SYSTEMS AND METHODS FOR DETECTING FRAUD IN RETAIL RETURN TRANSACTIONS
This disclosure describes systems, methods, and computer-readable media related to detecting fraud in retail return transactions. In some embodiments, one or more parameters associated with a retail transaction may be received by at least one server comprising one or more computer processors. The server may evaluate the one or more risk factor conditions associated with the one or more parameters. The risk factor conditions may be indicative of a fraudulent return transaction. The server may generate one or more risk scores associated with the retail transaction based at least in part on the evaluating of the one or more risk factor conditions.
1 . A computer-implemented method comprising:
receiving, by at least one server comprising one or more computer processors, one or more parameters associated with a retail transaction;
evaluating, by the at least one server, one or more risk factor conditions associated with the one or more parameters, wherein the risk factor conditions are indicative of a fraudulent return transaction; and
generating, by the at least one server, one or more risk scores associated with the retail transaction based at least in part on the evaluating of the one or more risk factor conditions.
2 . The computer-implemented method of claim 1 , further comprising:
generating, by the at least one server, a recommended course of action based at least in part on the one or more generated risk scores; and
transmitting, by the at least one server, the recommended course of action to a merchant device.
3 . The computer-implemented method of claim 2 , wherein the recommended course of action comprises transmitting a notification to the merchant device to prevent a completion of the retail transaction based at least in part on one or more risk scores.
4 . The computer-implemented method of claim 1 , wherein generating the one or more risk scores associated with the retail transaction further comprises:
retrieving, by the at least one server, data associated with a customer initiating the retail transaction; and
generating, by the at least one server, the one or more risk scores based at least in part on the retrieved data associated with the customer.
5 . The computer-implemented method of claim 4 , wherein the data associated with the customer comprises at least one of historical transaction data associated with the customer, previous payment data associated with the customer, an identifier associated with the customer, or purchase history of the customer.
6 . The computer-implemented method of claim 4 , further comprising:
retrieving, by the at least one server, data associated with the customer from at least one of one or more serve providers or one or more government databases.
7 . The computer-implemented method of claim 4 , further comprising:
analyzing, by the at least one server, the data associated with the customer and the one or more parameters associated with the retail transaction, wherein analyzing the data comprises pattern matching to identify similarities between data associated with the customer and the one or more parameters associated with the retail transaction.
8 . A computer-readable medium storing computer-executable instructions which, when executed by a processor, cause the processor to perform operations comprising:
receiving one or more parameters associated with a retail transaction;
evaluating one or more risk factor conditions associated with the one or more parameters, wherein the risk factor conditions are indicative of a fraudulent return transaction; and
generating one or more risk scores associated with the retail transaction based at least in part on the evaluating of the one or more risk factor conditions.
9 . The computer-readable medium of claim 8 , wherein the operations further comprise:
generating a recommended course of action based at least in part on the one or more generated risk scores; and
transmitting the recommended course of action to a merchant device.
10 . The computer-readable medium of claim 9 , wherein the recommended course of action comprises transmitting a notification to the merchant device to prevent a completion of the retail transaction based at least in part on one or more risk scores.
11 . The computer-readable medium of claim 8 , wherein generating the one or more risk scores associated with the retail transaction further comprises:
retrieving data associated with a customer initiating the retail transaction; and
generating the one or more risk scores based at least in part on the retrieved data associated with the customer.
12 . The computer-readable medium of claim 11 , wherein the data associated with the customer comprises at least one of historical transaction data associated with the customer, previous payment data associated with the customer, an identifier associated with the customer, or purchase history of the customer.
13 . The computer-readable medium of claim 11 , wherein the operations further comprise:
retrieving data associated with the customer from at least one of one or more serve providers or one or more government databases.
14 . The computer-readable medium of claim 11 , wherein the operations further comprise:
analyzing the data associated with the customer and the one or more parameters associated with the retail transaction, wherein analyzing the data comprises pattern matching to identify similarities between data associated with the customer and the one or more parameters associated with the retail transaction.
15 . A system comprising:
at least one memory storing computer-executable instructions; and
at least one processor, wherein the at least one processor is configured to access the at least one memory and to execute the computer-executable instructions to:
receive one or more parameters associated with a retail transaction;
evaluate one or more risk factor conditions associated with the one or more parameters, wherein the risk factor conditions are indicative of a fraudulent return transaction; and
generate one or more risk scores associated with the retail transaction based at least in part on the evaluating of the one or more risk factor conditions.
16 . The system of claim 15 , wherein the at least one processor is further configured to execute the computer-executable instructions to:
generate a recommended course of action based at least in part on the one or more generated risk scores; and
transmit the recommended course of action to a merchant device.
17 . The system of claim 16 , wherein the recommended course of action comprises transmission of a notification to the merchant device to prevent a completion of the retail transaction based at least in part on one or more risk scores.
18 . The system of claim 15 , wherein to generate the one or more risk scores associated with the retail transaction, the at least one processor is further configured to execute the computer-executable instructions to:
retrieve data associated with a customer initiating the retail transaction; and
generate the one or more risk scores based at least in part on the retrieved data associated with the customer.
19 . The system of claim 18 , wherein the data associated with the customer comprises at least one of historical transaction data associated with the customer, previous payment data associated with the customer, an identifier associated with the customer, or purchase history of the customer.
20 . The system of claim 18 , wherein the at least one processor is further configured to execute the computer-executable instructions to:
retrieve data associated with the customer from at least one of one or more serve providers or one or more government databases.
21 . The system of claim 18 , wherein the at least one processor is further configured to execute the computer-executable instructions to:
analyze the data associated with the customer and the one or more parameters associated with the retail transaction, wherein analyzing the data comprises pattern matching to identify similarities between data associated with the customer and the one or more parameters associated with the retail transaction.