Visa Inc. has announced the introduction of six artificial intelligence-based tools aimed at enhancing the credit card dispute resolution process. These innovations are designed to alleviate the financial burden and frustrations associated with current, largely manual dispute mechanisms impacting merchants, issuers, and acquirers.
Andrew Torre, Visa’s president of value-added services, highlighted the significance of modernizing outdated back-office systems. In 2025, Visa handled over 106 million charge disputes globally, reflecting a 35% increase since 2019. Torre noted the company’s objective is to streamline this process significantly, ultimately reducing the growth rate of disputes.
Three of the newly introduced tools are tailored for merchants, enabling them to preemptively address disputes, manage cases using generative AI, and gain detailed insights into customer orders, thereby reducing confusion over unknown charges. Torre emphasized that many disputes arise from cardholders’ inability to recognize specific charges. The new tools will help financial institutions provide clearer data to customers.
The remaining three tools target issuers and acquirers, employing predictive AI to assist in individualized case analysis, automate document summaries and auto-filling processes, and create an all-in-one AI-powered dispute management platform. Torre explained that these innovations aim to shift the approach from reactive to proactive, ultimately delivering better outcomes for all parties involved.
In addition to the dispute resolution tools, Visa has recently introduced a subscription manager to help cardholders cancel unnecessary services efficiently. The overall suite of tools is expected to be available later this year.
Why this story matters:
- Visa’s advancements could redefine dispute resolution in digital payments.
Key takeaway:
- The introduction of AI tools aims to streamline credit card charge disputes and enhance customer experiences.
Opposing viewpoint:
- Concerns exist regarding the reliance on AI, including potential issues with data accuracy and the impact on jobs within the industry.
