Credit Card Dispute Resolution: Leveraging Generative AI for Efficient Conflict Management

Credit card disputes arise from various sources, including unauthorised transactions, billing errors, or issues with goods and services purchased through POS, e-commerce, or ATM withdrawals. Generative AI is transforming the dispute resolution landscape by streamlining processes, reducing costs, and enhancing fairness. Below, we delve into the current state of dispute resolution and how AI can improve it.

1. Understanding Credit Card Disputes

Types of Disputes:

• Unauthorised Transactions: Often due to card skimming or hacking, these involve charges made without the cardholder's consent.
• Billing Errors: Incorrect amounts charged or duplicate transactions.
• Item Not Received or Not as Described: Issues with delivery or product quality.

Platforms Involved:

• Point of Sale (POS): In-store purchases where disputes may arise due to incorrect charges or unauthorised transactions.
• E-commerce Websites: Online transactions where issues like non-delivery or product mismatches are common.
• ATM Withdrawals: Disputes related to cash dispensing errors or unauthorised withdrawals.

2. Current Dispute Resolution Process

Steps in Dispute Resolution:

1. Cardholder Initiation: The cardholder contacts their bank to dispute a transaction, providing details and supporting documentation.
2. Bank Investigation: The bank reviews the claim and may request additional information from the merchant.
3. Chargeback Process: If the bank finds the dispute valid, it initiates a chargeback, temporarily refunding the cardholder.
4. Merchant Response: The merchant can contest the chargeback by providing evidence of a legitimate transaction.

3. Role of Generative AI in Dispute Resolution

Prevention Strategies:

• Predictive Analytics: AI analyses transaction patterns to identify potential disputes before they occur, allowing for proactive measures like enhanced verification processes.
• Contract Analysis: AI reviews contracts for ambiguous terms that might lead to disputes, suggesting clarifications to prevent misunderstandings.

Automated Resolution:

• AI-Driven Case Triage: AI categorises disputes based on complexity and urgency, routing them to appropriate resolution channels.
• Evidence Compilation: AI assists in gathering and organising evidence (e.g., receipts, delivery records) to support merchant claims.
• Predictive Outcome Analysis: AI evaluates historical data to predict dispute outcomes, helping parties make informed decisions.

4. Benefits of AI in Dispute Resolution

Speed

Resolves disputes in hours vs. months.

Cost Savings

Reduces legal fees, administrative costs, and operational downtime.

Objectivity

Minimises human bias by relying on data-driven insights.

Scalability

Handles thousands of cases simultaneously without resource strain.

5. Challenges and Ethical Considerations

• Bias in Training Data: AI models must be trained on diverse datasets to avoid perpetuating biases.
• Transparency: Explainable AI is crucial to ensure that decisions are understandable and fair.
• Regulatory Compliance: Adherence to privacy laws and ethical guidelines is essential.

6. The Road Ahead

Implementation Steps for Organisations:

1. Assess Needs: Identify areas where AI can improve dispute resolution processes.
2. Adopt Hybrid Models: Combine AI efficiency with human judgment for complex cases.
3. Train AI on Domain-Specific Data: Use historical dispute records to refine predictive models.
4. Monitor and Iterate: Continuously audit AI performance and update algorithms.

Future Trends:

• AI Judges in Small Claims: Automated systems could adjudicate low-stakes disputes.
• Global Dispute Platforms: Unified AI systems may resolve cross-border conflicts by harmonising international laws.

Conclusion

Generative AI is poised to revolutionise credit card dispute resolution by enhancing speed, fairness, and efficiency. While challenges exist, proactive governance and human-AI collaboration will unlock its full potential. As AI continues to evolve, it will play an increasingly critical role in managing disputes across POS, e-commerce, and ATM transactions.