How AI Agents Are Splintering the Financial Industry

Photo of a man at the desk interacting with a cell phone.

For decades, banks and large financial institutions have served as the backbone of our economic systems. Their services were essential, their expertise exclusive, and their infrastructure unrivaled. But today, a new force is emerging that challenges their dominance not through confrontation, but through quiet, scalable substitution: AI agents.

AI agents are software systems that can reason, fetch data, analyze financial instruments, and produce actionable insights—all without human intervention. They don’t just replicate the work of a junior analyst or a robo-advisor; they represent a fundamental shift in who controls financial knowledge, access, and execution.

This shift has major implications. It threatens to erode the fee-based models that many financial institutions rely on. It undermines the very idea of centralized financial authority. Most significantly, it lays the groundwork for a splintered financial ecosystem: a future where finance is no longer controlled by a few monolithic institutions, but distributed across interoperable, intelligent systems.

What Financial Institutions Used to Offer

Traditionally, banks and investment firms justified their fees by providing access to things users couldn’t get on their own:

  • Data and insight: Institutional investors had better research tools, insider analysis, and economic forecasts.

  • Execution infrastructure: Trading, transfers, custody, and compliance were wrapped in expensive, proprietary systems.

  • Human advisory: Experts offered bespoke advice, long-term strategies, and trust built over relationships.

  • Regulatory overhead: Institutions handled the legal complexity of moving money and managing risk.

These value propositions made sense when the average user had neither the tools nor the expertise to operate independently. But the landscape is changing fast.

What AI Agents Now Provide

Modern AI agents remove many of the barriers that once required financial intermediation. Built on platforms like OpenBB, LangChain, or other open-source ecosystems, these agents can:

  • Analyze equities, portfolios, or macroeconomic trends in real time

  • Perform customized risk analysis based on user-defined criteria

  • Pull and synthesize data from APIs, news, social sentiment, and earnings reports

  • Recommend asset allocations based on real-time conditions, not static models

  • Offer structured outputs: dashboards, alerts, tables, charts, and even citations

And they do all this at a near-zero marginal cost. They operate continuously, improve with more usage, and are fully programmable.

For example, OpenBB’s financial agents can be deployed privately or shared across teams, integrating both internal and external data. In one configuration, agents specialize: one handles macro data, another evaluates technical indicators, another focuses on sentiment. A supervisor agent orchestrates them, combining their outputs into a single, usable insight for the end user.

This isn’t theoretical. It’s already happening.

Why Traditional Fee Structures Are Under Pressure

AI agents are poised to erode the economic foundations of many financial services. Some of the most vulnerable include:

Service TypeWhy It's at Risk
Wealth management (1–2% AUM fees)Agents offer tailored portfolios and rebalancing strategies at a fraction of the cost
Trading commissionsSmart order routing via agents reduces reliance on brokers and minimizes spread costs
Fund managementAI can replicate or outperform traditional strategies, making high-fee active funds obsolete
Transfers and wiresOn-chain and agent-mediated systems make global transfers cheaper and faster
Credit analysisAI-based lending decisions reduce the need for expensive origination services

When users can run an agent that performs better analysis, faster and cheaper than a human advisor, the justification for traditional fees disappears.

Toward a Splintered Financial Market

As AI agents grow more capable and accessible, the financial market is splintering. Here's what that fragmentation looks like:

  • Banking infrastructure becomes modular: APIs replace legacy rails. You don’t need a “bank”, you need components like custody, KYC, or payments, which can be plugged in as needed.

  • Investment services unbundle: Research, risk, allocation, and execution are separated and recombined using agents tailored to individual users or firms.

  • Lending decentralizes: Peer-to-peer and smart-contract-based lending, powered by AI scoring models, challenge centralized credit systems.

  • Advice is personalized and decentralized: Agents trained on your financial goals act like digital financial planners—without sales incentives.

  • Compliance is managed at the edge: AI agents can handle KYC/AML locally, monitor transaction risk, and adapt to jurisdictional rules without centralized oversight.

This is not the creation of one new financial institution to replace the old ones. It's the emergence of thousands of intelligent, interoperable services.

But What About Trust?

Financial institutions have always relied on trust. Band equity, security assurances, regulatory oversight. AI agents can’t fully replace this, but they shift the basis of trust.

Instead of trusting a bank, users will trust:

  • The agent’s code and transparency (explainability, logs, citations)

  • The data it uses (auditable, sourced, permissioned)

  • The system it runs on (secure, self-hosted, or open-source)

Institutions that adapt to this model, providing infrastructure, regulatory guarantees, and user control, can still thrive; those that cling to opacity and fees for basic services will struggle.

A Reorganization

AI agents don’t eliminate the need for financial services; they reorganize how they are delivered and who controls them. Institutions apparently will evolve into:

  • Back-end providers for compliance, custody, or liquidity

  • Agent hosts offering enterprise-grade AI tooling for clients

  • Data aggregators that feed agent systems with verified financial data

The center of gravity shifts from institutions to agents, and from products to personalized services.

En fin

The future of finance isn't monolithic. AI agents are empowering individuals and small business to operate at a level that once required an army of analysts and millions in infrastructure. This democratization challenges the economics of traditional finance, especially those built on fees and exclusivity.

A fragmented, agent-powered financial landscape is coming, not out of ideology, but because it’s simply more efficient, more transparent, and more aligned with user needs.

The splintering has already begun.

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