Written by Chandler Fang
Walk into any bank and ask to open an account or transfer a large sum of money, and the first thing you’ll hear definitely won’t be, “How much would you like to deposit?” Instead, it’s much more likely to be something like, “Sure, can I see a form of identification?”
That small interaction says a lot about how the financial system works. Before any money moves, before any transaction is approved, and before any relationship begins, there has to be trust., which starts with identity. Banks are not being difficult for the sake of it, they need to know exactly who they are dealing with.
Regulators require it. Risk teams depend on it. Customers expect it. Identity is one of the foundational pillars of modern finance because every other process, from payments to lending to investing, is built on top of it.
Now imagine replacing the person standing at the counter with an AI agent. That agent could open accounts, rebalance portfolios, pay suppliers, hedge currency exposure, and move funds across borders without sleeping, taking breaks, or waiting for office hours. It could make thousands of decisions every day and act on them in real time. That is the tantalising promise of the agentic economy.
It’s an exciting vision, but if an agent is acting on your behalf, how does it prove it can be trusted?
Fast Decisions Need Even Faster Trust
AI agents are fundamentally different from traditional software. Most software follows narrow instructions and waits for human input. Agents are more autonomous. They can interpret goals, make judgment calls, and adapt to changing circumstances. In finance, that means they may decide when to move money, which invoices to pay, which assets to buy, or how to respond to unusual market conditions. And they can do all of this 24 hours a day, seven days a week.
That constant activity is what makes them so powerful, but it is also what makes them risky.
If a human employee makes a poor decision, there is usually time to catch it. A manager reviews the transaction, a compliance officer spots an issue, or a control process flags something unusual. With AI agents, decision cycles are compressed from hours or days into milliseconds, which changes everything.
A small error that once affected one transaction could now be repeated thousands of times before anyone notices. An incorrect instruction, a misunderstood mandate, or a flawed model assumption could trigger a cascade of actions at machine speed. And if money is lost, who takes responsibility?
Is it the individual who delegated authority? The company that developed the agent? The provider of the underlying model? Or the institution that allowed the transaction to proceed?
These questions go to the heart of how trust will be established in the agentic economy.
Compliance Has to Become Continuous
The traditional compliance model was built for a slower world. Risk controls were designed around periodic reviews, approval chains, and manual oversight. That approach works reasonably well when humans are making a manageable number of decisions each day. It does not work when autonomous agents are making thousands of micro-decisions every minute.
In the agentic economy, compliance has to operate continuously, which means every agent needs a verifiable identity and a clearly defined mandate. It needs to prove what it is authorized to do, who it represents, and what limits apply to its actions. Transaction thresholds, fraud detection, sanctions screening, and audit logging must happen in real time rather than after the fact.
Just as importantly, there needs to be automatic escalation when something looks unusual.
If an agent attempts to exceed its authority, initiate an unfamiliar payment pattern, or behave inconsistently with its instructions, the system should pause the activity and alert a human operator immediately.
This is where trust becomes more than a philosophical concept, it becomes infrastructure.
Identity frameworks, cryptographic credentials, permissioning systems, and tamper-proof audit trails will provide the foundation for agent-based finance. They will allow institutions to verify not just who is acting, but under what authority and with what accountability.
Trust Will Determine Who Wins
The companies that succeed in the agentic economy will not necessarily be the ones with the most advanced models or the fastest agents. They will be the ones that build the strongest trust architecture. Consumers and businesses are willing to delegate tasks to machines, but only when they feel confident that the system is secure, accountable, and operating within clearly defined boundaries. Speed and efficiency are valuable, but they are not substitutes for trust.
In many ways, the future of autonomous finance will look a lot like the banking system we already know. Before anything important happens, someone, or something, will need to prove who they are, what they are allowed to do, and who is responsible if things go wrong.
That principle is as old as banking itself.
The difference is that instead of verifying a passport at a branch counter, we will be verifying the credentials and permissions of intelligent agents acting at machine speed. The agentic economy has enormous potential. AI agents could reduce operational costs, improve financial decision-making, and create entirely new ways for businesses and individuals to manage money. But none of that will matter if trust is missing.
