Consider a common scenario. A member receives a call that appears to come from their credit union. The caller explains that the member’s account has been compromised and instructs them to move the funds into a secure account. Convinced by the caller’s knowledge of their account and with the intention of protecting their money, the member validates the transfer. The payment is authenticated, security controls function as intended, and yet the member still suffers a financial loss.
That shift from authentication to intent represents one of the most significant operational changes facing credit unions. According to ACI Worldwide’s Scamscope Report, APP fraud losses in the U.S. are projected to rise from $2.16 billion in 2023 to $3.08 billion by 2028, meaning this dispute challenge is one that credit unions will continue to face over the next decade.
Credit unions must be capable of reconstructing the timeline of events, gathering supporting context across multiple channels, and assessing if the available evidence contextualizes the authentication determination. Completing those steps requires coordination across fraud operations, disputes, digital banking, payments, contact centers, compliance, and legal teams. Analysts may need to review the signals that were present, transaction records, authentication logs, device and session data, fraud alerts, digital banking activity, member communications, and prior case records.
Most of the necessary information already exists, but it is often dispersed across multiple applications and departments. Investigators must gather files, reconcile information, and coordinate with several teams before they can produce a defensible record. When documentation practices vary and ownership is fragmented, these handoffs introduce delays, reduce visibility, and make it difficult to maintain a cohesive record. Operational risk increases as a result, while case decisions become challenging to explain and defend during examiner reviews. The compliance conversation is moving beyond simply following Reg E timelines toward ensuring institutions have the operational infrastructure to consistently document, govern, and defend how case decisions were made.
Artificial intelligence (AI) has an important role to play in this evolution by supporting repeatable, information-intensive tasks. It can aggregate information across multiple systems, build timelines, summarize large volumes of documentation, identify missing evidence, and surface patterns that may otherwise be overlooked. These capabilities can significantly improve efficiency as case volumes continue to increase. Human expertise also remains essential as investigators must still evaluate conflicting evidence, determine if authorization can reasonably be supported, apply regulatory requirements, and approve final outcomes and member communications.
Effective AI depends on strong governance and consistent case documentation. When evidence is fragmented or investigative processes vary, AI is limited in its ability to generate reliable insights. Well-governed case management provides the structure needed for AI to support intent-based investigations while preserving the transparency, accountability, and auditability that evolving regulatory expectations demand.
Strong governance will become a defining capability as fraud tactics and regulatory expectations continue to evolve. Credit unions that can align case work across teams, preserve a complete record, and provide clear, defensible explanations of their decisions will be better positioned to protect members, satisfy regulators, and strengthen operational resilience.