New England’s community and regional banks have long thrived on local trust. Customers walk into a branch not just for financial services but for a sense of familiarity and human connection. That trust is their strength — but it is no longer enough to compete in today’s digital-first world.
The reality is that individually, these larger community banks face structural limits. Their balance sheets are smaller, their technology budgets constrained, and their digital experiences often lag those of national players and fintechs. JPMorgan alone spends over $15 billion annually on technology. A single community bank cannot match that scale.
But what if they didn’t have to?
What if a group of banks pooled their resources to create a New England Banks AI Exchange — a shared platform delivering enterprise-grade intelligence and efficiency, while allowing each bank to preserve its brand and customer intimacy?
A Shared AI Exchange : How it could work
Pooling resources would unlock AI capabilities no single bank could achieve alone.
Four areas stand out
- Fraud & AML Intelligence : A shared, anonymized transaction dataset would train AI to detect fraud patterns faster and more accurately. Each bank benefits from richer insights, while regulators gain comfort knowing systemic blind spots are addressed collectively.
Impact: Higher detection accuracy, lower fraud losses, reduced compliance costs. - AI-Powered Credit Decisioning: By pooling anonymized SME and consumer credit data, banks could build stronger models to predict delinquency and support smarter underwriting. Each member plugs into the shared AI engine via APIs, while retaining local decision authority.
Impact: Faster lending, better risk management, a level playing field with national banks. - Customer Service AI Hub: Banks could co-develop multilingual service bots for FAQs, disputes, and onboarding. Each bank customizes the front end, but the intelligence improves collectively.
Impact: Better 24/7 service at lower cost, with digital parity against fintechs. - Talent & Infrastructure Pooling: Instead of competing for scarce AI engineers, banks could staff a joint AI Center of Excellence. Infrastructure costs — cloud GPUs, training, monitoring — are shared. They could also partner with local universities such as University of Connecticut to pilot the AI Exchange, tap into research, and secure a pipeline of graduates.
Impact: Cutting-edge AI without straining individual budgets.
Why This Matters Now
Bank customers no longer benchmark their bank against the one across town. They compare it to the app on their phone. If fintechs deliver instant onboarding and predictive insights, expectations shift everywhere.
As Tom Grottke, CPA, Managing Partner & CEO of The NBS Group, LLC, observes:
“Absolutely a sea change has occurred in the relative efficacy of the New England community bank branch over the last decade inclusive of the Pandemic. Traffic is way down, customers are not getting younger, and with relatively weak to no online account opening by these community banks, the branches are not really a meaningful ‘road sign’ advertisement for when a potential customer goes online after hours and searches for a bank to open an account.”
This is exactly why digital sophistication is no longer optional.
A Practical Way Forward
Skeptics will point out that collaboration is difficult — banks worry about competition, governance, and data sharing. All valid concerns. But the way forward isn’t to build a perfect utility from day one. It’s to start small, prove value, and expand.
Step 1: Pick one use case, such as fraud detection.
Step 2: Run a secure pilot hosted by a neutral cloud partner — potentially with a university like UConn as research collaborator and talent provider.
Step 3: Measure outcomes — lower fraud losses, faster alerts.
Step 4: Use those results to build trust, then expand into credit decisioning and customer service AI.
This incremental path lowers cultural barriers while also positioning the AI Exchange as a collaborative ecosystem among banks, regulators, and academic partners.
Shared AI as a Regional Edge
New England’s community and mid-sized banks will probably never outspend JPMorgan or replicate Bank of America’s national reach. But they don’t need to. Their true edge lies in local trust and relationships. By collaborating on AI, they can combine that intimacy with digital sophistication.
Pooling AI power won’t be simple. It requires trust, governance, and experimentation. But bold moves are rarely easy. If New England’s banks want to thrive in the decade ahead, experimenting with a shared AI Exchange could be the most powerful step they take together.
Head to this link to read Part 2 & Part 3 of this series
About the Author
As the Director and Regional Head of the North America region at Maveric Systems, Pankaj Misra is responsible for driving strategic growth, scaling accounts, building new client relationships, and forming industry partnerships. He is also entrusted with spearheading the marketing initiatives to establish a strong brand presence for Maveric.
