Systems and methods for a context-driven electronic transactions fraud detection

Abstract

Systems and methods are disclosed for establishing a multi-dimensional fraud detection system and payment analysis. One method includes: receiving transaction history of a user, the transaction history including a first payment vehicle and a second payment vehicle; determining, of the received transaction history, one or more instances of switching from one the first payment vehicle to the second payment vehicle; and determining a user-specific abandonment score for the user, based on the determined instances of switching from the first payment vehicle to the second payment vehicle.

1 - 20 . (canceled) 
     
     
         21 . A computer-implemented method for calculating a user-specific abandonment score to authorize a transaction, the method comprising:
 receiving an authorization request for at least one transaction from a device associated with a user;   retrieving user information, device information, and account information associated with the at least one transaction;   processing the retrieved information to determine transaction history associated with the user;   identifying, of the determined transaction history, one or more authorization requests associated with a first payment vehicle of the user;   determining, of the identified authorization requests, transaction data associated with a second payment vehicle of the user, wherein the transaction data includes a second authorization request;   calculating the user-specific abandonment score based, at least in part, on the determined transaction data associated with the second payment vehicle, wherein the determined transaction data includes switching pattern of payment vehicles by the user; and   determining on authorization of the at least one transaction based, at least in part, on the user-specific abandonment score.   
     
     
         22 . The computer-implemented method of  claim 21 , wherein a low user-specific abandonment score is assigned to the user with a higher switching pattern of the payment vehicles during the at least one transaction. 
     
     
         23 . The computer-implemented method of  claim 21 , further comprising:
 calculating a fraud risk score for the at least one transaction based, at least in part, on the device utilized during the at least one transaction, one or more payment vehicles utilized during the at least one transaction, total sum of the at least one transaction, one or more service providers associated with the at least one transaction, temporal information of the at least one transaction, and/or location information of the at least one transaction.   
     
     
         24 . The computer-implemented method of  claim 23 , wherein the fraud risk score is higher for the one or more payment vehicles with shorter transaction history, lower interest rates, and/or direct access to the one or more service providers. 
     
     
         25 . The computer-implemented method of  claim 24 , further comprising:
 denying the authorization of the at least one transaction with a higher fraud risk score based, at least in part, on low user-specific abandonment score,   wherein the at least one transaction is denied at a higher frequency upon determining the user switches the payment vehicles until a risk of fraud for the at least one transaction is reduced.   
     
     
         26 . The computer-implemented method of  claim 24 , further comprising:
 calculating a risk tolerance score for the user based, at least in part, on the transaction history associated with the user and/or preference information of the one or more service providers,   wherein the risk tolerance score indicates a pre-determined risk threshold for the one or more service providers, and wherein a low risk tolerance score is assigned to the user with at least one incidence of fraudulent activity in the transaction history.   
     
     
         27 . The computer-implemented method of  claim 26 , further comprising:
 comparing the user-specific abandonment score with the fraud risk score and the risk tolerance score; and   determining on the authorization of the at least one transaction based, at least in part, on the comparison, wherein the at least one transaction is authorized upon determining the abandonment score is higher than the fraud risk score and the risk tolerance score.   
     
     
         28 . The computer-implemented method of  claim 21 , further comprising:
 searching for a fraud analysis profile of the user in a database based, at least in part, on the authorization request; and   retrieving the fraud analysis profile of the user from the database, wherein the fraud analysis profile is generated within a specific time period.   
     
     
         29 . The computer-implemented method of  claim 28 , further comprising:
 comparing the transaction data associated with the second payment vehicle and the transaction history associated with the user stored in the fraud analysis profile,   wherein a high fraud risk score is assigned to the user upon detecting irregularities between the transaction data associated with the second payment vehicle and the transaction history associated with the user, or   wherein a low fraud risk score is assigned to the user upon detecting consistency in the switching pattern of the payment vehicles.   
     
     
         30 . The computer-implemented method of  claim 21 , further comprising:
 searching for a fraud analysis profile of the user in a database based, at least in part, on the authorization request;   determining an absence of the fraud analysis profile of the user in the database;   generating a unique hash and a request for the fraud analysis profile;   extracting, transforming, and loading transaction data associated with the at least one transaction;   tokenizing account identifying information associated with the transaction data;   transmitting the transaction data with the tokenized data for analysis to generate the fraud analysis profile; and   de-tokenizing the generated fraud analysis profile for storing in the database.   
     
     
         31 . A decentralized computer system for calculating a user-specific abandonment score to authorize a transaction, the system comprising:
 a data storage device storing instructions for establishing a multi-dimensional fraud detection system and payment analysis; and   a processor configured to execute the instructions to perform a method including:
 receiving an authorization request for at least one transaction from a device associated with a user; 
 retrieving user information, device information, and account information associated with the at least one transaction; 
 processing the retrieved information to determine transaction history associated with the user; 
 identifying, of the determined transaction history, one or more authorization requests associated with a first payment vehicle of the user; 
 determining, of the identified authorization requests, transaction data associated with a second payment vehicle of the user, wherein the transaction data includes a second authorization request; 
 calculating the user-specific abandonment score based, at least in part, on the determined transaction data associated with the second payment vehicle, wherein the determined transaction data includes switching pattern of payment vehicles by the user; and 
 determining on authorization of the at least one transaction based, at least in part, on the user-specific abandonment score. 
   
     
     
         32 . The system of  claim 31 , wherein a low user-specific abandonment score is assigned to the user with a higher switching pattern of the payment vehicles during the at least one transaction. 
     
     
         33 . The system of  claim 31 , wherein the processor is further configured for:
 calculating a fraud risk score for the at least one transaction based, at least in part, on the device utilized during the at least one transaction, one or more payment vehicles utilized during the at least one transaction, total sum of the at least one transaction, one or more service providers associated with the at least one transaction, temporal information of the at least one transaction, and/or location information of the at least one transaction.   
     
     
         34 . The system of  claim 33 , wherein the fraud risk score is higher for the one or more payment vehicles with shorter transaction history, lower interest rates, and/or direct access to the one or more service providers. 
     
     
         35 . The system of  claim 34 , wherein the processor is further configured for:
 denying the authorization of the at least one transaction with a higher fraud risk score based, at least in part, on low user-specific abandonment score,   wherein the at least one transaction is denied at a higher frequency upon determining the user switches the payment vehicles until a risk of fraud for the at least one transaction is reduced.   
     
     
         36 . The system of  claim 34 , wherein the processor is further configured for:
 calculating a risk tolerance score for the user based, at least in part, on the transaction history associated with the user and/or preference information of the one or more service providers,   wherein the risk tolerance score indicates a pre-determined risk threshold for the one or more service providers, and wherein a low risk tolerance score is assigned to the user with at least one incidence of fraudulent activity in the transaction history.   
     
     
         37 . The system of  claim 36 , wherein the processor is further configured for:
 comparing the user-specific abandonment score with the fraud risk score and the risk tolerance score; and   determining on the authorization of the at least one transaction based, at least in part, on the comparison, wherein the at least one transaction is authorized upon determining the abandonment score is higher than the fraud risk score and the risk tolerance score.   
     
     
         38 . A non-transitory machine-readable medium storing instructions that, when executed by a server, cause the server to perform a method for calculating a user-specific abandonment score to authorize a transaction, the method comprising:
 receiving an authorization request for at least one transaction from a device associated with a user;   retrieving user information, device information, and account information associated with the at least one transaction;   processing the retrieved information to determine transaction history associated with the user;   identifying, of the determined transaction history, one or more authorization requests associated with a first payment vehicle of the user;   determining, of the identified authorization requests, transaction data associated with a second payment vehicle of the user, wherein the transaction data includes a second authorization request;   calculating the user-specific abandonment score based, at least in part, on the determined transaction data associated with the second payment vehicle, wherein the determined transaction data includes switching pattern of payment vehicles by the user; and   determining on authorization of the at least one transaction based, at least in part, on the user-specific abandonment score.   
     
     
         39 . The non-transitory machine-readable medium of  claim 38 , wherein a low user-specific abandonment score is assigned to the user with a higher switching pattern of the payment vehicles during the at least one transaction. 
     
     
         40 . The non-transitory machine-readable medium of  claim 38 , wherein the method further comprises:
 calculating a fraud risk score for the at least one transaction based, at least in part, on the device utilized during the at least one transaction, one or more payment vehicles utilized during the at least one transaction, total sum of the at least one transaction, one or more service providers associated with the at least one transaction, temporal information of the at least one transaction, and/or location information of the at least one transaction.