Systems and methods for computing and applying user value scores during transaction authorization

Abstract

Systems and methods are disclosed for generating a consumer value score. One method includes: receiving a user identifier associated with a first user; receiving a designation of a period of time for analysis; receiving transaction data associated with the user identifier, the transaction data including a record of one or more transactions, wherein each transaction is associated with the user identifier, a merchant, a transaction time, and a purchase amount; identifying, of the received transaction data, a set of transactions conducted during the received period of time, based on the transaction time of each transaction; identifying, of the set of transactions, purchase data related to a given merchant; determining, of the purchase data related to a given merchant, a value of a purchase amount; and generating a consumer value score based on the determined value of the purchase amount.

1 - 20 . (canceled) 
     
     
         21 . A computer-implemented method of generating a user value score for authorizing a transaction, the method comprising:
 receiving an authorization request for at least one transaction from at least one device associated with a user;   retrieving identifying data associated with the transaction based, at least in part, on the authorization request, wherein the identifying data include personally identifiable information (PII) of the user, device-specific information for the at least one device, and/or internet protocol (IP) address;   searching at least one database for a fraud detection profile of the user based, at least in part, on the identifying data associated with the transaction, wherein the fraud detection profile includes past activity information and/or past behavior patterns of the user;   calculating the user value score for the user based, at least in part, on transaction data associated with the at least one transaction and the fraud detection profile, wherein the transaction data includes current activity information and/or current behavior patterns of the user; and   comparing the user value score to a pre-determined score threshold to determine authenticity of the at least one transaction to authorize the transaction.   
     
     
         22 . The computer-implemented method of  claim 21 , further comprising:
 monitoring an amount for one or more transactions associated with the user and a plurality of service providers, wherein the amount indicates an average amount for a pre-determined time period or an aggregate amount for the pre-determined time period; and   generating the user value score based, at least in part, on the amount for the one or more transactions, wherein a higher user value score is generated for the at least one transaction with higher amount, and wherein different consumer value scores are generated for each of the one or more transactions with the plurality of service providers.   
     
     
         23 . The computer-implemented method of  claim 22 , further comprising:
 determining a frequency for the one or more transactions associated with the user during the pre-determined time period; and   generating the user value score based, at least in part, on the frequency of the one or more transactions, wherein a higher user value score is generated for the user with a higher number of transactions during the pre-determined time period.   
     
     
         24 . The computer-implemented method of  claim 21 , further comprising:
 determining a category for one or more items purchased during the at least one transaction based, at least in part, on processing the transaction data associated with the user; and   generating the user value score based, at least in part, on the category of the one or more items purchased by the user, wherein a higher user value score is generated for the user with at least one item categorized within the category recommended by a service provider.   
     
     
         25 . The computer-implemented method of  claim 21 , further comprising:
 determining irregularities in the user's behavior based, at least in part, on processing the transaction data associated with the user, wherein the transaction data includes spending pattern of the user, location data associated with the transaction, temporal data associated with the transaction, and/or type of payment vehicles utilized during the transaction; and   generating the user value score based, at least in part, on the irregular behavior of the user, wherein a lower user value score is generated for the user with the irregular behavior.   
     
     
         26 . The computer-implemented method of  claim 21 , further comprising:
 calibrating the user value score based, at least in part, on average amount per transaction by a pre-determined group of users during a pre-determined time period,   wherein the average amount per transaction by the user is compared to the average amount per transaction by other users, and wherein a higher user value score is generated upon determining the average amount per transaction by the user is greater than average amount per transaction by the other users.   
     
     
         27 . The computer-implemented method of  claim 21 , further comprising:
 isolating the transaction data associated with the user for a specific time period based, at least in part, on a request from at least one service provider;   processing the isolated transaction data to determine spending pattern of the user; and   monitoring, replacing, or stocking an inventory based, at least in part, on the spending pattern of the user.   
     
     
         28 . The computer-implemented method of  claim 21 , further comprising:
 generating a profile for the user based, at least in part, on the transaction data associated with the user,   wherein the profile includes a unique identifier hash recognizing the profile of the user, primary account numbers associated with the user, identifiers of payment vehicles associated with the user, data analysis report on spending patterns of the user, and/or fraudulent activities report on the payment vehicles associated with the user.   
     
     
         29 . The computer-implemented method of  claim 28 , wherein the identifiers of the payment vehicles are tokenized and encrypted. 
     
     
         30 . The computer-implemented method of  claim 28 , further comprising:
 generating, via a user interface of a device associated with the user, a presentation of a user behavior report, the data analysis report, and/or fraudulent activities reports for the user,   wherein the user behavior report, the data analysis report, and/or the fraudulent activities reports are presented in a portable document format.   
     
     
         31 . A decentralized computer system for generating a user value score for authorizing a transaction, the system comprising:
 a data storage device storing instructions for generating a consumer value score; and   a processor configured to execute the instructions to perform a method including:   receiving an authorization request for at least one transaction from at least one device associated with a user;
 retrieving identifying data associated with the transaction based, at least in part, on the authorization request, wherein the identifying data include personally identifiable information (PII) of the user, device-specific information for the at least one device, and/or internet protocol (IP) address; 
 searching at least one database for a fraud detection profile of the user based, at least in part, on the identifying data associated with the transaction, wherein the fraud detection profile includes past activity information and/or past behavior patterns of the user; 
 calculating the user value score for the user based, at least in part, on transaction data associated with the at least one transaction and the fraud detection profile, wherein the transaction data includes current activity information and/or current behavior patterns of the user; and 
 comparing the user value score to a pre-determined score threshold to determine authenticity of the at least one transaction to authorize the transaction. 
   
     
     
         32 . The system of  claim 31 , further comprising:
 monitoring an amount for one or more transactions associated with the user and a plurality of service providers, wherein the amount indicates an average amount for a pre-determined time period or an aggregate amount for the pre-determined time period; and   generating the user value score based, at least in part, on the amount for the one or more transactions, wherein a higher user value score is generated for the at least one transaction with higher amount, and wherein different consumer value scores are generated for each of the one or more transactions with the plurality of service providers.   
     
     
         33 . The system of  claim 32 , further comprising:
 determining a frequency for the one or more transactions associated with the user during the pre-determined time period; and   generating the user value score based, at least in part, on the frequency of the one or more transactions, wherein a higher user value score is generated for the user with a higher number of transactions during the pre-determined time period.   
     
     
         34 . The system of  claim 31 , further comprising:
 determining a category for one or more items purchased during the at least one transaction based, at least in part, on processing the transaction data associated with the user; and   generating the user value score based, at least in part, on the category of the one or more items purchased by the user, wherein a higher user value score is generated for the user with at least one item categorized within the category recommended by a service provider.   
     
     
         35 . The system of  claim 31 , further comprising:
 determining irregularities in the user's behavior based, at least in part, on processing the transaction data associated with the user, wherein the transaction data includes spending pattern of the user, location data associated with the transaction, temporal data associated with the transaction, and/or type of payment vehicles utilized during the transaction; and   generating the user value score based, at least in part, on the irregular behavior of the user, wherein a lower user value score is generated for the user with the irregular behavior.   
     
     
         36 . The system of  claim 31 , further comprising:
 calibrating the user value score based, at least in part, on average amount per transaction by a pre-determined group of users during a pre-determined time period,   wherein the average amount per transaction by the user is compared to the average amount per transaction by other users, and wherein a higher user value score is generated upon determining the average amount per transaction by the user is greater than average amount per transaction by the other users.   
     
     
         37 . The system of  claim 31 , further comprising:
 isolating the transaction data associated with the user for a specific time period based, at least in part, on a request from at least one service provider;   processing the isolated transaction data to determine spending pattern of the user; and   monitoring, replacing, or stocking an inventory based, at least in part, on the spending pattern of the user.   
     
     
         38 . A non-transitory machine-readable medium storing instructions that, when executed by a server, cause the server to perform a method for generating a user value score for authorizing a transaction, the method including:
 receiving an authorization request for at least one transaction from at least one device associated with a user;   retrieving identifying data associated with the transaction based, at least in part, on the authorization request, wherein the identifying data include personally identifiable information (PII) of the user, device-specific information for the at least one device, and/or internet protocol (IP) address;   searching at least one database for a fraud detection profile of the user based, at least in part, on the identifying data associated with the transaction, wherein the fraud detection profile includes past activity information and/or past behavior patterns of the user;   calculating the user value score for the user based, at least in part, on transaction data associated with the at least one transaction and the fraud detection profile, wherein the transaction data includes current activity information and/or current behavior patterns of the user; and   comparing the user value score to a pre-determined score threshold to determine authenticity of the at least one transaction to authorize the transaction.   
     
     
         39 . The machine readable medium of  claim 38 , further comprising:
 monitoring an amount for one or more transactions associated with the user and a plurality of service providers, wherein the amount indicates an average amount for a pre-determined time period or an aggregate amount for the pre-determined time period; and   generating the user value score based, at least in part, on the amount for the one or more transactions, wherein a higher user value score is generated for the at least one transaction with higher amount, and wherein different consumer value scores are generated for each of the one or more transactions with the plurality of service providers.   
     
     
         40 . The machine readable medium of  claim 39 , further comprising:
 determining a frequency for the one or more transactions associated with the user during the pre-determined time period; and   generating the user value score based, at least in part, on the frequency of the one or more transactions, wherein a higher user value score is generated for the user with a higher number of transactions during the pre-determined time period.