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 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: 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: 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: A digital story includes textual, visual, and/or audio aspects. Generation of a new digital story and/or editing of an existing digital story can include, for instance, coordinating presentation of textual, visual, and/or audio aspects of the digital story. A digital story can be viewed and/or accessed by a user remote from one or more authors of the digital story.

Abstract: An image acquisition method, an image acquisition device and a storage medium are provided. The method includes: acquiring a preview image collected by a camera; detecting a target area in the preview image based on a preset composition model; and in response to detecting the target area, acquiring an image including the target area as a target image.

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: Methods for creating emails with complex graphics and customized web fonts that are ensured to render consistently across multiple platforms and email client applications and systems that ensure consistent rendering of created emails with complex graphics and customized web fonts by automatically transforming, completely transparently, the contents of each created email to a form that renders properly across the platforms and email clients are disclosed.

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

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.