Banking's New Identity Problem: Real-Time Fraud 

Financial institutions have spent years building fortress-level defenses like layered authentication, real-time fraud monitoring, and endless customer education campaigns. Generative AI just handed impostors the keys to walk right past it all.

Today, banks and credit unions are increasingly confronting scammers who can replicate voices, generate convincing identification documents, create synthetic identities, impersonate executives or family members, and produce remarkably realistic videos. As their tactics grow more sophisticated, financial institutions face a core question: How do we really know this is the person they claim to be?

Running parallel with this challenge is the speed of financial activity. According to the ABA Banking Journal, voice fraud [in banking] increased roughly 30% in 2025 and is trending upward this year. At the same time, instant payments continue to expand, but the window to identify suspicious activity before money moves is shrinking.

Consequences extend well beyond financial loss. AI-enabled fraud erodes customer trust, damages an institution's reputation, increases operational costs, and creates regulatory and compliance exposure.

Verifying credentials used to be enough. In today’s environment, it isn’t. Financial institutions must also consider context and behavior, using information around an interaction or transaction to determine whether the person on the other side is really who they claim to be.

The Data Problem
Credentials tell a financial institution who someone claims to be. Data can determine whether their behavior validates their claim.

Consider a customer or member who successfully provides appropriate credentials. On the surface, the encounter appears legitimate, but what if the login comes from an unfamiliar location, follows a recent password reset, and is immediately followed by an unusually large transfer to a new recipient? Individually, these signals may not indicate fraud, but when put together in context, they tell a markedly different story.

Fortunately, banks and credit unions already have much of the information needed to provide additional context. The challenge is deriving those signals before making decisions. If critical information is fragmented across disparate systems, the institution might not connect the dots in time to flag the fraudulent behavior.

What Financial Institutions Can Do About Real-Time Fraud

Banks and credit unions need a clear strategy and data architecture that lets existing technologies work together, so identity is evaluated not only by the credentials someone provides, but also by the context surrounding the interaction. Start by examining how authentication, fraud, payments, digital banking, and other systems share information. Identify gaps where important signals don’t reach employees or systems when decisions are made.

Banks and credit unions must also hold vendors accountable and ask the right questions. What data does the solution consume, and can it incorporate information from other systems? How well is the vendor adapting its fraud and authentication capabilities for AI-enabled threats? How is the vendor leveraging AI within its solution, and what controls, explainability, and oversight measures are in place?

Employees remain an important layer of the institution’s defense against fraud, especially as these criminals use increasingly sophisticated social engineering tactics. Train contact center and frontline employees to recognize emerging AI-enabled fraud and give them clear escalation procedures when a scenario doesn’t compute. Just as importantly, make relevant customer context readily available, so employees aren’t forced to search across multiple systems when they need to decide.

Community financial institutions have a valuable relationship advantage. Banks and credit unions often know their customers and members in ways larger financial institutions do not. Those personal relationships can add context that technology alone cannot replicate. The goal shouldn't be to replace human knowledge with technology, but to equip employees with better data so they can put that knowledge to work.

Fraud will continue to evolve alongside AI, and no single tool or policy will solve for it permanently. The answer isn't to fear the technology, but to build the strategic discipline to keep pace. That means treating fraud prevention as an ongoing program, not a one-time investment: regularly revisiting fraud scenarios, controls, employee training, and vendor capabilities as generative AI advances.

Engage fi partners with banks and credit unions to evaluate the right technology and vendors, stress-test their controls, and build an adaptable fraud strategy that strengthens defenses without adding friction for customers and members. In a landscape that won't stop changing, having the right advisor at the table keeps institutions ahead. Learn more at www.engagefi.com.