AI Opportunities in Card Replacement Calls for Banks

A recent report from PYMNTS highlights a significant opportunity for card issuers to leverage artificial intelligence (AI) in enhancing customer service, particularly in the realm of card replacement. Approximately 25% of inbound calls to contact centers are related to card status, indicating a substantial area where AI can streamline processes and improve customer experiences. This finding is critical as it suggests that by optimizing card replacement workflows, issuers can not only reduce call volumes but also enhance operational efficiency.

The report, titled “Why Modern Issuing Platforms Will Determine Which AI Strategies Succeed,” produced in collaboration with Thales, emphasizes that the effectiveness of AI is contingent upon the integration of modern systems that share real-time information and enforce clear operational protocols. For card issuers, this means that a connected issuing platform can facilitate the entire lifecycle of a card—from account creation to replacement—by automating and coordinating various tasks that are typically siloed across different teams.

AI can play a pivotal role in managing the complexities of card replacement. When a card is reported lost or damaged, multiple steps are triggered, including address verification, card production, and updates to digital credentials. Traditionally, these tasks are handled separately, leading to delays and customer frustration. A unified platform allows AI to streamline these processes, enabling simultaneous actions and reducing the time it takes to fulfill customer requests. This integration is akin to a relay team that operates seamlessly without the need to pause at each handoff.

Moreover, enhancing communication through AI can significantly decrease the number of unnecessary customer inquiries. By providing proactive updates regarding card status and delivery, issuers can keep customers informed and reduce the likelihood of them reaching out for information. This not only improves customer satisfaction but also allows service teams to focus on more complex issues that require human intervention.

The report also notes that for AI to be effectively deployed, it must have access to reliable customer data, transaction histories, and institutional policies. Modern issuing platforms facilitate this by connecting disparate systems, thereby enabling a broader range of automation. This capability extends beyond card replacements to include transaction disputes and the introduction of new card products, all of which necessitate collaboration among multiple teams. Incorporating human oversight into these automated processes is essential for maintaining security and fostering customer trust.

Despite the potential, the report reveals that many banks have yet to fully embrace AI. Research from EY indicates that only 16% of banks have fully deployed AI in production, while 52% have merely piloted its use. In contrast, Visa reports that 60% of neobanks and fintech companies have experienced significant AI advancements in transaction risk management, compared to just 44% of traditional banks. This disparity underscores the competitive advantage that agile, technology-driven firms hold over their more established counterparts.

To capitalize on these insights, the report recommends that issuers identify and modernize disconnected processes while establishing governance frameworks. This approach offers a practical pathway for banks to enhance their AI capabilities and improve customer service.

As the landscape evolves, card issuers must recognize that the integration of AI is not merely an operational enhancement but a strategic necessity. Companies that can effectively harness AI to streamline customer interactions and improve service delivery will likely gain a competitive edge in an increasingly digital financial ecosystem. The ability to respond swiftly to customer needs while maintaining robust security protocols will be crucial as the market continues to shift toward more automated and efficient service models.