Designation of a trusted user

Abstract

A device receives a request for a trust designation for a user that is to utilize a merchant application to interact with one or more other users, wherein the merchant application includes one or more interfaces that allow the user to interact with the one or more other users while remaining anonymous or partially anonymous. The device obtains user data for the user based on information included in the request. The device determines the trust designation for the user by using a data model that has been trained using machine learning to process the user data. The device permits at least one of the one or more interfaces of the merchant application to display the trust designation, wherein the user remains anonymous or partially anonymous while the trust designation is displayed.

What is claimed is: 
     
         1 . A method, comprising:
 receiving, by a device and based on receiving a request, via a first communication interface, for a trust designation for a user, user data via a second communication interface different from the first communication interface;   determining, by the device and based on receiving the user data, the trust designation using a data model trained using machine learning,   wherein the data model is configured to generate trust tokens by:   accessing a data structure that maps the trust tokens to trust designations including the trust designation, or   using one or more trust determination techniques that defines rules that map ranges of user data values, including at least one data value associated with the user data, to one or more of the trust tokens or the trust designations, and   wherein each of the trust tokens identify a particular one of the trust designations including the trust designation; and   providing, by the device and based on determining the trust designation, a response, including a particular trust token, associated with the user, of the trust tokens, using the second communication interface.   
     
     
         2 . The method of  claim 1 , wherein the request is received from a merchant server, and wherein the particular trust token is provided to the merchant server. 
     
     
         3 . The method of  claim 2 , wherein the user has an account with a merchant application, associated with the merchant server, and another account with a source different from the merchant application. 
     
     
         4 . The method of  claim 1 , wherein the request includes second user data generated by a user device, different from the device, and associated with the user. 
     
     
         5 . The method of  claim 1 , wherein the request includes second user data, and wherein the user data includes a subset of the second user data. 
     
     
         6 . The method of  claim 1 , further comprising:
 training, using the machine learning, the data model based on a set of features associated with historical data associated with the user,   wherein generating the trust designation is based on training the data model.   
     
     
         7 . The method of  claim 6 , wherein the historical data includes one or more of:
 historical transaction data identifying one or more transactions made via an account of the user,   historical account data for the account of the user,   historical location data associated with the account of the user,   historical user identification data identifying one or more characteristics of the user,   historical browser fingerprint data associated with browser usage of the user, or historical credit data identifying credit information of the user.   
     
     
         8 . The method of  claim 1 , further comprising:
 processing, based on receiving the request, a transaction, associated with the user, to verify the user,
 wherein generating the trust designation is based on processing the transaction. 
   
     
     
         9 . The method of  claim 1 , further comprising:
 obtaining, based on providing the response, new user data different from the user data;   determining a new trust designation, different from the trust designation, based on the new user data; and   providing, based on determining the new trust designation, a response including a new trust token.   
     
     
         10 . A device, comprising:
 one or more memories; and   one or more processors, coupled to the one or more memories, configured to:   receive, based on receiving a request, via a first communication interface, for a trust designation for a user, user data via a second communication interface different from the first communication interface;   determine, based on receiving the user data, the trust designation by using a data model trained using machine learning,   wherein the data model is configured to generate trust tokens by:   accessing a data structure that maps the trust tokens to trust designations including the trust designation , or   using one or more trust determination techniques that defines rules that map ranges of user data values, including at least one data value associated with the user data, to one or more of the trust tokens or the trust designations;   wherein each of the trust tokens identify a particular one of the trust designations including the trust designation; and   provide, based on determining the trust designation, a response, including a particular trust token, associated with the user, of the trust tokens, using the second communication interface.   
     
     
         11 . The device of  claim 10 , wherein the request is received from a merchant server, and wherein the particular trust token is provided to the merchant server. 
     
     
         12 . The device of  claim 10 , wherein the one or more processors are further configured to:
 train, using machine learning, the data model based on a set of features associated with historical user data,   wherein generating the trust designation is based on training the data model.   
     
     
         13 . The device of  claim 10 , wherein the one or more processors are further configured to:
 process, based on receiving the request, a transaction of the user to verify the user,   wherein generating the trust designation is based on processing the transaction.   
     
     
         14 . The device of  claim 10 , wherein the one or more processors are further configured to:
 obtain, based on providing the response, new user data different from the user data;   determine a new trust designation, different from the trust designation, based on the new user data; and   provide, based on determining the new trust designation, a response including a new trust token.   
     
     
         15 . A non-transitory computer-readable medium storing a set of instructions, the set of instructions comprising:
 one or more instructions that, when executed by one or more processors, cause the one or more processors to:   receive, based on receiving a request, via a first communication interface, for a trust designation for a user, user data via a second communication interface different from the first communication interface;   determine, based on receiving the user data, the trust designation using a data model trained using machine learning,   wherein the data model is configured to generate trust tokens by:   accessing a data structure that maps the trust tokens to trust designations including the trust designation, or   using one or more trust determination techniques that defines rules that map ranges of user data values, including at least one user data value associated with the user data, to one or more of the trust tokens or the trust designations, and   wherein the trust tokens identify a particular one of the trust designations including the trust designation; and   provide, based on determining the trust designation, a response, including a particular trust token, associated with the user, of the trust tokens, using the second communication interface.   
     
     
         16 . The non-transitory computer-readable medium of  claim 15 , wherein the trust designation is generated using the data model. 
     
     
         17 . The non-transitory computer-readable medium of  claim 15 , wherein the trust designation is generated using the one or more trust determination techniques. 
     
     
         18 . The non-transitory computer-readable medium of  claim 15 , wherein the data model is a neural network. 
     
     
         19 . The non-transitory computer-readable medium of  claim 15 , wherein the trust designation includes at least one of a designation, as a trusted or untrusted user, or a designated trust level of the user. 
     
     
         20 . The non-transitory computer-readable medium of  claim 15 , wherein the user data includes at least two or more of:
 location data that identifies a geographic location associated with an account of the user,   transaction data that identifies one or more transactions made via the account of the user,   account data for the account of the user,   user identification data that identifies one or more characteristics of the user,   browser fingerprint data associated with browser usage of the user, or credit data that identifies credit information of the user.