Abstract: A method performed by at least one computing device. The method includes receiving a credit request from a self-checkout device before a customer completes an instore checkout process and sending a request for a Uniform Resource Locator (“URL”) to one or more authentication computing devices. The authentication computing device(s) send the URL to the mobile device. The method includes sending a credit application to the mobile device after the customer selects the URL, receiving a submission of the credit application from the mobile device, approving credit based on the submission, and forwarding a code to the mobile device. The code indicates that the credit is to be used to complete the instore checkout process when scanned by the scanner.

Abstract: A data classification system obtains a data set including first data associated with a first characteristic and second data associated with a second characteristic. In response to obtaining the data set, the system uses a classification model to generate a classification by classifying the first data into majority data and the second data into minority data. From the classification and using the classification model, the system determines a loss. The system modifies the classification model based on this loss to generate an updated classification model. The system uses the updated classification model to re-classify a subset of the first data into the minority data and a subset of the second data into the majority data.

Abstract: Systems and methods provide a framework through which user data is automatically propagated to different service provider systems through one or more decentralized distributed ledger nodes in response to modification of the user data and to changes to service provider systems authorized to access the user data.

Abstract: Disclosed embodiments may provide a framework to implement post-purchase tender switches. For example, following a transaction made with a particular payment instrument, a customer may be offered the ability to apply for a preferred payment instrument and/or to switch his or her tender type to the preferred payment instrument for the previous transaction.

Abstract: A system architecture of a gift transaction system is disclosed. The gift transaction system can include a buyer interface module, a recipient interface module, a merchant backend interface module, a store front interface module, a curation module, a reminder module, an analytics module, or a media plug-in interface module. A method of operating the gift transaction system under the system architecture includes: providing an embedded widget on a website to determine gift intent to initiate a gift transaction by a buyer account for a recipient account; generating a gift buyer interface for a first client device to personalize a gift package including a gift item; generating a gift recipient interface for a second client device to customize the gift package; and communicating with a merchant backend system to complete the gift transaction to ship the gift package.

Abstract: Disclosed embodiments may provide a framework to measure and leverage the observable attributes that most directly affect the data stability of a customer. In addition, embodiments track the dynamics of the observable components that sustain the data stability of a customer. Embodiments may be used to estimate the stability of a variety of conditions for various contexts, such as the stability of a computing system over time.

Abstract: Systems, devices, methods, instructions, and other implementations are described for network data management. One embodiment involves request data received at a device associated with a digital lockbox, where the request data includes identifying information for an originating device associated with a location and is associated with a user device. A unique token is generated with the identifying information. The unique token can be used to tokenize a network link to create a secure one-time link. The system transmits the one-time link, which can then be used to facilitate secure communications between a computing system associated with the originating device and the user device.

Abstract: Systems and methods for a dynamic encryption model in which dynamic encryption keys are associated with an access token having an expiration time. The access token is generated for a user session of a user application seeking to make API calls to a service provider system. When the access token expires, or becomes otherwise invalid, the dynamic encryption keys are discarded, and any further API calls are made using an updated access token and updated dynamic encryption keys. The dynamic encryption keys are used to encrypt specially designated fields of API calls and/or API call results.

Abstract: Systems and methods are described for analyzing user data, for instance for eligibility of a user for one or more programs. The user data is analyzed in two or more stages, with each stage including rules and/or program qualification criteria specific to that stage. In some examples, the systems and methods used trained machine learning models for at least one stage of the analysis. The systems and methods disclose identifying one or more programs that the user is eligible for, and in some cases, applying the one or more programs to the user's account.

Abstract: Examples describe data security for communication systems. One example includes validating a user device using secure user data and generating a long term token for the user device, where the long term token is generated with a randomized unique token system. The method further includes receiving a transaction communication associated with a secure transaction, the transaction communication including the long term token, generating a transaction token that is different than the long term token for the transaction communication using the long term token from the transaction communication, and facilitating the secure transaction using the transaction token and the long term token.

Abstract: Examples describe data security and routines structured to avoid conflicts. One example includes accessing data for a merchant website including a framework with a first routine for a function, and accessing an account security element for the merchant website with a second routine associated with an account security system for the function. The second routine is optimized to avoid conflicts with the first routine. The framework is automatically updated while the second routine is maintained with no changes. The merchant website data is then transmitted with the updated first routine and the account security element with the second routine, where the updated first routine and the second routine facilitate data security on the client device without framework conflicts when the updated first routine for the function and the second routine for the function operate concurrently on the client device.

Abstract: A distributed acquisition environment downloads a snapshot of a large dataset from one or more remote environments. The download may occur regularly to enable the distributed acquisition environment to operate on a nearly up-to-date instance of the large dataset. The download may begin when a computing device receives a request to load a dataset into memory of the distributed acquisition environment. The dataset may be divided into one or more data segments. Each data segment of the one or more data segments is associated with a data loader of one or more data loaders of the distributed acquisition environment. The one or more data segments are transferred to a temporary location within a cloud environment. The data loaders of the distributed acquisition environment to then download the one or more data segments from the temporary location.

Abstract: In one aspect, a microservice based method of processing a request includes receiving a request for a service from an end terminal; identifying one or more microservices for servicing the request; deploying the one more microservices for processing the request; and servicing the request using the one or more microservices, wherein the one or more microservices operate in a combination of synchronous and asynchronous steps to service the request.

Abstract: Systems and methods are provided for generating surprise gift objects presentable to intended recipients based on real-time location data associated with recipients. Users are provided with recommendations for surprise gift objects that can be provided to recipients based on information associated with recipients and inventory data associated with locations through which options associated with these surprise gift objects are made available. Through these systems and methods, recipients are notified of the availability of surprise gift objects based on their real-time location data. As recipients select different options associated with these surprise gift objects or otherwise redeem these surprise gift objects at the one or more locations, data corresponding to these redemptions is used to further enhance the systems and methods in order to provide more accurate tailored recommendations to users wishing to send surprise gift objects to recipients and to the recipients when redeeming surprise gift objects.

Abstract: Aspects of a dynamic offer system are described. In one example, a method involves receiving a data feed of offer data, generating a set of current offers in a database using a set of offer rules and the data feed, receiving merchant configuration data associated with a merchant portal, and dynamically selecting current merchant offers from the set of current offers in the database using the merchant configuration data. A request is received for the current merchant offers, where when the request for the current merchant offers is received from a customer device, the request includes dynamic customer data customized based on user selections, one or more offers of the current merchant offers based on the dynamic customer data are dynamically selected, and a transaction between the customer device and the merchant portal associated with the one or more offers dynamically selected by the computing device is facilitated.

Abstract: A device may capture real-time images of a product. Capturing may include using an outward-facing sensor on a device. A device may identify the product by using an identification machine learning model. A device may obtain user interaction data corresponding to previous images displayed on the device. A device may identify available offers. A device may identify a set of offers from the available offers using an offer selection machine learning model trained to automatically select offers presentable to users through devices. The offer selection machine learning model may be trained using a dataset of historical interaction data and corresponding offers. A device may present the set of offers through the device. A device may monitor in real-time user interaction with the set of offers. A device may update the offer selection machine learning model according to the real-time user interaction with the set of offers.

Abstract: Data selection systems and techniques are described. For instance, a system receives a data set with a plurality of data elements. The system generates a plurality of random values. The system generates a ranking of the plurality of random values. The system selects a subset of the plurality of data elements based on a comparison between the ranking and a predetermined threshold. The predetermined threshold is based on a predetermined proportion of the plurality of data elements to be included in the subset. The system outputs a randomization scheme that includes the ranking and the predetermined proportion, wherein a second selection of a second subset of the plurality of data elements is based on the randomization scheme. The system output an indication of the subset and the second subset.

Abstract: Examples presented herein describe secure point of sale (POS) operations. One example is a method including receiving, at a mobile device, a communication associated with a custom tender payment for a secure transaction payment, where the mobile device includes a custom payment application configured for the secure transaction payment with a point of sale (POS) device. The method includes receiving account data associated with a user account selection for the custom tender payment for the secure transaction payment, transmitting an account signal including the account data, where when the account signal is transmitted to an integration server as part of the secure transaction payment, the account signal is not transmitted to the POS device, and receiving an authorization communication, where when the authorization communication is received by the mobile device from the integration server, the authorization communication is not communicated to the mobile device via the POS device.

Abstract: Examples described herein include implementations for big-data validation. One aspect includes generating a configuration file including dynamic matching data describing a first plurality of data entries and a second plurality of data entries, and generating a data action file. A plurality of data queries are generated based on the dynamic matching data indicated in the configuration file. The plurality of data queries are dynamically executed in parallel, including execution of a plurality of simultaneous data queries to the data source system. Fields of the first plurality of data entries and the second plurality of data entries are matched using the key type and the value structure, corresponding fields of the first data fields and the second data fields having a data mismatch are identified, and a mismatch database entry for the corresponding fields having the data mismatch is automatically generated.

Abstract: Examples describe data security for communication systems. One example includes validating a merchant system using merchant data and generating a set of merchant credentials. The set of merchant credentials is then used in authentication to facilitate a secure transaction, which involves automatically generating transaction data with a tokenized client account number associated with the secure transaction. A refund request associated with the secure transaction is received with the set of merchant credentials that are used for automatically authenticating the merchant system. The example then involves accessing a database that includes the transaction data for automatically facilitating settlement of a refund payment using the authenticated merchant system and the transaction data.