Abstract: Techniques are disclosed in which a computer system receives a transaction request and uses a federated machine learning model to analyze the transaction request. A server computer system may generate a federated machine learning model and distribute portions of the federated machine learning models to other components of the computer system including a user device and/or edge servers. In various embodiments, various components of the computer system apply transaction request evaluation factors to the portions of the federated machine learning model to generate scores. The server computer system uses the scores to determine a response to the transaction request.

Abstract: Methods and systems are presented for providing an asynchronous communication system for facilitating computing services to computer nodes across multiple availability zones. Each computer node includes a client application configured to receive a service request and to generate a request file based on the service request. The client application uploads the request file to a folder hosted by a file sharing system and shared with a processing server. When a new request file is detected in the folder, the processing server downloads the request file from the file sharing system. Based on performing one or more computing services according to the request file, the processing server generates a response file including output data from the computing services. The processing server uploads the response file to the folder hosted by the file sharing system. The client application downloads the response file and presents the output data on a device.

Abstract: A quantity sensing storage device enables automatic ordering of a product using an ordering engine that monitors quantity signals generated by a quantity sensor that is configured to provide the quantity signals based on a quantity of a first set of a product stored at the quantity sensing storage device. Base on the quantity of the first set, the ordering engine determines whether an order threshold has been satisfied. The quantity sensing storage device automatically provides instructions to a service provider device via a wireless communication subsystem to order a second set of the product in response to determining that the order threshold has been satisfied. The ordering engine continuously updates the order threshold such that when the second set of the product is received by a user of the quantity sensing storage device, an optimal portion of the first set of the product remains stored in the storage enclosure.

Abstract: A wearable device, e.g., a smart watch, may be connected to a communication device, such as a mobile smart phone, via Bluetooth or other Near Field Communication (NFC). In particular, the wearable device may have a touch screen that may serve as an extended display and/or user input device of the communication device. For example, a user may receive payment related notifications on the wearable device. The user also may operate the wearable device to make and/or receive payments, view transaction history, view and/or accept offers from nearby merchants, view and/or check in to nearby stores and etc. Further, the wearable device also may allow the user to make payment transactions in extreme environments not suitable for the communication device, such as under water.

Abstract: The present disclosure provides an exemplary system, method, and computer program product. The exemplary system includes at least one non-transitory memory storing user account information, wherein the information comprises a digital receipt associated with a user purchase and one or more conditions for delivering the digital receipt. The system further includes one or more hardware processors coupled to the at least one memory and operable to read instructions from the at least one memory to perform the steps of: receiving a payment request from a user; receiving at least one condition from the user for delivering a digital receipt associated with the payment request to at least one recipient; determining whether the at least one condition is satisfied; and delivering the digital receipt to the at least one recipient.

Abstract: There are provided systems and methods for on-device data privacy operations to prevent data sharing at user locations. A service provider, such as a merchant location of a merchant and/or associated online transaction processor, may provide additional services for to users via user data that may be tracked or stored of the user. However, the user may not want to share certain data with the merchant or other backend processor for privacy concerns. Thus, on-device data privacy operations may be used to detect when a user is at a location that has a corresponding privacy setting to hide or abstract user data for the location. The privacy setting may designate data to prevent from sharing when the user uses their device with devices associated with the location. Abstracted data associated with recommendations or actions to provide the user may be generated and provided to a merchant for the location.

Abstract: A system and method for selecting diverse product titles to display on a website are disclosed. In some example embodiments, the methods and systems described herein identify available products to be displayed, cluster the identified products based on their similarity to one another, select one or more products from each of the clusters, and display information, such as a title, associated with the randomly selected products.

Abstract: Machine learning techniques are disclosed that allow device contact list information to be leveraged in building better models that provide more accurate assessment of user transaction risks. A computing device may receive a contact list that includes a first set of user device identifiers and generates a contact graph for that user by associating the user device identifier with the first set as first-degree contacts. The computing device may then determine that a portion of the first set of the user device identifiers are stored in a contact database (e.g. on a server) and generate a user score based on user information associated with the first set, the contact graph, and a contact graph model. The computing device may provide the user score to a transaction assessment service as in input for the transaction assessment service deciding whether particular electronic transactions are approved for processing by an electronic service provider.

Abstract: There are provided systems and methods for requesting payment for selected items or services using payment tokens. A first user, such as a requester for a transaction, may initiate a transaction with a merchant for at least one item or service. Upon checkout for the transaction, the first user may request that a second user complete payment for the transaction, such as a parent, spouse, or relative. A payment provider may generate a token for the transaction and instruct the merchant to hold the transaction for a period of time. The token may be communicated to the second user, a payer, for the transaction. The second user may then decide to authorize or decline payment for the transaction. The token may be kept valid for a period of time and the transaction may be cancelled with the merchant if the token is not paid for within the period.

Abstract: There are provided systems and methods for flexible digital tokens with application programming interfaces for reduced computing calls. A service provider, such as an electronic transaction processor for digital transactions, may provide a processing system, stack and API that allows for generation of flexible payment tokens that can be used for electronic transaction processing with external service providers including social networking platforms and services. The processing system for the transaction processor may include an API in a compatible language with the APIs of the external service providers. Specific API calls and queries, which may correspond to GraphQL mutations, may be used to execute operations between the APIs of the interfacing systems to have a legacy processing system and API to generate a billing agreement. Once generated, the billing agreement may be tokenized, and a payment token used for payment processing.

Abstract: A cryptographic scheme associated with a transaction service is received at a first computer system. Subsequent to receiving the cryptographic schema, the first computer system performs a configuration process for a transaction to be performed with the transaction service. The configuration process includes receiving a request for transaction configuration information from a client device. The request includes a cryptographic token generated by a second computer system the transaction service. The first computer system determines whether to grant the request based on analyzing the cryptographic token according to the cryptographic schema. Based on the determining, the first computer system sends transaction configuration information. The configuration process is performed by first computer system independent of communication between the second computer system and the first computer system.

Abstract: There is provided systems and method for generating sale transaction from voice data input by a user. A user device may receive voice data including a preference for purchasing an item. The user device may convert the voice data to the preferences and perform a search for a sales transaction corresponding to the preferences. The search may include parameters about the user, such as a location. The sales transaction may include purchase prices, times, locations, or other relevant data. A user may accept or decline the sales transaction with additional user data. If the user accepts the sales transaction, the sales transaction may be completed with a payment provider and a transaction history given to the user for later redemption of the item. If the user declines the sales transaction, further sale transactions with additional items may be present to the user.

Abstract: There are provided systems and methods for sentence level dialogue summaries using unsupervised machine learning for keyword selection and scoring. A service provider, such as an electronic transaction processor for digital transactions, may provide live chat service channels for assistance through live agents and chatbot services. When interacting with these channels over a period of time, a user may create a dialogue with multiple different live agents and/or chatbots. These chat sessions may be asynchronous but have important and relevant information for future live agents to review. Thus, the service provider may provide a dialogue summarizer, which may summarize a dialogue automatically to a number of most relevant sentences. This may be done using an unsupervised machine learning system that utilizes different machine learning algorithms to select and rank keywords within the sentences. The sentences are then scored and highest scored sentences are output as a summary.

Abstract: Systems and/or techniques for facilitating online-monitoring of machine learning models are provided. In various embodiments, a system can receive monitoring settings associated with a machine learning model to be monitored. In various cases, the monitoring settings can identify a first set of data features that are generated as output by the machine learning model. In various cases, the monitoring settings can identify a second set of data features that are received as input by the machine learning model. In various aspects, the system can compute a first set of statistical metrics based on the first set of data features. In various cases, the first set of statistical metrics can characterize a performance quality of the machine learning model. In various instances, the system can compute a second set of statistical metrics based on the second set of data features.

Abstract: Systems, computer-implemented methods, apparatus, and/or computer program products that can facilitate electronic generation and/or display of enhanced, transaction-based QR codes are provided. In various embodiments, a system can receive, from an electronic beacon of a point-of-sale device, context data characterizing a transaction facilitated by the point-of-sale device. In various instances, the system can generate a quick response (QR) code based on the context data and based on financial instrument data, such that the context data and the financial instrument data are embedded within or correlated to the QR code. In various aspects, the system can visually render the QR code on an electronic display, such that the QR code is scannable by the point-of-sale device.

Abstract: Systems and methods for providing merchant/customer interaction include determining that a tablet computer is in a merchant orientation, retrieving merchant product information according to a received instruction and merchant orientation information, and displaying a merchant screen on the tablet computer that includes the merchant product information according to the merchant orientation information. A change in the orientation of the tablet computer enclosure/stand is then detected from the merchant orientation to a customer orientation. In response, the merchant screen is transitioned on the tablet computer display to a customer screen as the tablet computer enclosure/stand changes orientations by moving the merchant screen and the customer screen linearly while in a stacked orientation.

Abstract: Systems and/or techniques for facilitating image forgery detection via headpose estimation may include a system that can receive a document from a client device. The system can identify, by executing a first trained machine learning model, an object that is depicted in the document. The system can determine, by executing a second trained machine learning model, a pose of the object. The system can determine, by executing a third trained machine learning model, whether the document is authentic or forged based on the pose of the object. The system can, in response to determining that the document is forged, transmit an unsuccessful validation message to the client device.

Abstract: There are provided systems and methods for iframe injection in mobile web browser applications for web browser extension opt-in. A service provider may provide a mobile application web browser extension, which may operate in conjunction with a mobile application web browser. The extension may interface with the web browser in order to determine data for browsed websites and user interactions and provide offers and savings to users during electronic transaction processing. In order to use the extension with the web browser, an opt-in preference and permission may be required. To provide this opt-in, the extension may cause the web browser to navigate to and load a webpage of the service provider. The extension may then inject an iframe that calls another domain, and a script of the extension executes in the iframe. The script may then infer that a permission has been granted.

Abstract: A payment device comprising of a housing, a slot for insertion of a user instrument located on a front surface of the housing, and wherein the housing includes a smart card interface integrated circuit that is configured to read an EMV chip located on the user instrument, and a universal serial bus (USB) type C male connector configured to be inserted into a female connector on a computing device, wherein the USB type C male connector is located on a back surface of the housing, and wherein a size of the USB type C male connector is configured so that when the USB type C male connector is inserted into the female connector on the computing device, the back surface of the housing is within a distance of three centimeters of a surface of the computing device.

Abstract: Methods and systems are presented for predicting a likelihood of an occurrence of an event, such as a dispute or a chargeback, associated with an electronic transaction based on monitoring user interactions of a user with one or more computing systems after the electronic transaction has been conducted. The electronic transaction may involve a purchase of a product and/or service from a merchant. After the transaction is conducted, user interactions of the user with the one or more computer systems, such as a website of the merchant involved in the transaction, a website of another merchant, and a website of a payment service provider may be monitored. A machine learning model may then be used to predict whether the event associated with the transaction will occur in the future based on the monitored user interactions.