Abstract: A payment gateway is configured to directly access a revenue stream and financial information about the revenue stream. A machine learning (ML) model is trained to continuously process the financial information about the revenue stream to continuously analyze and score the revenue stream. A smart contract factory is responsive to the scoring by the ML model to generate at least one smart contract on a distributed, decentralized network. The smart contract is programmed to receive payments in stablecoins with respect to revenue stream.

Abstract: An on-board signage system includes one or more vehicles, a display device installed in each of the vehicles, and a signage controller, in which the signage controller is configured to function as a post collecting unit that collects a post content item uploaded to an SNS site, a post analyzing unit which extracts a location relating to the post content item as a relevant location, a post database that stores post-related information obtained from the post content item in association with the relevant location, and a selector that selects at least one of a travel route of the vehicle and an image to be assigned to the vehicle, based on information stored in the post database, and transmits the selected travel route or image to the vehicle.

Abstract: Verifiable order message handling for electronic auctions. Electronic order messages are received, with at least one message including an order of a predetermined type having sell order information associated with an entity having securities not previously registered for transactions. Requests for participation in an electronic auction are identified from among the messages. The requests include auction-only order information, with at least one request including the order of the predetermined type. It is determined whether the sell order information in the order of the predetermined type meets a predetermined auction condition based on an auction price. When the sell order information meets the predetermined auction condition, the order is permitted to participate in the electronic auction, such that the order is executed in full in the electronic auction. When the sell order information does not meet the predetermined auction condition, the electronic auction is canceled.

Abstract: A system for electronic data interchange (EDI) management includes a memory for storing the EDI document data and a machine learning model representing a set of features of EDI documents and a corresponding status. The system further includes a processor and a non-transitory computer readable medium storing instructions for: accessing an EDI file, the EDI file comprising envelope metadata for an envelope and a first EDI document; and translating the EDI file into a first translated EDI document containing the envelope metadata and a set of EDI document data extracted from the first EDI document, the first translated EDI document formatted according to a hierarchical structure comprising attributes translatable into features processable by the machine learning model to determine a status of the first EDI document.

Abstract: A method includes: processing a request to execute a transaction of a virtual asset of a video game; responsive to the request, accessing a blockchain to perform an anti-fraud verification, including analyzing data of a prior transaction involving the virtual asset; responsive to the anti-fraud verification providing a result that does not indicate fraudulent activity, then generating transaction data based on an identifier for the first user account, an identifier for the second user account, an identifier for the virtual asset, and state data of the virtual asset, and submitting the transaction data to a node network, to write the transaction data to a block of the blockchain; receiving confirmation of the writing of the transaction data; responsive to receiving the confirmation, then updating a registry of virtual assets to transfer ownership of the virtual asset from the first user account to the second user account.

Abstract: A processor may receive first issue data. The first issue data may be associated with input data entered by a user into a user interface on the issue submission application. The processor may analyze the first issue data. The processor may select a first set of prompted issue descriptions. The first set of prompted issue descriptions may be selected based on analyzing the first issue data. The processor may prompt the user to select a subset of the first set of prompted issue descriptions. The processor may receive from the user a selected subset of the first set of prompted issue descriptions. The processor may output an identified issue description. The identified issue description may be generated based on the selected subset of the first set of prompted issue descriptions.

Abstract: A computer system including a processor in communication with a memory and a database may be provided. The processor may be programmed to: (i) execute a query on the database including a list of user identifiers associated with a plurality of users, (ii) receive license data associated with the user identifiers including a list of licenses and respective license renewal data associated with each user, (iii) determine, from the license data, that one or more licenses of a group of users is in a renewal period, (iv) notify each user of the group of users of the one or more licenses in the renewal period, (v) pre-populate a license renewal application for the one or more licenses in the renewal period the group of users, (vi) transmit the pre-populated application to be approved by the group of users, and (vii) receive the approved pre-populated application from the group of users.

Abstract: A method of detecting whether electronic fraud alerts are false positives includes receiving data detailing a financial transaction, inputting the data into a rules-based engine that determines whether to generate an electronic fraud alert for the financial transaction based upon the data, and, when an electronic fraud alert is generated, inputting the data into a machine learning program trained to identify one or more facts indicated by the data. The method may also include determining whether the identified facts can be verified by customer data and, in response to determining that the facts can be verified, retrieving or receiving first customer data. The method may further include verifying that the electronic fraud alert is not a false positive based upon analysis of the first customer data, and transmitting the verified electronic fraud alert to a mobile device of the customer to alert the customer to fraudulent activity.

Abstract: Techniques for resource allocation with content creators are described that overcome the challenges of conventional techniques by supporting customized digital content generation and resource allocation specified by content creators of digital content. In one example, a content provider system, based on user input received via a control, specifies the portions of a resource allocation to be shared. A first portion is configured to be shared with a content creator of digital content, the digital content including service access data configured to access a digital service. A second portion is also configured to be shared with a client device that utilizes the service access data to access the digital service. Digital content is generated based on the specified portions and is transmitted. Upon access by the client device to the digital service, an indication of receipt of the first portion of the resource allocation is displayed by the content provider system.