Cigna Intellectual Property, Inc.

Evernorth Strategic Development, Inc.

Jeffrey R McCormick

A computerized method includes receiving, from a user, a request to perform an operation on data stored in a shared data resource, which stores physically integrated data from multiple tenants. The method includes obtaining a credential document from the user that includes a session portion that is specific to a current session of the user and a set of restriction criteria. The method includes determining, using user attributes in the credential document, a set of tenants whose data the user is authorized to access; evaluating, based on the session portion, whether the set of restriction criteria restricts the user from performing the operation; and in response to the evaluating identifying that the user is not restricted from performing the operation, performing the operation on a subset of the shared data resource. The subset is limited to data stored in the shared data resource that corresponds to the set of tenants.

Digital data passport and visa credentialing for data authorization

A computer system includes memory hardware configured to store computer-executable instructions and processor hardware configured to execute instructions. The instructions include receiving, from a user device, a user verification request. The user verification request includes user identity credentials, a login context describing a login event, and a request for access to a computer system object. The instructions include determining whether the user identity credentials are verified. The instructions include, in response to determining that the user identity credentials are verified, requesting a user token based on the user identity credentials and the login context. The user token specifies entitlements associated with the user identity credentials. The instructions include determining whether the user token specifies entitlements sufficient to access the computer system object. The instructions include, in response to determining that the user token specifies entitlements sufficient to access the computer system object, permitting access to the computer system object.

Computer user credentialing and verification system

An apparatus may be configured to determine an industry object model for a data set of an enterprise; and generate an archive package for an archive time point by generating a set of global objects such that each global objects of the set of global objects is represented in the data set and for a respective data source of the set of data sources, generating a set of data source objects based on the industry object model, associating the set of data source objects with the set of global objects, and storing, in the archive package, the set of data source objects and the associated global objects for the respective data source.

Data archival system and method

A computer-implemented method includes determining whether historical profile data structures are stored in a database with corresponding structured supplemental data and selected health care plan option identifiers of a set of health care plan option identifiers. The method includes generating historical feature vectors using the historical data structures stored in the database or generating the historical feature vectors using created sample profile data structures. The method includes training machine learning models using the generated historical feature vectors, selecting one of the machine learning models for use in generating recommendation outputs, presenting an interactive voice interface to an entity to generate audio questions and prompts for obtaining response data from the entity, classifying voice survey responses of the entity, and generating feature vectors. The method includes processing, using the selected machine learning model, the feature vectors to generate the recommendation outputs, and transforming a user interface to display the recommendation output.

Machine learning systems for computer generation of automated recommendation outputs

An apparatus may be configured to determine an industry object model based on an industry of a data set of an enterprise; generate an archive package for an archive time point by, for each data source, determining archival data of the data source to be archived and transforming the archival data of the data source into a set of data source objects based on the industry object model, and storing, in the archive package, the data source objects for each data source; identify a subset of the data source objects to be purged based on a purge time point; and remove the subset of the data source objects from the archive package. An apparatus may also be configured to generate and store a set of global objects that are represented in the data set, and to associate the set of data source objects with the set of global objects.

A computer system includes memory hardware and at least one processor. The memory hardware stores a credential database and computer-executable instructions. The credential database includes multiple user profiles and multiple credentials. Each credential specifies one or more function privileges for each user profile that has been granted the credential. The instructions include receiving a specified one of the multiple credentials and a specified one of the multiple user profiles, granting the specified one of the multiple credentials to the specified one of the multiple user profiles, receiving a verification request including a user profile identifier, contextual qualities and a requested function, retrieving the credential granted to the user profile associated with the user profile identifier, determining whether the requested function is included in the one or more function privileges specified by the retrieved credential, and permitting the verification request or denying the verification request according to the determination.

A computerized method of automatically generating a recommendation output includes training a machine learning model with historical feature vector inputs to generate a recommendation output, generating a set of inputs specific to an entity, and transforming the set of inputs into a profile data structure. The profile data structure includes multiple attributes. The transforming includes, for each attribute, assigning a preference according to the set of inputs. The method includes obtaining structured supplemental data associated with the entity. The method includes obtaining a set of option identifiers by filtering the option identifiers according to option criteria specific to the entity. The method includes creating a feature vector input according to the set of option identifiers, the structured supplemental data, and the assigned preferences of the profile data structure. The method includes processing, by the machine learning model, the feature vector input to generate the recommendation output.

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Cheshire, CT, United States of America

Jeffrey R McCormick