How AI is Redefining the Open Banking Revolution in the US

A forward-looking bank’s guide to building the infrastructure for an open, agentic AI-driven, customer-centric future.

91% of US consumers link their bank accounts to third parties.

Unlike the UK/EU, the US does not have a federal mandate for open banking. Adoption is industry-led and driven by fintech partnerships and consumer demand for integrated financial apps. According to the 2024 Visa report titled “Open banking, open possibilities”, open banking is approaching full penetration in the US.

Despite the lack of a regulatory framework, open banking in the US is set to reach new benchmarks, thanks to customer demand and FI push.

This white paper details why Open Banking is the Future of Finance.

What This Means for the IT Infrastructure of US FIs

Financial institutions need to continue their compliance efforts, while refining their data practices as agentic AI prepares to take the steering wheel. Here’s what your infrastructure needs:

API-Centric Architecture

Banks must build robust API layers on top of core systems for real-time data sharing using REST/JSON standards, OAuth 2.0, etc. Many are already implementing API gateways and developer portals to manage third-party access, throttle usage, and provide sandboxes for fintech developers.

Legacy Modernization & Integration

Banks are introducing middleware and microservices to bridge core systems with external-facing APIs. This requires refactoring legacy processes into more modular services, migrating significant workloads to cloud platforms, and ensuring high availability for always-on connectivity.

Data Security & Privacy Controls

Banks must comply with GLBA (Graham-Leach-Bailey Act) and other data privacy laws when sharing customer data. Infrastructure investments include encryption of data in transit, robust authentication, such as multi-factor for API access, and monitoring tools to detect anomalies in API usage that might indicate breaches.

Third-Party Risk Management

IT teams must extend vendor risk management to API consumers. Regulators (OCC, FDIC, etc.) have issued guidance on managing the risks of these interconnections. This entails onboarding processes for new API partners, ongoing due diligence, and establishing support frameworks (developer support, issue escalation) to maintain reliability across integrations.

Scalability & Performance

The infrastructure must handle high API transaction volumes with low latency. Banks are adopting cloud and load-balanced architectures to scale on demand. Caching mechanisms and efficient API design (e.g., filtering data at source) are used to optimize performance.

Compliance and Standards Alignment

Adhering to a common data schema and security profile, such as FDX’s use of OAuth2 and FAPI profiles, reduces complexity and accelerates integration with multiple partners. Many banks also ensure their APIs meet any forthcoming regulatory tech standards to avoid rework.

AI as a Catalyst for Open Banking Adoption in the US

Harnessing AI has enabled FIs to:

Break Down Data Silos

Today, the average US consumer uses 15–20 financial institutions or apps, yet any single bank only sees ~25% of that customer’s economic life. Open banking enables banks to get a fuller picture of customers’ finances. This, when fed into AI/ML models, allows far more accurate insights, risk assessments, and personalization.

Deliver Hyper-Personalized Services

With open banking data, banks can use AI to craft highly personalized recommendations and services, strengthening customer loyalty.

“The world is now awash in data, and we can see consumers in a lot clearer ways.” — Max Levchin.

Data lies at the foundation of lasting customer relationships.

Learn how in this Strategic Guide to Transforming Customer Relationships in Banking.

Centralize Customer Relationships

AI can turn banks into financial hubs by leveraging open banking data. This “hub” strategy not only improves customer engagement but also incentivizes banks to adopt open banking (to avoid being displaced by fintech aggregators).

Optimize Operational Efficiency & Risk Management

AI can reduce the friction of implementing open banking by automating and optimizing processes. For instance, machine learning can monitor API traffic in real time to flag suspicious activities. AI tools can automatically check shared data for regulatory compliance, easing the burden of opening APIs.

Use Case ROI to Drive Adoption

Banks see that open data combined with AI can improve underwriting, power automated financial advice, and even identify revenue opportunities. These tangible benefits are helping rally executive support and budget for open banking initiatives.

Agentic AI paves the way for new products and services with open banking

Agentic AI refers to AI “agents” that can autonomously perceive, decide, and act on behalf of users. When combined with open banking (rich, permissioned data and interoperable services), these AI agents unlock powerful new financial use cases:

Autonomous Personal Finance Coach

AI agents can act as self-driving money managers for consumers. For example, an AI financial agent monitors all linked accounts and transactions across multiple banks of a user to optimize finances in real-time. It might automatically move funds to a savings account with higher interest or negotiate better loan terms by comparing offers across lenders via APIs.

Here’s what Personetics Global Survey found:

Automated Bill Switching & Cost Savings

Building on open banking data, AI agents can continuously hunt for cost savings on recurring expenses. A leading UK-based neobank’s AI agent monitors users’ utility bills via open banking and automatically finds cheaper providers, initiates the switch, fills out forms, and updates payment instructions, requiring just a one-click confirmation from the customer.

Dynamic Fraud Detection & Security

Agentic AI can supercharge fraud detection and compliance by analyzing patterns across a consumer’s entire financial activity, rather than within one bank’s silo. For instance, an AI agent could learn a user’s spending patterns across multiple cards and accounts and distinguish legitimate unusual behavior from fraud. Such an AI agent helped a European bank cut false fraud alerts by 40%.

Real-Time Product Matching & AI Marketplaces

Consumers could let AI agents shop for financial products in real time. An agent could use APIs to dynamically retrieve personalized quotes or even negotiate with other AI agents representing financial providers.

Proactive Financial Assistance & Service

Agentic AI assistants can initiate conversations and actions based on open banking data triggers. For example, if a small business’s bank agent sees that a checking account at another bank is low while bills are due, it could alert the business owner or automatically set up a just-in-time transfer.

Bottom Line: Agentic AI heralds a new era of autonomous, tailored banking services.

Conclusion & Key Takeaways

For financial institutions, open banking is a strategic opportunity to unlock new partnerships and services that meet the dynamic demands of today’s digital-first customers. AI amplifies the value of open banking data, while the future lies in customers entrusting routine financial decisions to autonomous agents.

With open banking coming of age in the US, the right infrastructure, smart use of AI, and support from forward-looking vendors can help financial institutions accelerate innovation while safeguarding trust. The mandate for CXOs is clear: open up, team up (with fintechs and tech providers), and step up to stay ahead in the digital finance ecosystem.