January is a time for thinking about the future.
And for most people, at this time of year, there are two familiar ways of doing that: predictions and resolutions.
Predictions tend to be more of a professional exercise. You look at the broad trends shaping your industry and come up with a set of specific guesses about what might happen over the next twelve months. Done well, predictions are calibrated to walk the line between obvious and bold. They are, fundamentally, observational in nature.
Resolutions are more personal. They’re an optimistic reflection of what you hope to accomplish in the coming year, calibrated to walk the line between motivating and realistic. They are, fundamentally, aspirational.
What’s interesting to me is that while both are extremely common, neither is very useful on its own.
For example, one popular resolution at this time of year (including for me) is to lose a little weight. But if I had to make a prediction relevant to my physical health, the safest and most accurate one would be that I will continue to cook and eat a lot of delicious, not-totally-healthy meals in 2026.
The two ideas aren’t incompatible, but they are in tension — and without a strategy to harmonize them, realism will almost always win out over optimism.
To solve for this, we need a third way of thinking about the future: priorities.
Think of a priority as a resolution, indexed to a prediction.
A priority acknowledges the facts on the ground while still pursuing a goal. Done well, priorities turn aspiration into strategy. A good example, for my personal health, might be something like this: cook whatever elaborate, unhealthy meals you want — but confine them to Saturdays and Sundays.
So here’s the plan for today’s essay.
First, I’ll lay out a set of predictions about banking and fintech in 2026. Then I’ll introduce a smaller set of personal resolutions for the industry. And finally, I’ll combine the two into ten priorities for the year ahead.
Predictions (What’s Likely to Happen)
To be useful here, predictions should describe momentum that’s already visible — not outcomes that require everything to go right.
The predictions below draw on my own views, a crowdsourced set of 2026 predictions from the Fintech Takes community, and a recent predictions piece from MX. What stood out wasn’t consensus on outcomes, but consensus on the forces shaping them.
Here’s what will shape banking and fintech in 2026:
1. Stablecoin adoption accelerates (unevenly).
Interest in and experimentation with stablecoins will continue to accelerate in 2026, building on momentum from 2025. The number of stablecoins in market will keep growing (one Fintech Takes reader predicted as many as 500 this year), even as real adoption remains concentrated rather than universal.
Growth will cluster around specific use cases — including cross-border remittances, corporate treasury, and developer infrastructure — rather than broad consumer payments.
Increasing regulatory clarity, particularly via the GENIUS Act and related crypto market structure efforts (which seem likely to get pushed through eventually, despite Coinbase’s obstinance), will provide a meaningful tailwind without resolving fragmentation or complexity.
2. AI adoption keeps expanding.
As MX notes in its predictions piece, AI has been THE trend in financial services for a while:
Today, artificial intelligence (AI) is everywhere in financial services — at least in promise. It leads every discussion about modernizing the industry, every industry conference agenda, and every strategic investment conversation. In fact, nearly 8 in 10 banking organizations report AI use in some capacity.
This will obviously continue in 2026.
The big AI labs will continue pouring outrageous amounts of money into improving foundation models and expanding usage. That pressure will force banks and fintechs to, at minimum, have a good-sounding answer to the question that all of their investors will ask: What is your AI strategy?
Most of those answers will be soundbites. Some will be more thoughtful, but still theoretical. And a small number of companies will make genuine progress in modernizing their data infrastructure and operationalizing LLMs to streamline workflows and empower employees and customers.
As MX notes in its predictions piece, the arc of AI adoption is long, but it bends towards customer value.
3. LLMs remain constrained in high-stakes decisions.
Despite rapid AI adoption, 2026 will not be the year banks or mainstream lenders hand over high-stakes customer decisions — especially credit decisions — to LLMs.
Institutions will experiment broadly with AI across workflows and support functions, but humans and traditional models will remain firmly in the loop when it comes to approving credit, setting limits, or pricing risk.
This isn’t a technical limitation so much as a governance one. Explainability, accountability, and liability still matter enormously in financial services, and today’s LLMs aren’t well-suited to shoulder that responsibility on their own.
Additionally, while financial service providers have a lot of valuable proprietary customer data, much of it was never collected, labeled, or governed with autonomous decision-making in mind. Messy, biased, and context-dependent data might be workable when humans are in the loop — but it becomes dangerous when decisions are delegated to systems that can’t explain, challenge, or correct themselves.
Significant improvements in data infrastructure and model and decision governance will need to be made before LLMs get anywhere near high-stakes customer decisions.
4. Agentic commerce hype outpaces real consumer demand.
If “AI” is the headline in 2026, “agentic AI” will be the subhead that refuses to go away.
The idea that LLM-powered agents can act semi-autonomously on behalf of customers has captured the imagination of builders across financial services — particularly those focused on payments and commerce enablement.
The enthusiasm, however, is far stronger on the supply side than the demand side. Agentic commerce often appears more compelling to platforms and payment providers than to consumers, who are already quite good at shopping on their own.
That mismatch won’t slow the hype cycle in 2026. But as agentic systems move closer to real-world deployment, they’ll increasingly collide with practical constraints around trust, agency, and accountability — and the gap between what’s easy to demo and what’s actually useful will become harder to ignore.
Instead of fully transforming financial lives, AI has largely delivered modest conveniences: quicker service responses, basic alerts, surface-level personalization, and chatbots that help around the edges but don’t meaningfully improve financial clarity or confidence. The result is a widening gap between what AI is supposed to unlock — better decisions, reduced stress, improved financial health, etc. — and what consumers actually experience.
5. U.S. open banking stalls (and Canada advances).
If you’re looking for regulatory clarity around open banking in the United States in the early parts of 2026, you’re likely to be disappointed.
The Personal Financial Data Right Rule (Section 1033) may remain stuck in limbo — challenged, delayed, or weakened enough to generate more uncertainty than guidance. Banks will continue pushing for cost recovery and risk limitations. Fintech companies will continue planning around ambiguity.
Meanwhile, Canada is overtaking the U.S. on open banking regulation. Here’s MX again:
In the past few months, Canada has moved ahead on implementing its open banking framework. Through the Consumer-Driven Banking Act (CDBA) and commitments reaffirmed in Budget 2025, the Canadian federal government has established both the legal foundation and a phased roadmap for Open Banking, including enabling secure “read access” in 2026, followed by a move toward “write access” in 2027. Framework oversight is also shifting to the Bank of Canada, signaling an emphasis on operational stability, risk management, and long-term infrastructure.
The regulatory gap between the U.S. and peer markets on open banking clarity is unlikely to close in 2026 — and may widen. Meanwhile, the performance and competitive gap between those who have invested and those who have not will continue to widen.
6. Credit scoring fragments faster than consumer understanding.
The credit scoring ecosystem will continue to fragment in 2026.
The end of FICO’s monopoly in conforming mortgages opened the door to more competition, and that competition is now accelerating — through new models, pricing structures, and distribution strategies.
This will be good for lenders. More choice generally leads to better models and lower costs.
For consumers, it will feel like the opposite. They’ll be exposed to more scores, more methodologies, and more definitions of creditworthiness — often without clarity on which ones actually matter. As the number of “scores” increases, the signal-to-noise ratio will get worse, not better.
7. Speculation becomes easier to package and scale.
Speculation isn’t going anywhere in 2026. It’s getting easier to package, distribute, and normalize.
Whether it’s crypto, zero-day options, or prediction markets, more companies will find ways to turn volatility into engagement. The lines between investing, hedging, betting, and entertainment will continue to blur.
Something in this ecosystem will almost certainly blow up. Something always does.
But the broader business model — selling access to speculative behavior, which, as Andrew Ross Sorkin reminds us in his excellent book 1929, is a model that has been around for a long time — will remain very much intact.
8. The “great wealth transfer” unfolds as a long transition.
I’m just going to shamelessly steal this one from MX:
For years, the “great wealth transfer” has been framed as a seismic financial event, a once-in-a-generation shift that will move unprecedented sums from older Americans to their heirs. Headlines often cite the same eye-catching number: an estimated $124 trillion expected to change hands by 2048. The dominant narrative says a tidal wave of assets is coming, and the financial industry must brace for dramatic disruption.
Those projections tell us about scale, but tell us little about timing. The reality is that longer lifespans, rising healthcare costs, estate planning choices, and shifting spending habits may eat into, or delay, that wealth transfer. At the same time, most wealth will shift within the older generations first, as spouses inherit before children or other heirs. Finally, it’s unlikely that we’ll see a mass event where older generations pass away and pass on their assets in a single year.
If we want a more accurate frame, the right word is transition, not transfer. What’s actually happening is a prolonged period in which people manage money in retirement for years or decades, while responsibility gradually shifts — sometimes intentionally, sometimes reactively — to spouses, children, or caregivers.
And this transition is unfolding in a more hostile environment. As MX notes in its predictions piece, financial lives are increasingly fragmented (MX research shows the average consumer has 5 to 7 financial accounts). And as identity authentication becomes better (one step forward!), fraudsters shift their focus to attacking the humans in the loop. Scams are becoming cheaper, more convincing, and harder to detect — especially as AI-powered social engineering improves (two giant steps back!)
The defining challenge for aging consumers in 2026 isn’t preparing for a sudden inheritance moment. It’s navigating a long stretch of complexity and vulnerability while trying to preserve independence and dignity.
9. Competition intensifies through simultaneous entry and exit.
Competition in banking and fintech will intensify in 2026 — not because the industry is fragmenting, but because it’s doing two things at once.
On the fintech side, VC enthusiasm has returned, especially for companies that can plausibly describe themselves using the words “AI” and/or “stablecoins.” That will drive a steady stream of new startups, products, and narratives. At the same time, regulators have effectively thrown the doors open on the banking side, enabling more de novo charters, more non-bank bank acquisitions, and more creative regulatory structures.
Alongside these new births, the industry will see a higher death rate. Banks and fintech companies that don’t build the capabilities to compete and win in digital channels (MX cites strong mobile banking and personalization capabilities as critical here) won’t survive. Consolidation through M&A will continue — with regulatory approval — and shorter runways plus less patient capital will lead to more acqui-hires and outright shutdowns.
The result won’t be less competition. It will be more dynamic competition: more motion at the edges of the market, and more consolidation in the middle.
10. Supervision loosens, confidence rises.
In 2026, supervision will feel noticeably more permissive — particularly around consumer protection.
That creates room to move. Some companies will use it thoughtfully. Others will move faster than they should. And many will mistake regulatory silence for regulatory approval.
This pattern is familiar. Periods of looseness tend to encourage behavior that looks defensible in the moment, questionable in hindsight, and indefensible once something breaks. The correction rarely comes immediately — but it almost always comes eventually (and may come sooner than folks think, if state banking regulators and attorneys general have anything to say about it).
The key difference in 2026 is confidence. After a year of uncertainty, companies are more likely to believe the room is real — and to act accordingly.
Resolutions (What I Want to Happen)
Predictions tell us what’s likely to happen. Resolutions tell us what we should be aiming for.
For the purposes of this exercise, we don’t need a long list of resolutions. We need a few bold statements of intent — principles about what matters if banking and fintech want to build durable value, not just chase momentum.
Resolutions are, of course, subjective. They’re a matter of taste. These are mine:
1.) Defeat financial nihilism. As I wrote at the end of last year, our most important job in 2026 is to give consumers hope — to help them believe that making good decisions still matters, rather than implicitly (or sometimes explicitly!) telling them the game is rigged and short-term speculation is the only rational response.
2.) Focus on long-term customer outcomes. Success shouldn’t be measured by engagement, conversion, or revenue alone. It should be measured by whether customers are actually better off — more resilient, more informed, and less stressed — over time. This is a sentiment that came up repeatedly in the Fintech Takes community’s crowdsourced predictions for 2026.
As usual, Jane Barratt, Chief Advocacy Officer at MX, puts it best:
If your business model focuses primarily on value extraction rather than delivering value to customers, you’re missing the mark. The financial services industry has a huge opportunity and responsibility to help customers better understand their finances, manage their money, and build financial strength. This isn’t just good for them, it’s good for the businesses that serve them too — directly translating into increased customer loyalty, engagement, and asset and revenue growth for financial providers.
3.) Build companies that will last. Optimize for durability, not just growth. That means durable unit economics, thoughtful risk management, and products designed to survive multiple market and regulatory cycles — not just the next funding round.
4.) Leave the ecosystem better than you found it. Building in financial services is a privilege, made possible by the decisions of those who came before us and the trust those decisions earned from customers. Don’t take shortcuts or externalize risk to customers, partners, or regulators. Find opportunities to collaborate for mutual benefit.
5.) Do not lose to Canada. If they can do open banking with clarity and coordination, so can we!
Priorities (What We Can Make Happen)
Predictions tell us what’s likely to happen. Resolutions tell us what we want to happen.
On their own, neither is enough.
Predictions without resolutions turn into excuses — reasons to accept outcomes we don’t actually like. Resolutions without predictions turn into wishful thinking — aspirations untethered from reality.
A priority is what you get when you combine the two.
Each priority below takes one or more predictions as a given, anchors them to one or more of the resolutions above, and translates that combination into a concrete area of focus for 2026.
They’re not guarantees. They’re not silver bullets. They’re bets about where effort is most justified, even when the odds are uncertain.
With that in mind, here are my priorities for banking and fintech in 2026:
1. Sustain open banking progress without regulatory clarity.
Predictions: U.S. open banking stalls (and Canada advances).
Resolutions: Leave the ecosystem better than you found it. | Do not lose to Canada.
Regulatory clarity is unlikely to arrive in the U.S. open banking market in 2026. But that doesn’t mean progress has to stop.
Even under a much more proactive and well-staffed CFPB, there were always limits to what rulemaking alone could accomplish. Section 1033 of Dodd-Frank simply isn’t very detailed or prescriptive. And now, in a post-Chevron world, any attempt by regulators to stretch beyond the statute is almost guaranteed to invite immediate legal challenges.
The reality is that many of the hardest problems in open banking — technical integration, information security, liability allocation, third-party risk management — can’t be solved by regulation alone anyway. They require cooperation between private companies on all sides of the market. Much of that work has already been happening, piece by piece, through bilateral commercial agreements and industry standard-setting efforts like the Financial Data Exchange (FDX).
Right now, tensions in the open banking ecosystem are high, and trust is in short supply. But as the business benefits of open banking become even more apparent — especially to banks — the incentives to cooperate will grow. That cooperation may be reluctant, uneven, and occasionally combative, but it’ll still be progress.
Keeping the ball moving in 2026 matters because it puts the industry in a far stronger position when the regulatory logjam inevitably breaks. The goal isn’t to wait for permission. It’s to be ready. As MX says in its piece:
… the demand for Open Banking is unmistakable: consumers are asking for more control over their financial data, and institutions want to modernize, reduce friction, and replace legacy data access methods with secure, API-based connectivity. Market momentum hasn’t slowed — it’s simply waiting for regulatory alignment. The winners will be the financial institutions that use this moment to modernize their data infrastructure, invest in secure APIs, and be ready to scale the moment regulatory alignment arrives.
Also, I would really prefer not to spend the next few years having my Canadian readers explain to me why their system works better than ours.
2. Invest early in AI governance and model risk management.
Predictions: LLMs remain constrained in high-stakes decisions. | Supervision loosens, confidence rises.
Resolutions: Build companies that will last.
Because AI adoption is accelerating faster than regulatory scrutiny, companies have a narrow window to invest before the stakes rise.
Right now, regulators are more focused on encouraging innovation than reining in excesses (not a criticism — just an observation). Fair lending and model risk management don’t feel urgent. And, for the most part, LLMs still aren’t being used to make high-stakes customer decisions directly.
That combination makes this the perfect time to invest.
Companies that wait until regulators care — or until AI systems are already embedded in customer-facing decisions — will find themselves scrambling. Retrofitting governance, explainability, and fairness onto systems that are already in production is expensive, disruptive, and often ineffective.
By contrast, companies that invest early in model risk management, data lineage, explainability, and fairness testing will build real internal muscle memory. They’ll understand where AI helps, where it doesn’t, and where humans need to stay firmly in the loop.
Investing countercyclically feels unintuitive in the moment. In hindsight, it’s what separates durable institutions from cautionary tales.
3. Make stablecoin-powered money visible and legible.
Predictions: Stablecoin adoption accelerates (unevenly).
Resolutions: Defeat financial nihilism.
When money becomes harder to see, trust erodes.
As stablecoins increasingly sit underneath consumer-facing financial products — especially in BaaS, embedded finance, and global money movement — users will often have no idea what rails their money is actually running on.
If money is spread across accounts powered by different technologies, issuers, and settlement systems, consumers lose the ability to see their full financial picture clearly. And when people can’t see or understand where their money is, nihilism sets in fast.
We’ve been here before. Open banking data aggregation helped restore coherence in a fragmented account landscape by giving consumers a unified view, even when the underlying infrastructure was messy.
That same functionality needs to be extended to stablecoins.
Practically speaking, that means aggregation, transparency, and standardized, permissioned access to account and transaction data (starting with read-only access, given the irreversibility of most crypto transactions).
If stablecoins are going to play a meaningful role in everyday finance, they need to make money systems feel more navigable, not less.
4. Build responsible consumer risk management tools.
Predictions: Speculation becomes easier to package and scale.
Resolutions: Defeat financial nihilism. | Focus on long-term customer outcomes.
If speculation is going to keep expanding — and it is — then ignoring it or scolding consumers for participating isn’t a strategy.
What is worth taking seriously is the motivation behind the behavior. Many consumers aren’t chasing excitement so much as trying to cope with uncertainty: volatile markets, unstable income, rising housing costs, and a general sense that the financial ground keeps shifting beneath them.
Betting on a football game or Time’s Person of the Year isn’t an effective hedge. But the underlying motivation is rational. The failure isn’t on the consumer side — it’s that we’ve given them very few responsible tools to manage risk in the first place.
We now have more primitives than ever to work with: real-time cash-flow data, AI, innovative insurance products like payment protection insurance, and yes, even prediction markets. Used thoughtfully, these tools can be combined into consumer-facing risk management experiences that reduce fragility rather than amplify it (I walked through one hypothetical example, focused on housing risk, here).
If we don’t build and market these products intentionally, someone else will build and market worse versions of them. And those versions will almost certainly reinforce the idea that the only rational response to uncertainty is to gamble.
5. Normalize self-exclusion in financial products.
Predictions: Speculation becomes easier to package and scale.
Resolutions: Defeat financial nihilism.
If speculative financial products are going to be widely available, consumers should have better tools to protect themselves from their own worst impulses.
Self-exclusion is a well-tested concept in gaming. People can proactively set limits, lock themselves out, or require cooling-off periods — especially when they know their future judgment may be worse than their present judgment. Financial services should have adopted this approach years ago.
Some banks already have. In the UK, many institutions offer ‘gambling blocks’ that let customers voluntarily block gambling transactions. In the U.S. — where mainstream access to gambling is newer — banks largely haven’t taken this step.
They should. And they should extend the same logic beyond cards to ACH transfers, wires, and real-time payments flowing to speculative platforms. Why shouldn’t a consumer be able to say, in advance, “Don’t let me send money to Robinhood, Coinbase, Kalshi, or DraftKings after midnight,” or “Require a 24-hour delay before I can move funds into this account”?
As speculative platforms increasingly go after direct deposits, this may soon stop being just a consumer issue and start becoming an employer one as well (Chime’s Enterprise division might want to kick the tires here).
If we’re serious about helping people make better financial decisions over time, giving them tools to pre-commit — and to protect themselves in moments of weakness — is an obvious place to start.
6. Make internal scoring models legible to customers.
Predictions: Credit scoring fragments faster than consumer understanding.
Resolutions: Defeat financial nihilism. | Leave the ecosystem better than you found it.
As credit scoring fragments, consumers are increasingly unsure which signals actually matter — and that confusion breeds cynicism.
The old promise — “this is your credit score, and here’s how to improve it” — no longer holds. There is no single, universal answer anymore. Pretending otherwise only deepens the sense that the system is arbitrary and rigged.
You can’t solve this problem for the entire ecosystem. But you can solve it within your own walls.
Cash App has shown the way. By exposing its internal scoring logic, explaining what behaviors matter, and showing customers how their actions translate into outcomes, it replaces mystery with legibility. That clarity builds trust and gives customers a sense that the system is navigable, not capricious.
Opacity feeds financial nihilism. Transparency fights it. Making internal models customer-facing won’t just reduce confusion — it creates better engagement, more informed cross-sell, and stronger long-term relationships.
And, the value of transparency extends beyond just credit scoring. Consumers are overwhelmed by multiple financial accounts at multiple providers, unclear transaction data, and a constant stream of generalized information about how they should manage their finances. They want a financial partner that helps them make sense of the noise and then actually do something. This is exactly the environment where clean transaction data and consistent categorization — something MX has long focused on — becomes a prerequisite for meaningful guidance, not just noise.
7. Use agentic AI to optimize consumer savings outcomes.
Predictions: Agentic commerce hype outpaces real consumer demand.
Resolutions: Focus on long-term customer outcomes.
If agentic AI is going to matter for consumers, it shouldn’t start with spending.
What people actually struggle with isn’t finding new ways to transact — it’s saving consistently and ensuring their savings compound as much as possible over time. Inertia, not intent, is the real enemy.
This is where agentic AI could deliver genuine value. A well-designed savings optimizer could continuously monitor cash flow, balances, rates, and constraints, and help consumers maximize yield without constant manual intervention. Not by taking full control (at least not yet), but by removing friction, surfacing tradeoffs, and nudging money toward its most productive place.
We already know the upside is real. Small improvements in yield compound meaningfully over time, especially for households living close to the margin. Yet most consumers leave real money on the table simply because optimization is tedious.
It’s not obvious that banks or fintechs are best positioned to build this. It may come from a company with different incentives and distribution — a Credit Karma or Apple or Walmart.
If agentic AI is going to justify its hype, perhaps we should start by helping people earn more on the money they already have.
8. Shift loyalty from products to relationships.
Predictions: Competition intensifies through simultaneous entry and exit.
Resolutions: Build companies that will last.
In industries that have already become highly competitive, we can see what winning looks like. Airlines are the clearest example.
Loyalty programs like SkyMiles don’t just reward transactions — they reward relationships. They create gravity. They align incentives across the business and make the best customers feel known and valued.
Banking is now entering a similar phase. Switching costs are falling. New entrants keep showing up. Distribution advantages that once felt permanent are eroding.
Banks should be well-positioned to respond. They sit on decades-long customer relationships, rich behavioral data, and frequent touchpoints across a customer’s financial life.
But much of that advantage is trapped. Legacy core systems, fragmented data architectures, and product-centric operating models make it hard to see customers holistically — let alone reward them consistently across products. Data that could power relationship-based loyalty is siloed, stale, or operationally inaccessible.
So the constraint isn’t just urgency. It’s also translation.
In a louder, more competitive environment, durable winners will be the institutions that break out of product silos and use their data to recognize, reward, and deepen relationships over time. Loyalty won’t come from any single product feature. It will come from making customers feel understood — and making that understanding economically meaningful.
9. Design multi-player banking for aging households.
Predictions: The “great wealth transfer” unfolds as a long transition.
Resolutions: Focus on long-term customer outcomes.
Most financial products are still designed for a single user making decisions in isolation. That model breaks down quickly as people age.
What’s far more common in real life is a gradual transition: adult children helping parents manage bills, monitor accounts, avoid scams, and make sense of increasingly complex financial decisions — often informally, often under stress, and often without the right tools.
Today, families are forced to hack together solutions using shared passwords, ad-hoc account access, or full legal instruments like powers of attorney that are either too blunt or too late. None of that reflects how financial responsibility actually shifts over time.
The opportunity here isn’t capturing a future inheritance. It’s building trust during a long transition — by enabling shared visibility, graduated permissions, alerts, and safeguards that preserve independence while reducing risk.
Products that solve these coordination problems won’t just serve aging parents better. They’ll earn the trust of the next generation, too. And that’s what durable, outcome-oriented banking relationships actually look like.
(Editor’s Note — I wrote, in a lot more depth, about the importance of life stage-based product design in a different sponsored deep dive essay with MX, which you can read here.)
10. Reintroduce place into digital financial products.
Predictions: Competition intensifies through simultaneous entry and exit.
Resolutions: Defeat financial nihilism. | Build companies that will last.
As financial products become more centralized and interchangeable, they also become easier to distrust.
One promising countertrend is the reintroduction of place into digital finance.
Companies like Bilt and Block are experimenting with ways to embed local geography, merchants, and communities into financial products — not as nostalgia, but as a way to create relevance, loyalty, and real-world utility. These efforts recognize something important: people don’t experience their financial lives in the abstract. They experience them where they live.
For community banks in particular, this should be a wake-up call. As consolidation accelerates, “local” can’t just be a slogan or a branch footprint. It has to show up in product — through local rewards, partnerships, data, and networks that reflect how money actually moves within a neighborhood.
Done well, neighborhood-scale financial networks create positive feedback loops: stronger local economies, deeper customer loyalty, and a clearer sense that participating in the financial system actually benefits the places people care about.
Choosing Where to Push
Predictions force us to confront reality. Resolutions remind us what we care about. But neither, on their own, tells us where to apply effort to bring about the future we want.
That’s what priorities are for.
None of the priorities in this essay are guaranteed to succeed. Some will prove harder than expected. A few may turn out to be wrong. That’s fine. The goal isn’t to predict the future perfectly — it’s to be intentional about how we respond to it.
Many of the forces shaping banking and fintech in 2026 — fragmentation, speculation, abstraction, consolidation — can either deepen cynicism or motivate better design. The difference isn’t the trend itself. It’s how we choose to engage with it.
If we want consumers to believe that good decisions still matter, we have to build systems that reward those decisions. If we want long-term growth and durable companies, we have to resist optimizing only for the moment. And if we want to be proud of what this industry produces, we have to take responsibility for the second- and third-order effects of the products we ship.
2026 will bring plenty of noise. These priorities are my attempt to identify the signals worth acting on anyway.
Let’s see how we do.
About Sponsored Deep Dives
Sponsored Deep Dives are essays sponsored by a very-carefully-curated list of companies (selected by me), in which I write about topics of mutual interest to me, the sponsoring company, and (most importantly) you, the audience. If you have any questions or feedback on these sponsored deep dives, please DM me on Twitter or LinkedIn.
Today’s Sponsored Deep Dive was brought to you by MX.
MX helps financial providers connect, analyze, engage with, and act on consumer-permissioned data to drive growth and create better experiences.
