Chargeback Fraud Detection via Merchant Name Mapping
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Solution Overview
Problem
Friendly fraud in online transactions, where users initiate chargebacks due to unfamiliar merchant names on their statements, leads to costly processing issues for entities involved in transaction processing.
Innovation Solution
A system and method that processes chargeback requests by determining potential familiar merchant names from unfamiliar ones, using browser history data and database searches, and communicates recommendations to users for confirmation, thereby preventing fraudulent chargebacks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the merchant name listed on the user's statement is the legal name or payment gateway name, then the transaction can be processed, but the user may not recognize the merchant and initiate a chargeback
Solution Approach 1:
The system introduces an intermediary process that maps unfamiliar merchant names (legal names or payment gateway names) to familiar merchant names that users recognize. This intermediary mapping layer resolves the conflict between using accurate legal/payment gateway names for transaction processing and using recognizable names for user understanding, thereby preventing friendly fraud chargebacks.
Solution Approach 2:
The system implements feedback by analyzing user interactions and chargeback patterns to continuously improve the merchant name mapping. When users initiate chargebacks or provide feedback about unrecognized merchants, the system learns and refines its mapping algorithms, making the connection between unfamiliar and familiar merchant names more accurate over time.
2Reliability
If chargeback requests are processed without verification, then processing speed is maintained, but fraudulent chargebacks are not prevented
Solution Approach 1:
The system performs preliminary actions by proactively identifying and flagging potential friendly fraud chargebacks before they are fully processed. By analyzing merchant name recognition patterns and user behavior in advance, the system can prevent fraudulent chargebacks from completing, reducing both fraud loss and overall processing time by avoiding unnecessary full chargeback investigations.
3Reliability
If the system scans browser history to verify merchant visits, then accurate fraud detection is achieved, but system complexity increases
Solution Approach 1:
The system utilizes self-service by leveraging data that users have already provided voluntarily (browser history, shopping cart information) without requiring additional active participation. This approach achieves accurate fraud detection by using existing user-generated data, avoiding the need for complex additional verification systems while maintaining high reliability.
Data Source
AI summary
A method for processing a chargeback request associated with at least one online transaction associated with a user includes: receiving a chargeback message associated with the at least one online transaction; based at least partially on the unfamiliar merchant name in the chargeback message, determining at least one potential familiar merchant name associated with the at least one unfamiliar merchant name; scanning a browser history of the user including browser data; determining whether the user visited a website associated with the at least one potential familiar merchant name; and generating and communicating a recommendation message including the at least one potential familiar merchant name. A system for processing a chargeback request associated with at least one online transaction associated with a user is also disclosed.