The ‘Letter from the Editor’ series features exclusive insight and opinion-driven analysis from Tearsheet editor Sara Khairi.The focus is on linking ideas, questioning assumptions, and tracking shifts across both mature and emerging trends in financial services.
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Issue # 12
Does revenue double while costs, headcount, and operational complexity rise with it? Or does the business actually get better as it gets bigger, more data to work with, more automation, better risk decisions, lower unit costs, and deeper customer integration?
I think that’s becoming a more useful way to think about fintech moats. I’m now looking for defensibility in operating leverage: the ability to grow more customers, transactions, and complexity without absorbing the same amount of cost.
This story lives in reconciliation, fraud controls, underwriting, routing, settlement, data infrastructure, and the workflows nobody puts on a product launch page. The new fintech moat is “boring,” and boring is what actually makes it durable. Let’s unpack how.
The numbers are telling us the same
The industry’s financial performance is increasingly rewarding operating leverage alongside growth. BCG and QED Investors’ 2026 fintech research found that global fintech revenue reached $504 billion in 2025, growing 22%, while 74% of the largest public fintechs were profitable and average EBITDA margins rose 400 basis points to 20%. The industry is moving toward profitable scale, with technology increasingly being judged by the economics it creates rather than simply the growth it enables.
So, what happens to your economics when you grow?
Adyen offers a good example. In 2025, its processed volume grew 21%, excluding a large-volume customer, while net revenue grew 18% and operating expenses rose just 13%. EBITDA increased 26%, pushing its margin to 53% from 50% a year earlier. Adyen attributed the expansion to the scalability of its single platform and the operating leverage it creates as the business grows.
If a fintech adds customers and volume but has to add people, systems, and operating expense at roughly the same pace, scale doesn’t create much of a moat. On the other hand, if more volume makes the data better, automation more effective, and unit economics stronger, scale starts to compound.
The ‘Letter from the Editor’ series features exclusive insight and opinion-driven analysis from Tearsheet editor Sara Khairi.The focus is on linking ideas, questioning assumptions, and tracking shifts across both mature and emerging trends in financial services.
This is now PRO-only content. Subscribe to PRO so you never miss a Letter from the Editor exclusive.
Issue # 11
Financial services is an industry built around knowledge, language, and decision-making. If any industry was ready for AI and generative AI, surely it was banking. So, companies moved quickly. They announced partnerships with OpenAI. They rolled out ChatGPT Enterprise. They built ChatGPT-like AI assistants. And gave employees access to large language models.
But two years into this experiment, the industry is now asking: What needs to be in place around AI before we can actually trust it?
The beginning of it all: The ChatGPT timeline
2023: “We have ChatGPT”
In 2023, the focus was access. Financial institutions rushed to experiment with the tech after ChatGPT demonstrated something that felt almost impossible at the time: a machine capable of understanding and generating human-like language.
The first wave was about discovery. The excitement was understandable, but it also created unrealistic expectations. Because the assumption was that if AI could understand language, it could eventually understand finance, which isn’t exactly true.
2024: “We have AI copilots”
In 2024, the industry’s language started changing. The idea of AI replacing workers became less prominent. The idea of AI assisting workers became more realistic.
Morgan Stanley’s OpenAI partnership became one of the most visible examples. The firm integrated GPT-4 into tools designed to help financial advisors search through its research and access information more efficiently.
The interesting part was what the model was not asked to do. It was not managing client relationships. It was not making investment decisions. It was not replacing financial judgment. It was just helping advisors spend less time searching and more time advising. The technology became valuable when it supported expertise, not when it attempted to replace it.
Around the same time, banks and fintechs across the industry began launching their own ChatGPT-like assistants, copilots, and enterprise LLM deployments, first for employees, then for customers, to search information, draft content, answer questions, and streamline everyday work.
Again, the biggest opportunity was removing friction from everyday work. Finding information, drafting documents, helping employees move faster. In general, the most successful AI implementations were asking LLMs to make the bank work better.
2025/2026: “We need governance, data and ROI”
By late 2025 and into 2026, the conversation had shifted again. Institutions began building AI agents designed to execute specific financial tasks like underwriting, compliance, servicing, and other financial workflows on top of proprietary data.
As the AI novelty disappeared, the industry then moved from experimentation to accountability. Investors became less interested in hearing that companies had AI initiatives; they wanted evidence around productivity gains and revenue opportunities.
Those points exposed a reality that was easy to overlook during the excitement. The model was never the hardest part.
Introducing our new ‘Letter from the Editor’ series featuring exclusive insight and opinion-driven analysis from Tearsheet editor Sara Khairi.The focus is to link ideas, question assumptions, and track shifts across both mature and emerging trends in financial services.
This will soon be PRO-exclusive content. Subscribe to PRO so you don’t miss out on future exclusives.
Issue # 5
Fintech is moving beyond the interface wars.
Competition has been traditionally defined by visibility; building the app consumers opened more often, the experience that felt smoother, the financial product that looked less like a bank and more like software.
That model created some of the most important companies of the last generation. But it also trained the industry to think the interface was the business.
That is becoming less true by the day.
Value is shifting underneath the surface, into infrastructure: APIs, orchestration systems, settlement layers, compliance engines, treasury coordination, embedded banking capabilities. Increasingly, the most powerful companies are the ones other systems rely on.
Stripe’s relevance comes from how deeply it’s embedded inside the operating systems of digital businesses. Plaid matters less as a consumer connectivity tool and more as a financial data layer sitting underneath thousands of workflows. Circle’s significance is not really about crypto branding anymore; it’s about whether stablecoin settlement becomes infrastructure for internet-native money movement. Modern Treasury is solving a problem most consumers never see at all, which is the fragmentation between banking systems that still do not move coherently in real time.
Even Banking-as-a-Service has moved beyond its original form. At its most mature, BaaS has become more about making regulated financial capabilities available as infrastructure that software companies can build directly into their operations.
Increasingly, these companies are competing for the same place in the stack: the infrastructure layer beneath financial services. The first era of fintech was about access. The second was about user experience. This next phase is about system dependency.
Financial products are merging into processes. Payments now happen inside software workflows. Lending decisions originate within accounting platforms. Compliance increasingly operates as code. Treasury is becoming orchestration, and banking is evolving from a standalone relationship into an embedded capability.
The interface does not disappear entirely, but it stops being where the real strategic value sits.
We still talk about embedded finance, stablecoins, APIs, and AI automation as if they are separate developments. In reality, they are all part of the same shift. Finance is moving out of standalone products and becoming embedded within the software systems where people already work and transact.
That shifts the balance of power. Fintech assumed owning the customer experience was the ultimate advantage. But infrastructure plays by different rules, accumulating leverage in ways interfaces rarely can.
Interfaces compete for attention, while infrastructure competes for dependency.
Once financial infrastructure becomes woven into everyday workflows, replacing it becomes operationally painful, even if end users barely notice it exists. That is what makes infrastructure businesses so durable. Their value grows through dependence instead of visibility. The better they work, the more invisible they become, and the harder they are to replace.
That is why many fintech companies that once sold disruption are now building operational layers. Underneath that evolution is a deeper shift in how financial decisions get made. What was once a visible user action is increasingly becoming a system-driven outcome shaped by APIs, risk models, permissions, and embedded logic operating behind the scenes.
The key question is no longer who owns the customer relationship. Increasingly, the more important questions are:
Who defines the conditions under which financial activity happens in the first place?
Who controls identity verification inside workflows?
Who controls settlement?
Who controls compliance logic?
Who controls how money moves between platforms?
Who becomes the orchestration layer everything else plugs into?
This also explains why fintech firms are starting to look more like infrastructure providers than consumer brands, prioritizing integration over interfaces and system positioning over product differentiation.
This transition also carries a trade-off that deserves more scrutiny than it currently gets.
Infrastructure centralizes power. The more finance disappears into systems, the harder it becomes to see where decisions are being made, who is making them, and how much autonomy users are actually giving up in exchange for efficiency.
That does not necessarily make the shift or automation wrong. It is, in many ways, inevitable. Financial systems were going to become more programmable, more embedded, and more automated with emerging tech. But it does allude to the fact that innovation won’t be the sole focus of fintech’s next phase; governance will be just as defining.
Financial evolution has always involved the same trade-offs: efficiency versus clarity, automation versus control, abstraction versus understanding. What has changed now is how deep we are into that trajectory. This is why the key question in fintech today is who is capturing the rails, because everything else builds on that foundation.
– Sara
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Somewhere in the meaty space between IR, PR, and investment research falls DearCEO. The site is essentially an investor and corporate management network that allows investors to submit questions about a stock to corporate management and then provides a mechanism for management to respond.
