Banks worldwide are accelerating the deployment of AI agents that can initiate transfers, approve payments, flag anomalies, and even freeze accounts in milliseconds. The promise is speed, scale, and round-the-clock execution. The challenge is identity.
Traditional security architectures were designed around humans. A person logs in, proves who they are through passwords, biometrics, or one-time codes, and then performs an action. With AI agents, that sequence breaks. The system must now verify two actors simultaneously: the human who delegated authority and the machine carrying it out. This is the emerging dual-authentication crisis.
If an agent is compromised, misconfigured, or overly privileged, it can move money at machine speed long before manual oversight can intervene. Unlike employees, agents do not sleep, hesitate, or second-guess unusual instructions. They execute.
Risk leaders warn that legacy identity and access management tools lack the granularity to determine intent, scope of delegation, and real-time behavioral legitimacy. Who is liable—the bank, the customer, or the software provider—when an autonomous system makes the wrong call?
Regulators are beginning to ask similar questions. Auditability, explainability, and revocation of authority are becoming as important as raw automation capability.
The path forward is not to slow AI adoption but to redesign trust frameworks for a world where software acts as a financial operator. Continuous verification, least-privilege delegation, and immutable activity trails will define the next era of banking security.
In the race toward autonomous finance, identity has become the new control plane.
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