Systems and methods for optimizing electronic refund transactions for detected fraudulent transactions

Patent metadata

Field	Value
Publication number	US-2025384444-A1
Application number	US-202519303758-A
Country	US
Kind code	A1
Filing date	Aug 19, 2025
Priority date	Mar 18, 2020
Publication date	Dec 18, 2025
Grant date	—

Abstract

A method for optimizing refunds for suspected or detected fraudulent transactions includes receiving a chargeback analysis request for a potential chargeback transaction from a merchant or a payment processor extracting identifying information of transactions associated with the chargeback transaction from the chargeback analysis request, searching for a chargeback analysis profile in a profile database, determining whether the chargeback analysis profile exists in the profile database, upon determining that the chargeback analysis profile does not exist in the profile database, obtaining a new fraud analysis profile, determining, based on the chargeback analysis profile, a first probability that the potential chargeback transaction will result in a chargeback, determining, based on the chargeback analysis profile, a second probability that the potential chargeback transaction will result in a chargeback after a proactive electronic refund transaction, and generating a proactive electronic refund transaction based on the first probability and the second probability.

First claim

What is claimed is:

1 . A method for optimizing electronic refund transactions for suspect or detected fraudulent transactions, the method comprising:
receiving, by a computer processor, a chargeback analysis request for a potential chargeback transaction including identifying information associated with one or more transactions; querying, by the computer processor, historical transaction data associated with the identifying information associated with the one or more transactions from at least one of a plurality of issuer chargeback databases; retrieving, by the computer processor, a chargeback analysis profile, wherein the chargeback analysis profile includes a unique profile identifier and aggregated historical transaction data from the plurality of issuer chargeback databases; determining, by the computer processor based on the chargeback analysis profile, a first probability that the potential chargeback transaction will result in a chargeback; determining, by the computer processor based on the chargeback analysis profile, a second probability that the potential chargeback transaction will result in a chargeback following a refund of the potential chargeback transaction; comparing, by the computer processor, the first probability to a first threshold likelihood and the second probability to a second threshold likelihood, wherein the first threshold likelihood is a minimum threshold and the second threshold likelihood is a maximum threshold; and generating, by the computer processor, an electronic refund transaction based on the first probability being greater than the first threshold likelihood and the second probability being less than second threshold likelihood.

2 . The method of claim 1 , further comprising:
receiving, by the computer processor, a second chargeback analysis request for a second potential chargeback transaction including second identifying information associated with a second one or more transactions; querying, by the computer processor, second historical transaction data associated with the second identifying information associated with the second one or more transactions from at least one of a plurality of issuer chargeback databases; and determining, by the computer processor, a second chargeback analysis profile does not exist for the second identifying information and the second one or more transactions.

3 . The method of claim 2 , further comprising:
generating, by the computer processor, a chargeback analysis profile request, wherein the chargeback analysis profile request includes the second identifying information; tokenizing, by the computer processor, the second identifying information of the chargeback analysis request; and sending, by the computer processor, the chargeback analysis profile request to a cloud platform for analysis.

4 . The method of claim 3 , further comprising:
receiving, by the computer processor, a second chargeback analysis profile from the cloud platform; detokenizing, by the computer processor, the second identifying information; determining, by the computer processor based on the second chargeback analysis profile, a first probability that the second potential chargeback transaction will result in a chargeback; determining, by the computer processor based on the chargeback analysis profile, a second probability that the potential chargeback transaction will result in a chargeback following a refund of the second potential chargeback transaction; and comparing, by the computer processor for the second potential chargeback transaction, the first probability to a first threshold likelihood and the second probability to a second threshold likelihood, wherein the first threshold likelihood is a minimum threshold and the second threshold likelihood is a maximum threshold.

5 . The method of claim 4 , further comprising:
generating, by the computer processor, a second electronic refund transaction based on the first probability being greater than the first threshold likelihood and the second probability is less than second threshold likelihood for the second potential chargeback transaction.

6 . The method of claim 4 , further comprising:
determining, by the computer processor based on the comparing for the second potential chargeback transaction, a chargeback is likely to occur and a second electronic refund transaction should not be generated.

7 . The method of claim 4 , further comprising:
generating, by the computer processor, a chargeback analysis report, wherein the chargeback analysis report includes information related to at least one of: the chargeback analysis profile or the second chargeback analysis profile.

8 . A system for optimizing refunds for suspected or detected fraudulent transactions, the system comprising:
a data storage device storing instructions for fraud chargeback automatic refunds in an electronic storage medium; and a processor configured to execute the instructions to perform operations comprising: receiving, by a computer processor, a chargeback analysis request for a potential chargeback transaction including identifying information associated with one or more transactions; querying, by the computer processor, historical transaction data associated with the identifying information associated with the one or more transactions from at least one of a plurality of issuer chargeback databases; retrieving, by the computer processor, a chargeback analysis profile, wherein the chargeback analysis profile includes a unique profile identifier and aggregated historical transaction data from the plurality of issuer chargeback databases; determining, by the computer processor based on the chargeback analysis profile, a first probability that the potential chargeback transaction will result in a chargeback; determining, by the computer processor based on the chargeback analysis profile, a second probability that the potential chargeback transaction will result in a chargeback following a refund of the potential chargeback transaction; comparing, by the computer processor, the first probability to a first threshold likelihood and the second probability to a second threshold likelihood, wherein the first threshold likelihood is a minimum threshold and the second threshold likelihood is a maximum threshold; and generating, by the computer processor, an electronic refund transaction based on the first probability being greater than the first threshold likelihood and the second probability is less than second threshold likelihood.

9 . The system of claim 8 , the instructions further comprising:
receiving, by the computer processor, a second chargeback analysis request for a second potential chargeback transaction including second identifying information associated with a second one or more transactions; querying, by the computer processor, second historical transaction data associated with the second identifying information associated with the second one or more transactions from at least one of a plurality of issuer chargeback databases; and determining, by the computer processor, a second chargeback analysis profile does not exist for the second identifying information and the second one or more transactions.

10 . The system of claim 9 , the instructions further comprising:
generating, by the computer processor, a chargeback analysis profile request, wherein the chargeback analysis profile request include the second identifying information; tokenizing, by the computer processor, the second identifying information of the chargeback analysis request; and sending, by the computer processor, the chargeback analysis profile request to a cloud platform for analysis.

Assignees

• Worldpay Llc

Inventors

• Burmistrov Dmitriy
• Kettler Dennis A
• Hong Tao

Classifications

• G06Q20/407 Primary

  Cancellation of a transaction · CPC title

• G06Q30/01

  Customer relationship services · CPC title

• G06Q30/0185

  Product, service or business identity fraud · CPC title

• G06Q20/4016 Primary

  involving fraud or risk level assessment in transaction processing · CPC title