Abstract: Systems and methods for automated servicing of a subsidized loan are disclosed. An example system may include a crowdsourcing services circuit to collect information related to a set of entities involved in a set of subsidized loan transactions and a condition classifying circuit including a model and an artificial intelligence services circuit to classify a set of parameters of the set of subsidized loans based on information from the crowdsourcing services circuit, where the model is trained using a training data set of outcomes related to subsidized loans. The example system may further include a smart contract circuit for automatically modifying a term or a condition of the subsidized loan based on the classified set of parameters from the condition classifying circuit.

Abstract: The present disclosure involves systems, software, and computer implemented methods for automatically generating acquisition IDs and using them to track and record how products are identified, offered, and sold, as well as how customers respond to particular variations of product offers. The acquisition ID can be associated with any product sale, transaction completion, or account creation initiated using or otherwise identifying or associated with the acquisition ID, where the connection to the acquisition ID can be maintained and retained with ongoing records associated with the interaction and created account, transaction, and/or product purchase. Using the stored information and the acquisition IDs, an organization can precisely determine what products were sold using which marketing tactic, campaign, or channel through which the transaction occurred and/or was initiated, among others.

Abstract: A system and method for automated blockchain custody service for managing a set of custodial assets with block chain authenticity verification is disclosed.

Abstract: A computer-implemented method for printing customized 3D medication based on the current user data and one or more medical records of the user. The method obtains current user data via one or more user IoT sensors and accesses one or more medical records of the user. The method further determines a medication design based on the obtained current user data and the accessed one or more medical records of the user and prints a 3D medication based on the determined medication design.

Abstract: Disclosed are a system, method and apparatus for classification of data in a machine learning system. In one aspect, a method for classification of data in a machine learning system through one or more computer processors is disclosed. Further, generating, through one or more computer processors, a data classifier using a first dataset and determining an accuracy value of the data classifier to achieve a predefined model accuracy threshold. Still further, iterating, through one or more computer processors, calibration of the first dataset based on a set of parameters until the accuracy value matches or exceeds the predefined model accuracy threshold value. Further, the calibration comprises a user input to indicate a correctness of a presented subset of data from a second dataset and using the above to generate an enhanced data classifier for the classification of data.

Abstract: Systems and methods are disclosed for detecting a suspicious and/or a non-suspicious activity during an electronic transaction performed by a user device. One method comprises identifying, by a monitoring and detection component, a starting check point in the electronic transaction. The monitoring and detection component may then receive contextual data from one or more sensors of the user device. Based on the contextual data and a machine learning model, the monitoring and detection component may determine whether an expected behavior occurred. Entry of user credentials may be enabled in response to determining that the expected behavior occurred, whereas the electronic transaction may be terminated in response to determining that the expected behavior did not occur.

Abstract: A data processing system for recommending insurance plans implements obtaining an electronic copy of demographic information associated with a user; analyzing the demographic information with a first machine learning model to recommend a bundle of insurance policies based on the demographic information, wherein the first machine learning model is configured to group insured people having similar demographics into clusters and to generate the bundle of insurance policies based on predicted medical insurance consumption associated with a respective group into which the model predicts that the first user falls; customizing the recommended bundle of insurance policies based on the demographic information associated with the user to generate a customized bundle of insurance policies; generating an insurance recommendation report that presents the customized bundle of insurance policies to the user; and causing a user interface of a display of a computing device associated with the user to present the insurance rec

Abstract: A computer-implemented method is provided for identifying potential individuals to contact in a campaign of interest. The method includes receiving campaign data including description about the campaign of interest and information about the potential individuals to contact for the campaign of interest and selecting a plurality of trained machine learning models from a library of trained machine learning models based on the campaign data. The library of trained machine learning models is created from data of historical campaigns administered, and each of the selected plurality of trained models corresponds to a historical campaign that is within a similarity threshold from the campaign of interest. The method also includes scoring a pool of existing customers using the select plurality of trained machine learning models and identifying the potential individuals to contact in the campaign of interest by ranking the existing customers by their corresponding propensity scores.

Abstract: Systems and methods for using social network data to validate a loan guarantee are disclosed. An example system may include a social networking input circuit to interpret a loan guarantee parameter; a social network data collection circuit to collect data using a plurality of algorithms that is configured to monitor social network information about an entity involved in a loan in response to the loan guarantee parameter; and a guarantee validation circuit to validate a guarantee for the loan in response to the monitored social network information.

Abstract: Methods, systems, and apparatuses for block chain security schemes for electronic cash tokens are described herein.

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 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: 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 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: An online system receives information describing a target group of online system users from a third party system that includes one or more user properties, which may identify an action performed by a an online user within a time interval to include the user in the target group. When an opportunity to present advertisement requests to a user is identified, the online system retrieves actions associated with the user and times associated with the actions. If an action associated with the user matches the action identified by the user properties and occurred within the time interval identified by the user properties, and other characteristics of the user satisfy at least a threshold number of the user properties, the online system includes the user in the target group. Advertisement requests having targeting criteria, including the target group, satisfied by characteristics of the user are evaluated for presentation to the user.

Abstract: A method of reducing a future amount of electronic fraud alerts includes receiving data detailing a financial transaction, inputting the data into a rules-based engine that generates an electronic fraud alert, transmitting the alert to a mobile device of a customer, and receiving from the mobile device customer feedback indicating that the alert was a false positive or otherwise erroneous. The method also includes inputting the data detailing the financial transaction into a machine learning program trained to (i) determine a reason why the false positive was generated, and (ii) then modify the rules-based engine to account for the reason why the false positive was generated, and to no longer generate electronic fraud alerts based upon (a) fact patterns similar to fact patterns of the financial transaction, or (b) data similar to the data detailing the financial transaction, to facilitate reducing an amount of future false positive fraud alerts.

Abstract: Systems and methods for sharing user inventory information to initiate peer-to-peer exchanges of digital assets that are usable within an online gaming platform are disclosed. Exemplary implementations may: receive a sharing request for information regarding a first user inventory; access a blockchain to obtain asset information; transfer the asset information in response to the sharing request; receive an offer request for the transfer of ownership of a first digital asset from a first user to a second user; if the offer according to the offer request is accepted, receive a transfer request and transfer the ownership of the first digital asset as requested.

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.