Hey, fintech fam 💜

Officially getting back into the New York groove after a packed week in Orlando covering FIS Emerald.

The conference theme this year was “velocity,” but underneath the AI announcements and keynote demos, a much bigger shift is happening across banking and fintech infrastructure.

The conversation is no longer just about who has AI.

It’s about who controls the orchestration layer powering it.

Last week, FIS announced a major partnership with Anthropic to build AI agents for financial institutions, regional banks openly discussed operational AI deployment, and executives across the conference repeatedly returned to the same challenge: fragmented systems can’t support intelligent banking.

Also, before we jump in:

Let’s get into it.

#TRENDING

Every Thursday, I break down the fintech stories that matter most — grounded in my reporting, interviews with industry leaders, and what I’m seeing unfold across the industry.

The biggest takeaway from FIS Emerald last week wasn’t simply that AI is coming to banking.

Everyone already knows that.

The bigger story is that banking’s next competitive advantage may not be AI itself. It may be orchestration.

Throughout the conference, executives repeatedly returned to the same challenge: financial institutions still operate across fragmented systems, disconnected data environments, and siloed infrastructure that were never designed to communicate with each other in real time.

As FIS CEO and President Stephanie Ferris put it during the opening keynote:

“If your data doesn’t talk, your AI can’t think.”

That line captured the core theme of the week.

FIS used Emerald to formally position itself as the infrastructure layer connecting those systems together.

Then the company solidified its position by announcing a new strategic partnership with Anthropic to build AI agents for financial institutions, starting with financial crime and anti-money-laundering workflows. The broader vision is much bigger: building what FIS repeatedly called “orchestrated intelligence.”

The distinction matters.

The conversation in fintech has largely focused on AI interfaces over the past two years — chatbots, copilots, customer-facing assistants, and generative experiences.

But Emerald made it clear that many banking executives now view infrastructure and orchestration as the harder problem.

AI models are becoming more accessible.

Connected systems are not.

That’s especially important in highly regulated environments where trust, auditability, governance, and explainability matter just as much as speed.

Several executives described a future where AI agents are not simply assisting employees, but actively coordinating financial workflows across deposits, lending, fraud detection, customer servicing, and payments infrastructure.

But those systems only work if the underlying data can move together in real time.

That’s why FIS kept emphasizing orchestration over automation.

As Ferris said during the keynote:

“The future isn’t artificial intelligence. It’s orchestrated intelligence.”

The company also repeatedly framed regulation and trust as advantages rather than constraints — a notable shift from how fintech discussed compliance during the last decade.

In an increasingly agentic financial system, banks may actually benefit from being highly regulated institutions with auditable infrastructure and traceable decision-making systems.

As one executive on stage put it:

“Speed without trust is a liability.”

Banking’s AI race is starting to look less like a battle over interfaces and more like a battle over infrastructure.

The institutions that control orchestration, interoperability, data flows, and trusted infrastructure will ultimately hold more long-term power than the companies building standalone AI tools on top.

That’s a major shift for fintech.

Infrastructure companies that many viewed as “legacy” players are suddenly becoming strategically important again because AI systems are only as useful as the environments they can operate inside.

And in banking, fragmented systems remain one of the biggest bottlenecks to deploying AI at scale.

One of the more surprising themes at Emerald was how aggressively regional and community banks are already moving on AI adoption.

For years, the assumption across fintech has been that the largest banks would dominate AI deployment because of their budgets, engineering resources, and data advantages.

But many of the conversations happening at Emerald suggested something more nuanced is emerging.

Smaller and mid-sized financial institutions increasingly see AI as a way to reduce operational disadvantages that historically favored large banks.

That includes:

• fraud monitoring
• compliance operations
• customer servicing
• underwriting workflows
• onboarding
• personalization
• back-office operations

Several banks participating in FIS pilot programs described AI less as a futuristic experiment and more as an operational necessity.

Amalgamated Bank discussed how it has spent the past two years building out its data infrastructure specifically in preparation for AI deployment across business units.

FirstBank Puerto Rico described how combining fragmented data systems is already helping the institution compete more effectively in credit card and customer engagement strategies.

And FIS executives repeatedly emphasized that sophisticated AI infrastructure should not be limited to trillion-dollar institutions.

As Melissa Cullen, SVP of Regional & Community Banking at FIS, put it:

“The sophistication of solutions should never be determined by your asset size.”

That framing came up repeatedly throughout the conference.

Several executives described AI as a potential equalizer for regional and community banks because operational leverage becomes more accessible when infrastructure is standardized, and AI tools become embedded directly into banking workflows.

In practice, that could allow smaller institutions to compete with much larger players without needing to build enormous in-house engineering organizations.

The conversation also reflected a broader shift happening across fintech right now:

AI adoption is moving from experimentation into operational deployment.

Not someday.

Now.

That transition is especially visible in areas like AML investigations, fraud operations, customer support, and workflow automation, where banks are under pressure to improve efficiency while maintaining compliance standards.

For years, fintech narratives centered around the idea that technology would primarily advantage the largest institutions with the biggest balance sheets.

AI may partially disrupt that assumption.

If infrastructure providers can successfully democratize access to sophisticated AI tooling, regional and community banks could become much more technologically competitive than many people expect.

That matters because smaller banks still play a massive role across lending, small business financing, and local economic activity throughout the United States.

And increasingly, many of them no longer want to be viewed as technology laggards.

They want enterprise-grade infrastructure with community-bank agility.

That combination could become far more powerful over the next several years.

One of the smartest observations I heard repeatedly throughout Emerald was surprisingly simple:

Many financial systems were never designed to talk to each other.

That problem is now colliding directly with the rise of AI.

Across interviews with FIS executives and banking leaders, one theme kept resurfacing: AI is only as useful as the systems it can access.

The challenge is that most financial institutions still operate across fragmented infrastructure environments built over decades through mergers, acquisitions, legacy cores, third-party vendors, and disconnected workflows.

That creates a major orchestration problem.

Hashim Toussaint, who recently transitioned into a leadership role focused on ecosystem banking and commerce infrastructure at FIS, described much of the company’s current work as building “the plumbing” required to make AI systems function effectively at scale.

That includes:

• integrations
• interoperability
• data accessibility
• API connectivity
• ecosystem infrastructure
• real-time system communication

The reason this matters is because the next generation of AI systems will increasingly rely on coordinated workflows across multiple financial products and platforms simultaneously.

An AI agent handling fraud detection may need access to:
• payments systems
• transaction histories
• onboarding data
• customer servicing records
• compliance workflows
• external identity systems

If those systems cannot communicate cleanly, AI becomes fragmented very quickly.

Several executives also emphasized that personalization may become one of the biggest unlocks in financial services over the next decade.

But personalization at scale requires connected infrastructure.

As Toussaint explained, the industry may not yet fully understand the limits of what real-time personalization can become once AI systems can coordinate data, products, and workflows across banking ecosystems in real time.

That future looks very different from the static banking experiences consumers are used to today.

The next phase of fintech may belong less to companies building flashy AI interfaces and more to the firms connecting fragmented financial systems underneath them.

That’s a major infrastructure opportunity.

Over the past decade, fintech has focused heavily on front-end disruption and customer experience.

The next decade may focus far more heavily on orchestration, interoperability, and system coordination behind the scenes.

Because ultimately, AI systems are only as intelligent as the infrastructure environments they operate inside.

And right now, connectivity remains one of the financial industry’s biggest unsolved problems.

Let’s keep you booked and busy. Every Thursday, I share fintech events worth adding to your calendar— both IRL and online.

The Fintech + Insurtech Generations Conference is happening June 10 as part of Charlotte Fintech Week (June 8–12), bringing together leaders across banking, fintech, insurance, and financial infrastructure.

Charlotte continues to quietly build one of the strongest fintech ecosystems in the country, especially across banking infrastructure and enterprise fintech.

Definitely worth checking out if you’ll be nearby.

After the energy of FTW: NYC, we’re officially headed west.

FTW: SF is coming September 29 - October 1, and we’re already deep in planning mode.

If NYC showed us anything, it’s that the fintech industry is craving real community again — not just panels and pitch stages, but actual conversations between operators, builders, banks, fintechs, and infrastructure leaders shaping what comes next.

Grab your early bird passes now…

One of my favorite parts of building Fintech Is Femme has been watching The Academy of Fintech community grow into such an incredible network of operators, founders, executives, and emerging leaders across the industry.

This photo is from one of my favorite recent moments with Academy members and sponsors at the Fintech Is Femme Leadership Summit ✨

What makes this community special is the people inside it.

Leaders from J.P. Morgan, Amex, Prove, and many more are already part of the network — sharing ideas, making introductions, supporting each other, and helping shape the future of fintech together.

Inside The Academy, members get:
• semi-monthly virtual events
• curated networking opportunities
• direct access to me and the Fintech Is Femme team
• leadership conversations with top operators across fintech
• and a trusted community of people genuinely invested in helping each other grow

If that sounds like your kind of fintech community, we’d love to have you.

Throwing it back to this classic because honestly… it’s been the soundtrack of everyone’s life lately: work work work work work 💻✨

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That wraps up today’s edition—thanks for reading! Until next week, keep innovating and challenging the status quo.

See you Tuesday!

Love,

Nicole 💜