Balancing efficiency and empathy in retail payments disputes with AI

• How can financial institutions balance the need for operational efficiency with delivering a high-quality, empathetic customer experience when resolving payment disputes and fraud cases?
• What are the key regulatory differences across regions – for example, the UK, US, Canada – that impact how banks handle consumer disputes, and how should institutions adapt their processes accordingly?
• In what ways can automation and AI, including agentic AI, be effectively applied to dispute resolution, and what are the limitations or risks of over-relying on these technologies?
• Why is it important for banks to adopt a unified, interoperable approach to dispute management rather than relying on siloed solutions, and what are the practical steps to achieve this?

Financial institutions are under increasing pressure to resolve payment disputes and fraud cases swiftly while maintaining a high standard of customer experience. As real-time payments become the norm, the window for fraud detection narrows, demanding faster, more intelligent workflows. Manual processes are no longer sustainable; banks must modernise their dispute resolution systems to meet consumer expectations for speed, transparency, and fairness. Banks need to be empathetic; disputes, especially those related to fraud or scams, are highly emotional events. The industry must ensure that customers have a choice included as part of their user experience with their bank.

Regulatory frameworks governing payment disputes vary significantly across regions. In the UK, the Financial Conduct Authority (FCA) has introduced stricter safeguarding rules and emphasised consumer protection under the Consumer Duty. Meanwhile, the US is seeing increased litigation and calls for federal regulation – even though the CFPB has been pulled back in the short term – to shift fraud liability toward financial institutions. Canada’s approach remains more conservative but is evolving in response to global trends. Institutions must adapt their processes to remain compliant across jurisdictions, which requires both legal agility and operational flexibility to manage cross-border disputes effectively.

Automation and agentic AI are transforming dispute resolution by enabling automation, decision-making, and remediation. These technologies can dramatically reduce resolution times and improve accuracy, especially in high-volume environments. However, the industry must caution against over-reliance and remain empathetic to the stresses involved in retail disputes. Risks include systemic bias, lack of transparency, and regulatory uncertainty. Agentic AI systems must be predictable and carefully governed, with human oversight and ethical safeguards in place. Selecting low-risk, high-impact use cases, such as screening for friendly fraud or automating document collection, can help banks realise benefits without compromising trust or compliance.

Siloed systems remain a major barrier to effective dispute resolution. Fragmented data and disconnected tools lead to delays, inconsistencies, and poor customer outcomes. This is where a unified, interoperable approach comes in, where data flows seamlessly across departments and platforms. Practical steps include investing in cloud-native data unification, adopting open APIs, and aligning internal goals across fraud, compliance, and customer service teams. By dismantling silos and fostering collaboration, banks can build resilient, scalable dispute management systems that support both operational excellence and customer satisfaction.

Register for this Finextra webinar, hosted in association with Pega, to join our panel of industry experts who will discuss why banks must adopt a unified, interoperable approach to dispute management.