AI Agent Dispute Resolution for Consistent Transaction Decisions
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Solution Overview
Problem
Financial transaction disputes are resource-intensive and prone to human error due to inconsistent application and interpretation of complex payment network rules and regulations, leading to inconsistent resolutions.
Innovation Solution
A dispute resolution system utilizing artificial intelligence models trained on historical dispute resolutions, payment network rules, government regulations, and merchant policies to automate and standardize the dispute resolution process, reducing human intervention and improving consistency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If human personnel are used to resolve disputes, then complex rules and regulations can be interpreted and applied with flexibility, but the process becomes resource-intensive and prone to human error and inconsistencies
Solution Approach 1:
The system enables self-service dispute resolution by automatically matching disputed transactions against payment network rules, government regulations, and merchant policies without requiring human personnel. The AI model independently evaluates evidence, applies relevant rules, and determines dispute outcomes, eliminating the need for teams of personnel while maintaining consistent application of complex regulations.
Solution Approach 2:
The patent replaces the mechanical system of human personnel reviewing and deciding disputes with an artificial intelligence model that automatically processes disputed transactions. The AI model systematically evaluates transaction data, evidence, and applicable rules to determine dispute outcomes, eliminating human error and inconsistencies while improving resource efficiency and scalability.
2Productivity
If multiple personnel are deployed to resolve disputes, then more cases can be handled, but human error and inconsistent interpretation of rules increase
Solution Approach 1:
The system ensures homogeneous application of dispute resolution rules by using a single AI model that consistently evaluates all disputed transactions against the same payment network rules, government regulations, and merchant policies. This eliminates the variability inherent in human interpretation and ensures uniform outcomes across all cases, regardless of volume.
Solution Approach 2:
The AI model autonomously handles the complete dispute resolution process without human intervention, automatically applying rules and determining outcomes. This self-service capability allows the system to process any volume of disputes with consistent reliability, as the same automated logic is applied uniformly to all cases.
3Measurement precision
If manual review processes are used, then complex regulations can be thoroughly evaluated, but the process becomes time-consuming and resource-intensive
Solution Approach 1:
The patent replaces manual review processes with an AI model that automatically and accurately evaluates disputed transactions against complex payment network rules, government regulations, and merchant policies. The system efficiently processes and compares transaction data with applicable rules, determining outcomes without the time-consuming nature of manual review while maintaining thorough evaluation accuracy.
Solution Approach 2:
The AI model continuously and automatically evaluates disputed transactions without interruption or delay. The system processes transactions in real-time, continuously applying rules and generating outcomes, eliminating the intermittent and sequential nature of manual review processes. This continuous automated action significantly reduces dispute resolution time while maintaining accurate rule application.
Data Source
AI summary
Technologies for resolving disputed transactions include a system with circuitry configured to receive a user interaction from a user interface channel, provide the user interaction with multiple topics and available actions for agent responsibility to a large language model, identify an action and parameters related to a dispute for a financial transaction in response to providing the user interaction to the large language model, execute the identified action with the parameters, and log data indictive of the user interaction, the identified action, the parameters, and any response. Other embodiments are also described and claimed.