entity code based on the score exceeding a threshold value. Accordingly, a transaction summary comprising the transaction data may be generated and provided to a computing device.

Entity classification using cleansed transactions

Disclosed embodiments may include a method that includes receiving description data in an originating language for a user and a location associated with the user, identifying one or more names from the description data, retrieving additional data in the originating language based on the one or more names, generating enhanced description data in the originating language for the user based on the description data and the additional data, identifying a target language based on the location associated with the user, selecting a first trained neural network from a plurality of trained neural networks based the target language, providing the enhanced description data in the originating language to the first trained neural network, translating, via the first trained neural network, the enhanced description data from the originating language to the target language, and generating a graphical user interface for display that comprises the enhanced description data in the target language.

Systems and methods for translating transaction descriptions

Systems and methods for adaptive token verification are disclosed. For example, a system may include at least one memory storing instructions and one or more processors configured to execute the instructions to perform operations. The operations may include training a verification model to verify tokenized requests based on system identifiers. The operations may include receiving a tokenized request from an external system, the request comprising a system identifier of the external system. The operations may include generating output of the verification model based on the system identifier, and, based on the output, performing one of granting the request or blocking the request.

Adaptive artificial intelligence systems and methods for token verification

Aspects described herein may allow for determining network membership to facilitate detecting fraudulent messages. A computing device may receive, from one or more terminals at a first location, a plurality of interactive messages during a pre-determined time period. Each interactive message may comprise personally identifiable information of a user. The computing device may store a first record and a second record that indicate interactive messages were received from a group of users in temporal proximity to each other at the first location and the second location respectively. The computing device may send a request to confirm users in the subset are members of a network and update a membership list based on a reply received from the user. If further messages are received from devices outside the membership list, an alert may be sent to alert the possibility of a fraudulent message.

System for determining network membership

In some implementations, a data cleaning platform may determine a respective entity key for each data record in a cleansed dataset based on a combination of fields, in each data record, that contain information that uniquely identifies an entity associated with a respective data record. The data cleaning platform may generate a delta dataset based on a set of uncleansed data records related to transactions that occurred after a time when the cleansed dataset was first generated. For example, in some implementations, each uncleansed data record in the delta dataset may be associated with a corresponding entity key based on the combination of fields. The data cleaning platform may perform a data join to update the cleansed dataset to include data records related to the transactions that occurred after the time when the cleansed dataset was first generated.

Maintaining a dataset based on periodic cleansing of raw source data

Methods and systems are described herein for synchronizing communication records in computer networks. For example, the methods and systems may determine whether or not a first communication relates to a second and generate a recommendation that the communications relate to a single communication. In particular, the methods and systems described herein describe synchronizing communication records in computer networks based on detecting patterns in categories of metadata. For example, the methods and systems retrieve specific types of metadata and compare this metadata between communications in order to synchronize and/or deduplicate them.

Methods and systems for synchronizing communication records in computer networks based on detecting patterns in categories of metadata

In some implementations, an authorization device generate a decision to reject an authorization request that includes a credential associated with a user based on one or more inconsistencies between entity information provided in the authorization request and authorized entity information associated with the credential. The authorization device may transmit, to a biometric-enabled device associated with the user, a message that causes the biometric-enabled device to display a prompt indicating the one or more inconsistencies between the entity information provided in the authorization request and the authorized entity information associated with the credential. In some implementations, the prompt may further enable the user to provide a biometric input to authorize the entity information provided in the authorization request. The authorization device may grant the authorization request based on receiving information indicating that the user provided the biometric input to authorize the entity information provided in the authorization request.

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Mishawaka, IN, United States of America

Brice Elder