Disambiguation and authentication of device users

Abstract

Features are described for efficiently and accurately identifying a user of an electronic device with limited user interaction. The features include receiving a mobile device identifier from the mobile device. The features include transmitting the mobile device identifier to a service provider associated with the mobile device. The features include receiving information identifying the user from the service provider. The features include identifying a set of candidates associated with at least a portion of the information. The features include generating a metric for the candidates included in the set of candidates. An individual metric indicates a degree of relatedness between a value for the user for the at least one data field and a value for a candidate for the at least one data field. The features include identifying the user as a specific candidate included in the set of candidates based on the metric corresponding to a threshold.

1 . (canceled) 
     
     
         2 . A computer-implemented method of identification of a user of a mobile device, the method comprising:
 under control of one or more computing devices configured with specific computer-executable instructions,   receiving first information identifying a user of the mobile device from a service associated with the mobile device;   querying, based on a fuzzy matching of at least a portion of the first information, a database which indexes credit header files of a plurality of users for a set of candidate users having the largest quantity of identity data values that matches user information from the credit header files;   determining a degree of difference between the identity data values of candidate users of the set of candidate users and the first information;   determining a degree of relatedness between the identity data values and the user information;   removing users from the set of candidate users based on the degree of difference and based on the degree of relatedness;   for each user included in the set of candidate users, identifying an identity data type associated with different identity data values that distinguish between the candidate users;   receiving an input identity value from the user; and   identifying the user in the set of candidate users based on the received input identity value.   
     
     
         3 . The computer-implemented method of  claim 2  further comprising determining that the identified user qualifies for an offer for a line of credit. 
     
     
         4 . The computer-implemented method of  claim 2  further comprising transmitting instructions to be received at the mobile device to request the input identity value of the identified identity data type from the user. 
     
     
         5 . The computer-implemented method of  claim 2 , wherein the service comprises at least one of an internet service, an application service, a cellular service, or a merchant service. 
     
     
         6 . The computer-implemented method of  claim 2 , wherein generating the metric indicating the degree of relatedness between the identity data values and the user information comprises:
 generating a count of identity data types included in identity data having corresponding identity data types included in the user information; and   for an identity data type having a corresponding identity data type included in the user information, generating a comparison value indicating how closely the identity data value matches a user information value for the corresponding identity data type included in the user information, wherein the metric is based at least in part on the count and the comparison value.   
     
     
         7 . The computer-implemented method of  claim 2 , wherein generating the metric indicating the degree of relatedness between the identity data values and the user information comprises:
 identifying a historical weight for the identity data value based on a difference between a current time and a time when identity data was collected; and   generating a comparison value indicating how closely the identity data value matches a user information value for a corresponding identity data type included in the user information, wherein the comparison value is weighted based at least in part on the historical weight.   
     
     
         8 . The computer-implemented method of  claim 2 , wherein the first information is included in a request for personalized content, and wherein the computer-implemented method further comprises transmitting at least a portion of the user information and at least one of the identity data values of the one candidate user to a personalized content service. 
     
     
         9 . The computer-implemented method of  claim 2  further comprising:
 receiving second information identifying a second user of a second mobile device from a second service associated with the second mobile device; 
 requesting candidate user information from the database using the second information; and 
 in response to receiving no candidate user information results, transmitting instructions to the second mobile device to request input values to identify the second user. 
 
     
     
         10 . The computer-implemented method of  claim 2  further comprising:
 causing, in response to receiving the first information, a consent request to be received at the mobile device; and 
 receiving a consent response in response to causing the consent request, wherein said querying is based in part on the consent response. 
 
     
     
         11 . A system comprising:
 a computer-readable memory storing executable instructions; and   one or more computer processors in communication with the computer-readable memory, wherein the one or more computer processors are configured to execute the executable instructions to at least:
 receive first information identifying a user of a device from a service provider, the first information based on a device identifier associated with the device; 
 query, based on a fuzzy matching of at least a portion of the first information, a database which indexes credit header files of a plurality of users for a set of candidate users having the largest quantity of identity data values that matches user information from the credit header files; 
 determine a degree of difference between the identity data values of candidate users of the set of candidate users and the first information; 
 determine a degree of relatedness between the identity data values and the user information; 
 remove users from the set of candidate users based on the degree of difference and based on the degree of relatedness; 
 for each user included in the set of candidate users, identify an identity data type associated with different identity data values that distinguish between the candidate users; 
 receive an input identity value from the user; and 
 identify the user in the set of candidate users based on the received input identity value. 
   
     
     
         12 . The system of  claim 11 , wherein the one or more computer processors are further configured to execute the executable instructions to determine that the identified user qualifies for an offer for a line of credit. 
     
     
         13 . The system of  claim 11 , wherein the one or more computer processors are further configured to execute the executable instructions to transmit instructions to be received at the mobile device to request the input identity value of the identified identity data type from the user. 
     
     
         14 . The system of  claim 11 , wherein the one or more computer processors are further configured to execute the executable instructions to:
 identify the specific candidate and a second candidate having metrics corresponding to the threshold;   identify a differentiation data field, wherein a value for the differentiation data field for the specific candidate is different from a value for the differentiation data field for the second candidate;   receive input from the device for the differentiation data field; and determine the input corresponds to the value of the differentiation data field for the specific candidate.   
     
     
         15 . The system of  claim 11 , wherein the one or more computer processors are further configured to execute the executable instructions to transmit at least a portion of the device identifier and at least one of the values of the specific candidate to a personalized content service. 
     
     
         16 . The system of  claim 11 , wherein identifying the set of candidates comprises querying a database storing information regarding a plurality of users, wherein the set of candidates include one or more users having the largest quantity of identity data values matching the first information. 
     
     
         17 . Non-transitory, computer-readable storage media storing computer-executable instructions that, when executed by a computer system that comprises one or more hardware processors, configure the computer system to perform operations comprising:
 receiving first information identifying a user of the mobile device from a service associated with the mobile device;   querying, based on a fuzzy matching of at least a portion of the first information, a database which indexes credit header files of a plurality of users for a set of candidate users having the largest quantity of identity data values that matches user information from the credit header files;   determining a degree of difference between the identity data values of candidate users of the set of candidate users and the first information;   determining a degree of relatedness between the identity data values and the user information;   removing users from the set of candidate users based on the degree of difference and based on the degree of relatedness;   for each user included in the set of candidate users, identifying an identity data type associated with different identity data values that distinguish between the candidate users;   receiving an input identity value from the user; and   identifying the user in the set of candidate users based on the received input identity value.   
     
     
         18 . The non-transitory, computer-readable storage media of  claim 17 , wherein the computer system is further configured to determine that the identified user qualifies for an offer for a line of credit. 
     
     
         19 . The non-transitory, computer-readable storage media of  claim 17 , wherein the computer system is further configured to transmit instructions to be received at the mobile device to request the input identity value of the identified identity data type from the user. 
     
     
         20 . The non-transitory, computer-readable storage media of  claim 17 , wherein the computer system is further configured to generate an individual metric for each of the candidates included in the set of candidates, wherein the individual metric indicates the degree of relatedness. 
     
     
         21 . The non-transitory, computer-readable storage media of  claim 17 , wherein the computer system is further configured to:
 determine the set of candidates includes no candidate users;   in response to receiving no candidate user information results, cause instructions to be received at the mobile device to request input values;   generate a custom candidate user based on received input values; and   add the custom candidate user to the set of candidates.