Abstract: In some implementations, a device may obtain first location data associated with one or more exchanges, where the first location data is associated with a first level of granularity. The device may determine second location data associated with the one or more exchanges based on records associated with the one or more exchanges, where the second location data is associated with a second level of granularity that is higher than the first level of granularity. The device may detect an authentication event associated with an access attempt to the account. The device may provide, based on detecting the authentication event, one or more authentication queries that are based on the second location data. The device may authenticate the access attempt to the account based on one or more responses to the one or more authentication queries.

Abstract: In some implementations, a credential system may create a virtual credential bound to a physical location associated with a transacting entity based on a request from a user device. The credential system may send information to a transaction terminal at the physical location bound to the virtual credential to register the virtual credential and identify a user that owns an account associated with the virtual credential. The credential system may provide, to the user device, tokenized information related to the virtual credential. The credential system may receive the tokenized information from a transaction terminal requesting authorization for the transaction. The credential system may send, to the transaction terminal requesting the authorization for the transaction, an authorization decision associated with the transaction based on whether the transaction terminal is present at the physical location bound to the virtual credential.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: In some implementations, a device may receive, via an application, a record log associated with an account that is registered to the device. The device may determine that a user interface of the application is presenting the record log on a display of the device. The device may obtain record metadata that identifies a characteristic of a record of the record log. The device may analyze a local data structure of the device to identify image data associated with an event involving the record. The device may determine that the record is associated with the event based on the characteristic and image metadata associated with the image data, wherein the image metadata is stored in the local data structure in association with the image data. The device may cause the user interface to present, in association with the record, an image associated with the image data on the display.