Electronic Fraud Refund Scoring for Chargeback Loss Reduction

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Solution Overview

Problem

Existing systems provide proactive refunds for fraudulent transactions that may not be optimal, leading to unnecessary losses and inefficiencies in fraud chargeback protection services, as only about 50% of reported fraudulent transactions result in chargebacks, and 10-20% of proactive refunds do not prevent subsequent chargebacks.

Innovation Solution

A system and method for optimizing refunds by determining probabilities of chargebacks using a chargeback analysis profile, generating a proactive refund based on these probabilities, and adjusting thresholds to minimize ineffective refunds.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If proactive refunds are provided for all reported fraudulent transactions, then chargebacks may be prevented for reported fraud, but unnecessary refunds are issued for transactions that would not result in chargebacks

Engineering Contradiction:

Improvechargeback prevention effectivenessVSAvoidunnecessary refund losses

Core Design Contradiction:

ReliabilityVSLoss of energy

Solution Approach 1:

The system changes the parameter of refund decision-making from a binary automatic refund approach to a probability-based selective refund approach. By calculating chargeback probability scores and comparing them against configurable thresholds, the system identifies and refunds only those transactions with high likelihood of resulting in chargebacks, thereby preventing unnecessary refunds while maintaining effective chargeback prevention.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The system implements feedback mechanisms by analyzing actual chargeback outcomes from previous transactions and using this information to refine chargeback probability predictions. The system continuously learns from historical data, adjusting its probability calculations to improve accuracy over time, which helps distinguish transactions likely to result in chargebacks from those that won't.

Inventive Principle:

Principle #23Feedback

2Productivity

If automatic refund is provided for all reported fraudulent transactions, then possible chargebacks may be prevented, but the market for fraud chargeback protection service is narrowed

Engineering Contradiction:

Improvechargeback protection service effectivenessVSAvoidservice market adaptability

Core Design Contradiction:

ProductivityVSAdaptability or versatility

Solution Approach 1:

The system introduces dynamic configurability to the refund service, allowing merchants to adjust chargeback probability thresholds based on their specific risk tolerance and business needs. This dynamic approach enables the service to adapt to different merchant preferences and market conditions, maintaining versatility while preserving effectiveness through customizable parameters rather than a fixed automatic refund policy.

Inventive Principle:

Principle #15Dynamics

3Reliability

If proactive refunds are provided for reported fraudulent transactions, then chargebacks may be prevented, but 10-20% of refunds do not prevent following chargebacks

Engineering Contradiction:

Improvechargeback prevention rateVSAvoidineffective refund rate

Core Design Contradiction:

ReliabilityVSLoss of energy

Solution Approach 1:

The system replaces the mechanical automatic refund system with an intelligent probability-based decision system. Instead of mechanically refunding all reported fraudulent transactions, the system uses machine learning models and analytical algorithms to predict chargeback likelihood, substituting automated calculation and selection logic for blanket automatic refunds, thereby reducing ineffective refunds while maintaining prevention effectiveness.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS12406262B2Systems and methods for optimizing electronic refund transactions for detected fraudulent transactions

Publication Date: 2025.09.02 WORLDPAY LLC

AI summary

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.