The Machinery of Modern Finance
“The curious task of economics is to demonstrate to men how little they really know about what they imagine they can design.”
- Friedrich Hayek
Shortly after markets opened on January 28th, 2021, Vlad Tenev went on television to explain why millions of customers could no longer buy a handful of stocks that, until that week, most of Wall Street had barely noticed.
Robinhood had restricted purchases of GameStop, AMC, and several other heavily shorted names just as retail demand peaked. The explanation required an understanding of financial plumbing, something most Robinhood customers did not have.
While accounts were still funded and orders were still matching, the clearing requirements had increased and margin had to be posted. In response, Robinhood was scrambling to raise billions of dollars in emergency capital.
The explanation made little sense because (it seemed) trades were still executed and positions updated in real time. Why would buying a stock require billions in emergency financing after the fact?
The answer sat several layers beneath Robinhood itself in settlement infrastructure. Every trade executed on Robinhood was cleared through DTCC infrastructure and settled on delayed cycles. As volatility spiked, clearinghouses were recalculating risk in real time and demanding additional margin from brokers standing between buyers and sellers.
While Robinhood made markets easier to access and faster to interact with, it had not changed how value ultimately settled, how risk was absorbed, or who stood between a transaction when conditions deteriorated.
The same pattern had repeated across fintech for over a decade. Modern interfaces had been layered on top of infrastructure that remained largely unchanged since the mid-twentieth century.
This piece is an attempt to trace how financial infrastructure evolved and why successive waves of innovation changed how markets were accessed more than how they ultimately functioned. It also explores why the conditions now exist to address those foundations directly, opening meaningful room to redesign financial systems that are simpler, more resilient, and more global by default.
Preface
A brief note to the reader: this essay is written for a broad audience and covers foundational material in traditional finance, fintech, and crypto. Practitioners may wish to skip through sections where they have domain expertise.
It is the synthesis of, on one hand, time spent investing in and building within the industry and, on the other, a deep skepticism toward the narrative fervor that tends to surround crypto innovation. Much of what we call explanation is narrative built after the fact.
Part One (attempts to) explain why financial systems work the way they do. Part Two argues that the constraints they were built around are beginning to lift. It draws on experience, conversations, reading, building, watching, and learning, largely as a byproduct of trying to understand things well enough to operate within them.
Financial systems are path dependent, complex, and occasionally irrational, but they are also essential to economic prosperity. They change slowly (see part one) until they do not (see part two). We appear to be entering a period where some of the constraints that shaped their design are beginning to lift, creating room to rethink how these systems operate and settle.
As for why I wrote it at all: my interest in markets predates my career. My father, an immigrant who came to the United States in his late twenties for a nephrology fellowship at Jersey City Hospital, took to markets and spent much of his free time talking to me about them. The evolution and functionality of financial “machinery” has always fascinated me. Writing this was mostly a “Saturday project” for my own entertainment. I hope you find some of it informative, diverting, or at the very least a tolerable weekend read.
Finally, on process: if I commit to reading a long-form essay nowadays, there’s a quiet voice in the back of my head questioning whether it was written (by a human) or generated (by AI). If the latter, I close the tab. I’d rather talk to the model myself. Human-written prose offers readers something LLMs have yet to achieve (a window into another person’s mind).
I think the act of writing each word is the best way to organize thought. I wrote this piece without LLM assistance for sentence structure. I used Opus 4.6 and ChatGPT 5.2 as research assistants and, sparingly, as editors. Napkin.ai helped with visuals. Interviews and press releases were pulled largely from memory.
Part One
I. Why Financial Systems Work the Way They Do
Modern financial services are the centuries-long culmination of responses to a small number of persistent coordination problems:
How value moves across distance
How obligations settle over time
How counterparty risk is managed
How trust is enforced at scale among parties who do not know one another
Every major financial institution or piece of infrastructure that exists today can be traced back to an attempt to solve one or more of these problems, while often introducing new constraints or tradeoffs that successive generations of entrepreneurs and regulators were forced to navigate.
Coordination at Small Scale
Early financial systems relied on three factors: 1) proximity, 2) reputation, and 3) force. In medieval Europe, long-distance trade was organized around merchant fairs such as the Champagne Fairs of the 12th and 13th centuries.
Traders from Northern Italy, Flanders, and France gathered at fixed times and places to exchange goods and settle accounts. Credit was extended primarily within known merchant families or guilds, with enforcement relying on reputation and exclusion rather than formal legal systems. A merchant who defaulted risked being barred from future fairs or cut off from trade networks altogether. Settlement occurred in person, typically in coin, because once merchants dispersed there was no trusted mechanism to resolve disputes or enforce payment.
While functional, this model breaks quickly as scale increases. Once trade extends beyond local markets, bilateral trust becomes insufficient. Merchants can no longer reliably verify the value of the money they are paid (since coins often differed in weight or metal content and were frequently altered or debased). Obligations extend across time horizons that exceed any individual reputation where enforcement is effectively impossible. And sovereigns face the same constraint at larger scale. Wars and public works require financing obligations that extend far beyond any individual reputation or short-term enforcement, making ad hoc borrowing insufficient.
Early banking institutions emerged to address these coordination failures. The Bank of Amsterdam was founded in 1609 in direct response to problems of settlement and trust. Physical money consisted of gold and silver coins whose value was difficult to verify, as coins varied in weight, purity, and condition and were frequently clipped, shaved, or debased.
Merchants deposited metal with the bank and settled transactions through entries on the bank’s ledger rather than by exchanging coins. The innovation was certainty of settlement. Heterogeneous coins were converted into standardized ledger balances, and transactions were finalized on the bank’s books, backed by centralized custody and strict governance.
The Bank of England was founded in 1694 to address the inability to enforce trust over long periods at sovereign scale. England faced repeated fiscal crises and lacked a reliable mechanism to fund long-term sovereign debt. In exchange for lending to the Crown, the Bank received privileges that allowed it to issue notes and intermediate government obligations. Trust no longer depended on the reputation of individual lenders or the immediate threat of force. Instead it was institutionalized through sovereign backing, which allowed obligations to settle over time through an entity designed to persist beyond any single ruler or war.
A few observations are worth keeping in mind.
First, at small scale, centralization was an acceptable compromise. Concentrating settlement, custody, and credit decisions in a single institution reduced coordination costs and allowed trade to expand beyond personal networks.
Second, in exchange for providing these services, intermediaries earned durable economic rents. This point matters for understanding why incumbents resist change.
Third, while these institutions reduced certain risks, they did not eliminate risk altogether, and in some cases amplified it.
Scaling Trust Through Institutions
By the 19th century, industrialization introduced new coordination problems. Securities trading expanded beyond informal broker networks and trades were negotiated between parties who often would never meet again. This caused long settlement times, manual and error-prone reconciliation, and cascading defaults that were not identified in time. A fair summary for all of these issues is counterparty risk. Something anyone who has worked in traditional finance, fintech, or crypto knows a lot about.
Clearinghouses emerged to address this problem. A clearinghouse sits between buyers and sellers and becomes the counterparty to both sides of a trade. Rather than each participant settling individually with every other participant, obligations are netted and settled through a central entity that guarantees performance, manages margin, and enforces rules.
The London Clearing House was founded in 1773 to allow member banks to net obligations rather than settle transactions bilaterally, dramatically reducing the number of payments required and limiting the spread of defaults. The New York Clearing House was founded in 1853 to provide similar services while also acting as a source of emergency liquidity during periods of stress.
These institutions reduced bilateral counterparty risk by mutualizing it. The tradeoff was concentration. Risk became easier to manage in normal conditions and more dangerous under stressful ones. Clearinghouses only addressed a narrow slice of the problem. They protected participants in specific markets from the failure of individual counterparties. They did not provide liquidity to the broader financial system, nor did they cover institutions operating outside their membership.
This limitation became clear during the Panic of 1907. A growing share of financial activity in the United States was conducted through trust companies, lightly regulated institutions that sat outside the traditional banking system. Trust companies took deposits, made loans, and invested in securities, but they were not subject to the same reserve requirements as national banks and did not have routine access to clearinghouse support.
When a small number of trust companies experienced losses, confidence eroded quickly, driving depositors to withdraw funds, banks to hoard cash, and an almost complete freeze on interbank lending. Clearing mechanisms still existed, but they were ineffective once institutions questioned the solvency of one another. The problem was the absence of liquidity across the entire system.
In the absence of a formal lender of last resort, stability depended on ad hoc intervention. J.P. Morgan (the individual) organized private rescues by pooling capital from major banks and directing it toward institutions deemed systemically important. The same failure mode would surface again whenever private balance sheets were forced to carry systemic liquidity risk before a true lender of last resort intervened, most notably during the Global Financial Crisis of 2008 and the U.S. regional banking stress in 2023.
The Federal Reserve was created in 1913 to formalize the lender-of-last-resort function that had been improvised by J.P. Morgan and other private banks during the Panic of 1907. It provided a system-wide source of liquidity and a final settlement authority when private coordination broke down. In practice, this meant ensuring that payments cleared and solvent institutions could access cash even when markets froze. In doing so, the Federal Reserve centralized monetary authority and entrenched a single institution as the ultimate backstop for the financial system.
Each solution to a coordination problem had produced the same outcome. Concentration of trust in fewer hands, and new fragilities that would only become visible under stress.
The Paperwork Crisis
The next major inflection came in the 1960s, when U.S. securities markets experienced what became known as the Paperwork Crisis. In the decades following World War II, equity ownership shifted rapidly from individuals to institutions. Mutual funds, pension funds, and insurance companies grew in size and importance, trading more frequently and in larger volumes.
The underlying mechanics of settlement, however, had not kept pace. Trades were still confirmed, matched, and settled through physical paperwork; which meant stock certificates had to be printed and reconciled by hand. While the tools would eventually change, the underlying coordination problem of how to represent and transfer ownership reliably at scale has persisted to modern day (see tokenization commentary further below).
As these trading volumes surged, back offices were overwhelmed and physical certificates accumulated in warehouses, hence the “Paperwork Crisis”. This resulted in an increase in settlement failures causing a cascade of broker-dealers to go out of business because they could not process transactions quickly enough to meet their obligations.
In response, the Depository Trust Company immobilized securities and replaced physical certificates with electronic book-entry records in 1973. Ownership of securities became an entry in a centralized database. This solved the immediate operational problem, but it also concentrated trust in one institution and made the integrity of the system dependent on that ledger remaining accurate. Decades later, crypto would explicitly question whether settlement and ownership needed to rely on a single institutional system of record at all.
But that question was still many years away. In the meantime, the system did what financial systems always do, solve the immediate crisis by concentrating trust further.
The same period saw the standardization of settlement cycles. What is now known as T+1 settlement in U.S. equities (reduced from T+2 in May 2024) reflects deliberate tradeoffs made decades earlier. Delayed settlement created time for three critical processes:
Netting allowed institutions to offset buys and sells across many transactions so that only a single net obligation had to be settled, rather than thousands of individual trades.
Funding gave intermediaries time to source the cash or securities required to meet those net obligations, reducing the likelihood of forced sales or liquidity shortfalls.
Reconciliation allowed firms to confirm that all parties agreed on the details of each trade before settlement was finalized.
Together, these buffers reduced immediate liquidity pressure on intermediaries and made the system more stable under normal conditions. The cost was increased credit exposure between trade and settlement, as counterparties remained economically tied to one another until obligations were finally resolved.
Payments infrastructure evolved in parallel. SWIFT standardized interbank messaging but did not move money, the ACH Network enabled electronic transfers but retained batch processing and delayed finality, and card networks such as Visa and Mastercard scaled consumer payments globally while embedding multi-party fee structures and intermediated trust.
Foreign exchange settlement followed a different path. Moving value across currencies required coordinating pricing, liquidity, and settlement across separate banking systems and time zones. Rather than relying on shared settlement infrastructure, FX evolved around correspondent banking relationships and dealer balance sheets, with large banks acting as market makers and liquidity providers.
In many cases, payment and FX settlement occurred on different timelines, introducing settlement risk that had to be managed institution by institution rather than eliminated system-wide. This architecture worked, but it did so by embedding spreads, delays, and opacity as the cost of coordinating trust and liquidity across borders.
Each of these systems solved a specific coordination problem, but none delivered real-time, final settlement across institutions. In practice, this meant that a transaction was not truly finished at the moment it occurred. Cash and securities changed hands only after a delay, often days later. During that gap, both sides remained exposed to the possibility that the other might fail.
To manage that exposure, intermediaries filled the gap between execution and settlement. Clearinghouses demanded margin to cover potential losses, banks used their balance sheets to guarantee payments, and liquidity buffers were built up to ensure trades could be completed even if a counterparty failed in the interim. This arrangement worked under most conditions. But it worked by compensating for delayed settlement through margin, capital buffers, and balance sheet guarantees, imposing a large opportunity cost of capital rather than eliminating the delay itself.
The 2008 Stress Test
This architecture was put to a true system-wide test during the Global Financial Crisis of 2008. In the years leading up to the crisis, risk had become increasingly difficult to observe in aggregate. Financial institutions managed exposures on their own balance sheets, often through bespoke bilateral derivatives that transferred risk privately rather than through transparent markets. No single institution or regulator could see how leverage and credit exposure were distributed across the system as a whole.
When asset prices began to fall, the architecture described above left the system with little usable slack. Capital had already been immobilized across balance sheets to support delayed settlement, margin requirements, and counterparty guarantees.
When confidence broke, that capital could not be rapidly reallocated. Rather than failing at the point of settlement, stress propagated through short-term funding markets. Repo markets, which institutions relied on for day-to-day liquidity, froze as lenders questioned the value of collateral and the solvency of borrowers. Funding disappeared faster than capital buffers or margin requirements could adjust, and institutions that appeared solvent on paper were suddenly unable to meet cash obligations.
The Global Financial Crisis was driven by credit excesses, leverage, and a collapse in confidence, not by settlement mechanics themselves. But the architecture described above materially amplified the shock by leaving the system with little deployable capital once stress emerged.
Central banks and clearinghouses ultimately prevented collapse by stepping in as lenders, buyers, and guarantors of last resort. These interventions stabilized the system but they also concentrated risk and authority further within a small number of institutions, reinforcing the very centralization that had allowed the system to function under stress.
The Inherited Constraints
By the early 2010s, financial services had reached a relatively stable equilibrium. The system processed trillions of dollars daily and was generally resilient, but it was also expensive to operate and slow to adapt.
Settlement remained a core issue because transactions were often economically complete only after days, sometimes longer. Lack of uniformity drove reconciliation to become a major cost center, requiring duplicated systems, manual processes, and large operational teams whose sole function was to resolve discrepancies after the fact. Compliance evolved from a safeguard into a dominant operating function.
The result was an industry in which a substantial share of economic activity was devoted to managing the consequences of how the system itself was constructed rather than the efficient allocation of capital. Financial services real GDP has grown 24.5x since 1945 and as a percentage of GDP has increased more than 3x.
Understanding this evolution clarifies the core constraints any new financial system must contend with:
Settlement finality: in the absence of immediate, conclusive settlement across institutions, transactions remain economically incomplete for days. During that window, credit and liquidity risk must be absorbed by intermediaries through margin, capital buffers, and balance sheets.
Balance sheet risk: in a system without immediate settlement, intermediaries must temporarily guarantee transactions using their own capital. When stress rises, those balance sheets hit binding constraints at the same time, limiting the broader system’s ability to function regardless of demand.
Regulatory compliance: as risk is managed through institutions rather than infrastructure, regulation becomes the primary mechanism for enforcing trust.
Institutional trust: the system ultimately depends on confidence in a small number of intermediaries, clearinghouses, and central banks to act as sources of truth and backstops during stress.
Any attempt to build a new financial system, whether through crypto-native rails, tokenized infrastructure, or hybrid models that integrate with legacy systems, must either accept these constraints or restructure them.
II. What Fintech Changed
By the late 2000s, it had become visible how much friction consumers and enterprises were expected to tolerate for basic financial actions. Opening a bank account took days. Moving money across borders remained slow and expensive. Accepting payments required navigating opaque fee structures, and financial data was fragmented across institutions and difficult to access.
This stood in sharp contrast to the rest of the economy, where software was already reshaping user experience, distribution, and cost structures. Around the same time Marc Andreessen published ‘Software Is Eating the World,’ consumers were getting one-click checkout on Amazon and instant rides on Uber, while banks still required faxed documents and international wire transfers took days and cost $45.
In response, early fintechs largely chose a pragmatic path, they left the underlying financial infrastructure intact and focused on changing how it was accessed. This was a reasonable strategic choice. Building new settlement, clearing, or custody infrastructure would have required navigating heavy regulation, committing substantial upfront capital, and investing in systems with little near-term visibility into monetization. Partnering with existing rails offered dramatically faster time to market.
Abstractions on Legacy Rails
PayPal, founded in 1998, made online payments viable at internet scale by abstracting card networks and bank transfers into a single digital wallet. It did not build new settlement or clearing infrastructure. Users no longer had to understand or manage the underlying rails.
A decade later, Stripe took this further by turning card acceptance into a software primitive. With the launch of its payments API in 2011, Stripe replaced bespoke integrations and acquirer negotiations with a few lines of code, allowing developers to embed payments without becoming experts in interchange, settlement, or compliance.
Robinhood digitized account opening and eliminated trading commissions, lowering the cost of access to equity markets. From a user’s perspective, trades executed instantly and positions updated in real time. The underlying mechanics remained unchanged, orders still cleared through DTCC and settled on delayed cycles under T+2 settlement.
Wise (TransferWise) built a proprietary clearing network by prefunding local accounts and netting flows internally, but did not replace correspondent banking or FX settlement infrastructure. Final settlement still depended on banking relationships in each jurisdiction. The innovation was in how legacy rails were accessed and orchestrated.
There was an excellent conversation with Josh Wolfe and Jackson Dahl where Wolfe makes the point that everything ever built is a remix, referencing Kirby Ferguson’s original series on the topic. This framing is particularly useful in finance given fintech didn’t create new financial primitives, it just recombined existing ones and changed how those primitives were assembled and exposed through software.
What Fintech Built
None of these limitations negate fintech’s impact. Fintech expanded who could participate, accelerated time to market, and dramatically reduced the cost of distribution. It also marked a shift toward software being built atop standardized financial primitives, as Stripe did for payments, rather than bespoke, bank-by-bank integrations with acquirers like First Data or Chase Paymentech.
This transition was articulated early by Matt Harris in his essays “Fintech: The Fourth Platform.” Harris argued that fintech was moving from a standalone category into a native layer of the software stack, embedding payments, lending, and insurance directly into technology products. That shift transformed distribution and monetization, but it left underlying banking and settlement rails intact.
The result was a meaningful reduction in trading commissions and a dramatic expansion in access to digital payments. Platforms like Shopify and Uber embedded financial workflows directly into their products, turning what had once been standalone financial actions into background infrastructure. Developers could ship faster using standardized APIs, without first becoming experts in banking, payments, or compliance.
It even forced incumbents to change. Large banks rebuilt consumer interfaces that had been neglected for years. Card networks such as Visa and Mastercard shifted investment toward developer tooling and tokenization at the edges of their systems, including network tokenization initiatives launched in the mid-to-late 2010s.
The Limits Became Visible Under Stress
However, the limits of fintech became visible once abstraction improvements were exhausted. This was seen during periods of volatility when the underlying constraints (and the friction that comes with them) became very clear.
In March 2020, as the COVID shock moved through global markets, even U.S. Treasuries, typically among the most liquid markets, showed stress as dealers pulled back and banks reached balance sheet limits. Access to funds increasingly depended on relationships, balance sheet capacity, and perceived risk even though user-facing interfaces continued to function normally.
In January 2021, Robinhood had to restrict trading because of clearinghouse margin requirements imposed under standard T+2 settlement. As volatility spiked, required margin increased from approximately $26 million to $3.7 billion overnight. Trades were still executing and orders were still matching, but the legacy system failed to intermediate risk between execution and settlement at scale. Robinhood did not control settlement cycles, clearing rules, or margin frameworks.
As a quick aside, I recommend this conversation with Micky Malka and Patrick O'Shaughnessy about the hours surrounding this event.
Faster interfaces had increased the speed of demand while underlying rails remained constrained by cutoff times, batch processing, and intermediary risk limits. When volatility rose, the system reverted to its inherited settlement and risk management constraints, behaving much as it had long before real time digital interfaces existed.
III. Crypto’s False Starts
Crypto took the opposite approach. It began by questioning whether the constraints fintech worked around were necessary rather than improving interfaces or distribution.
Bitcoin was designed to enable peer-to-peer transfer of value without reliance on banks, clearinghouses, or payment networks. Once a transaction was confirmed on the network, ownership changed conclusively, without the need for reconciliation across institutions, a clearing intermediary, or balance sheet guarantees to stand behind the transfer.
Ethereum extended this idea by introducing smart contracts, which made it possible to encode financial logic directly into software. Trading, settlement, and custody could, at least in theory, occur within a single system rather than being distributed across multiple institutions with separate incentives and risk controls.
Both Bitcoin and Ethereum, along with several other projects founded during this period, were explicitly designed to challenge the back-end constraints that fintech had largely accepted.
One of those constraints was delayed settlement. In traditional financial systems, transactions are often considered complete only days after they occur, once multiple institutions have reconciled records and exchanged funds. Bitcoin and Ethereum proposed a system where transactions settled directly on a shared ledger, with ownership changing conclusively once confirmed, rather than being finalized later through back-office processes.
Another constraint was balance sheet intermediation. In legacy finance, banks and dealers stand between parties, using their own balance sheets to guarantee transactions while settlement is pending. This makes the system safer, but also slower and more capital intensive. Crypto systems sought to remove the need for intermediaries to temporarily absorb risk by allowing transactions to settle directly between participants.
The third constraint was trust enforced through intermediaries. Traditional finance relies on institutions (banks, clearinghouses, custodians) to maintain records and enforce outcomes. Bitcoin and Ethereum instead relied on shared rules and software to determine ownership state and execution, reducing dependence on any single institution as the source of truth.
In theory, removing these constraints opened the door to a wholesale re-architecture of the financial stack.
Speculation and the Search for Infrastructure
Between Bitcoin’s launch in 2009 and the speculative surge that began in 2017, the industry developed slowly.
In its early years, Bitcoin functioned primarily as a niche settlement network. It attracted technologists and libertarians interested in censorship resistance and self-custody rather than mainstream financial use cases. A worthwhile read if you’re interested in this era of crypto history is “The Age of Cryptocurrency” by Paul Vigna and Michael Casey.
During this period, there was essentially no liquidity, extremely high volatility and incredibly unreliable custody solutions. For most users, participating required running software, managing private keys, and accepting the risk of permanent loss.
The collapse of Mt. Gox in 2014, which at the time handled the majority of BTC trading volume, underscored how fragile the surrounding ecosystem was. It’s almost laughable how far away crypto was from broader financial integration. There was no regulation of exchanges, there were no robust custodial solutions, and the technology was being used for illicit purposes.
Ethereum’s launch in 2015 expanded the design space by introducing smart contracts. At a basic level, smart contracts made it possible to write financial rules directly into software and have them execute automatically once predefined conditions were met. Instead of relying on institutions to interpret contracts and enforce outcomes after the fact, logic could be embedded directly into the system itself.
However, most early applications built between 2015 and 2017 were experimental. Some of you may remember the DAO, but if not, I recommend this Wired article on the story. Some of those experiments were revisited many years later and ultimately found PMF, like prediction markets.
By 2017, token issuance had provided a new mechanism for financing projects without traditional gatekeepers. Naturally, speculation filled the gap that usage had not yet reached. This pattern is not unique to crypto, in fact Carlota Perez wrote a whole book about this phenomenon across industries. She articulates how periods of technological discontinuity are often accompanied by waves of speculative capital that fund experimentation well ahead of stable demand.
The 2017 ICO cycle reflected this. Billions of dollars flowed into token sales for projects that were little more than whitepapers. Tezos raised over $200 million, EOS raised more than $4 billion, and many others raised money with little to show on the other side.
However, it would be a mistake to treat the entire period as devoid of real progress. Several foundational protocols that continue to matter today were either launched or reached maturity during this window. Uniswap introduced AMMs that enabled permissionless liquidity. Compound and Aave demonstrated that overcollateralized lending and borrowing could function without centralized intermediaries.
The protocols were working well, the issue was more so that usage was just highly cyclical. Activity surged during bull markets when asset prices rose and incentives were abundant, then contracted sharply when prices fell.
Removing Safeguards Before Replacing Them
As discussed earlier, traditional financial systems rely on a set of imperfect but intentional safeguards. For example, delayed settlement creates time to net positions and source liquidity or capital buffers and margin requirements slow the realization of losses. These features introduce friction, but they exist because earlier systems failed without them.
Many early crypto platforms attempted to recreate familiar financial functions (trading, lending, leverage) while stripping away these buffers. In doing so, risk was removed from the system’s surface faster than it was replaced with guardrails capable of absorbing shocks.
The collapses of Terra in May 2022 and FTX later that year made the gap clear. Traditional financial systems are built with shock absorbers. They limit leverage up front and slow things down when volatility rises. This gives institutions time to manage losses before failure. Many of the things discussed in the sections above like capital buffers, margin calls, and regulatory intervention all exist to prevent sudden panic from turning into systemic cascades across the broader financial system.
Those safeguards were largely absent in the Terra and FTX ecosystems. Leverage built up quickly and liquidity was taken for granted so when confidence finally failed there were no effective circuit breakers or balance sheets to take the shock.
The implication was impossible to ignore for regulators: crypto appeared to remove intermediaries but in practice it often recreated them in weaker form, without the balance sheets, controls, or accountability that centuries of financial evolution had converged on.
A Hostile and Ambiguous Regulatory Environment
The outcome of this period cannot be understood without examining the regulatory environment in which it unfolded, particularly in the United States.
From 2021 onward, under SEC Chair Gary Gensler, U.S. crypto regulation took on an explicitly enforcement-first posture. Rather than issuing new market structure rules or providing clear pathways for registration, the SEC relied heavily on litigation and settlements to define the boundaries of permissible activity.
Over the following years, the SEC sued just about everyone: exchanges, token issuers, lending platforms, infrastructure providers. The cumulative message to builders and institutions was “engage at your own risk”. During the period there were over 125 enforcement actions with Wells Notices given to at least 10 well known companies, including Coinbase, Uniswap, and Robinhood.
This posture had predictable effects.
First, institutional participation slowed materially. Large financial institutions explored crypto but deferred meaningful integration into core products. Banks limited activity to pilots rather than deploying crypto rails in payments or capital markets. Even firms that publicly acknowledged the potential of blockchain technology largely avoided production use in the absence of clear regulatory pathways, opting instead to wait for clarity rather than risk enforcement.
Second, infrastructure investment shifted offshore. As U.S. enforcement actions mounted, many crypto companies chose to base core operations, token issuance, or liquidity outside the United States. Jurisdictions such as Singapore, Dubai, and Hong Kong offered clearer licensing regimes or forward-looking market structure frameworks. The result was not less crypto activity, but less of it occurring within U.S. regulatory oversight.
Third, product design increasingly optimized for regulatory arbitrage rather than durability. Founders structured products to minimize U.S. exposure, limited access for U.S. users, or relied on legal distinctions that were unlikely to scale long-term.
Importantly, this environment did not reduce speculative activity. Retail participation continued through offshore venues, and periods of rising asset prices still attracted capital. What it constrained was institutional adoption and long-horizon investment in core financial infrastructure, the very category of activity required to move crypto forward.
This was seen in adoption metrics. Onchain lending and trading volumes rose quickly during bull markets and receded just as quickly when prices fell. NFT marketplaces like OpenSea followed a similar trajectory in 2021, with activity largely driven by speculative demand rather than recurring economic use.
From the standpoint of the coordination problems outlined earlier, crypto had not yet demonstrated the property that matters most for financial systems, lindyness. Financial products become trusted because they persist (vs because they are novel). They need to survive stress and continue to be used when conditions are least favorable.
By 2022, the primary question was whether these primitives could persist under stress, integrate with existing safeguards, and reduce cost or complexity without sacrificing resilience.
Part Two
IV. Modern Financial Infrastructure Becomes Viable (2023-Present)
This brings us to the modern era. While speculation is still here (and always will be), crypto is finally becoming viable infrastructure for the coordination problems that have shaped financial services for centuries. Sometimes this means replacing legacy back-ends entirely. More often, it means running alongside them, integrating into existing workflows, or enabling capabilities the old system was never designed to support.
The remainder of this essay examines why I believe the next 10 years of financial innovation will surpass the prior 50 years, driven primarily by five converging themes:
We can finally build financial products on modern infrastructure, whether that means replacing legacy back-ends, running alongside them, or enabling entirely new capabilities.
We have regulatory clarity emerging around stablecoins and custody, alongside a converging federal approach to digital asset market structure that gives institutions clearer lines of authority and compliance.
We can see incumbents integrating crypto-native components directly into existing workflows or acquiring the capabilities outright.
We have capital markets that are maturing and attracting more sophisticated participants.
We can now combine these shifts with advances in AI, expanding the design space for financial systems that are automated and intelligent by default.
Modern Infrastructure Becomes Viable
For most of the last two decades, financial innovation progressed on the front end while remaining constrained by legacy back-end systems. That constraint is now meaningfully lifted. Modern fintechs and crypto-native companies are using crypto rails in production as default infrastructure.
One clear example is Robinhood. Robinhood has steadily expanded its crypto capabilities in ways that go beyond speculation. In mid-2025, the company launched tokenized U.S. equities and ETF tokens for European users, with the tokens issued and settled on Arbitrum. In effect, Robinhood paired a familiar consumer front end with a crypto-native back end (Arbitrum), in contrast to its legacy U.S. brokerage stack, where trades clear through DTCC infrastructure and settle on T+2 cycles via custodians and broker-dealers.
Vlad has been explicit about how he views tokenization’s role in the future of financial markets, describing it as an “unstoppable” force that will transform traditional finance. If of interest, this is a great conversation with Vlad Tenev and John Collison that discusses some of these themes. Brian Armstrong also unpacks the benefits of tokenization in his recent talk at Goldman Sachs.
Revolut began as a neobank abstracting FX and card networks. It has now evolved into a unified financial interface that incorporates crypto balances, transfers, and onchain exposure directly into the core product. Revolut processed over $10 billion in stablecoin transfers in 2025, up from $4.1 billion in 2024. The company is positioned to only scale this further. It holds a MiCA license across 30 EEA countries, offers 1:1 USD stablecoin conversion at zero spread, and has a Lithuanian EMI license that would allow it to issue its own stablecoin.
A similar but more cautious evolution is visible at Klarna. While Klarna has not yet deployed crypto-native settlement in its core BNPL flows, its leadership has consistently described tokenization as an inevitable shift in financial infrastructure rather than a consumer product. CEO Sebastian Siemiatkowski has publicly argued that crypto’s real impact will come from how assets are represented, settled, and financed, not from speculative trading.
Reflecting that shift, in late 2025 Klarna announced KlarnaUSD, a U.S. dollar-backed stablecoin it is launching on the Tempo blockchain to explore more efficient settlement and cross-border payment infrastructure.
Alongside consumer fintechs, a new layer of crypto-native companies has emerged that make modern back ends usable in production rather than experimental.
Privy addresses identity and access (the unglamorous problem of how a user logs in without managing cryptographic keys). In traditional finance, this is handled through custodial accounts tied to banks. Privy makes crypto wallets feel like normal accounts. Users don't know they're holding keys, and that's the point.
Fireblocks focuses on custody and internal transfers. In legacy systems, moving assets requires manual approvals, custodial instructions, and reconciliation across multiple teams and systems. Fireblocks preserves those controls and compliance requirements, but implements them through programmable custody and policy-based controls on crypto-native rails.
Bridge tackles global payments and treasury. Where cross-border money movement traditionally relies on correspondent banks, SWIFT messages, and batch settlement, Bridge treats stablecoins as the system of record. Value moves continuously onchain while users and merchants interact with familiar front-end abstractions.
Altitude replaces internal treasury and approval workflows. Instead of custodians, spreadsheets, and manual sign-offs, Altitude provides smart-contract wallets and a programmable treasury layer on Solana. Teams manage assets, approvals, and payments directly onchain, with rules enforced by code rather than process.
Dune & Blockworks focus on observability. In legacy systems, system-wide insight depends on delayed reporting and fragmented data ownership. These businesses replace that model with a shared analytical layer over public onchain data, enabling real-time measurement without centralized intermediaries.
M0 extends the modern logic to the monetary base itself. Instead of relying on bank balance sheets and central bank reserves as the foundation of settlement, M0 is designed as a crypto-native monetary primitive that other financial systems can build on.
At Layer3, we have built a series of products that are implemented directly on these new rails. Ample allows fintechs to increase asset retention through programmable prize-linked savings accounts, Stack allows consumers to trade tokenized equities (via perps) in a self-custodial mobile app 24/7, and Illa provides essential infrastructure to connect AI interfaces and financial rails.
This is the first time in history where modern front ends and modern infrastructure have actually converged in finance, whether through direct integration, parallel operation, or entirely new capabilities.
For a deeper articulation of why this convergence matters, and what it could mean for global capital flows, property rights, and financial inclusion, see Felipe Montealegre’s essay “Internet Finance”
The Regulatory Conditions for Institutional Adoption
From 2021 through much of 2023, U.S. crypto regulation was defined through enforcement. As discussed earlier, that posture pushed innovation offshore, led to suboptimal product design, and stalled institutional adoption. That posture persisted until the regulatory environment itself began to change in 2025.
The inflection began with the repeal of SAB 121. Issued in 2022, SAB 121 required banks and broker-dealers to treat customer-held crypto as on-balance sheet liabilities, effectively making regulated crypto custody uneconomic at scale. A bank offering custody for client crypto would have been forced to hold capital against assets it did not own or control economically, making the business unattractive compared to traditional custody services. It was removed in 2025, eliminating a major structural barrier to institutional custody and signaled that crypto assets could be integrated into existing frameworks.
In July 2025, President Trump signed the GENIUS Act into law, establishing the first federal regulatory framework for payment stablecoins. The act requires 1:1 reserve backing with U.S. dollars or short-term Treasuries, mandates monthly public disclosures, and creates pathways for both federal and state-level supervision. It explicitly positions stablecoins as payment and settlement instruments that reinforce the existing monetary system, linking stablecoin growth directly to demand for U.S. Treasuries.
Market structure legislation has followed a longer path. The House passed the Digital Asset Market Clarity Act in July 2025, laying out a split framework that places digital commodity spot markets under the CFTC while preserving SEC authority over investment contracts at issuance. As of January 2026, the Senate is still working through parallel drafts in Banking and Agriculture, with committee action ongoing and key provisions still under negotiation.
The result of this legislation stands to materially change the operating environment for all participants. Founders can design products with an understanding of compliance obligations. Investors can allocate capital without fear of the underlying business receiving a Wells Notice. And institutions can deploy crypto-native rails with clear disclosures around risk management.
Institutional Adoption Takes Shape
As discussed in Part One, financial institutions adopt new infrastructure only when it resolves a core coordination problem at lower cost without introducing additional risk. By 2025, crypto-native rails began to meet that threshold. They offered a credible way to address long-standing frictions around settlement, liquidity, and trust, problems that legacy infrastructure had managed through delays, balance sheets, and intermediaries (rather than eliminating outright).
Adoption first appeared in payments and cash management, where settlement speed and liquidity constraints are most visible. In December 2025, Visa announced the launch of USDC settlement capabilities for U.S. institutions, citing more than $3.5 billion in annualized stablecoin settlement volume. Mastercard followed with its Multi-Token Network, connecting to J.P. Morgan’s Kinexys Digital Payments platform to enable compliant, tokenized B2B settlement. In both cases, stablecoins were integrated alongside existing rails rather than replacing them, allowing value to move continuously while preserving established compliance and risk frameworks.
A similar shift became visible in brokerage and funding. In January 2026, Interactive Brokers enabled 24/7 account funding using USDC, allowing clients to move capital into brokerage accounts within minutes rather than business days. Stablecoins are converted to dollars on receipt, and trading continues within existing custody and regulatory structures.
Banks, which sit at the center of these coordination problems, moved more cautiously (but in the same direction). In November 2024, J.P. Morgan rebranded its blockchain and tokenization efforts under the Kinexys name. Since inception, the platform has processed more than $2 trillion in notional volume, averaging over $5 billion per day. While small relative to global bank flows, Dimon has been explicit that the cost-benefit is meaningful and the effort will scale. Citi followed by expanding Citi Token Services, integrating tokenized deposits and smart contracts directly into cash management workflows and allowing liquidity to move continuously across time zones.
Asset management adoption pushed tokenization into portfolios. Morgan Stanley expanded crypto trading and tokenized custody across public and private markets, explicitly framing tokenization as an infrastructure shift rather than a product feature. This shift became most visible in Larry Fink’s public reversal on crypto. As Fink and BlackRock COO Rob Goldstein wrote:
“Tokenization was tangled up in the crypto boom, which often looked like speculation. But in recent years traditional finance has seen what was hiding beneath the hype: tokenization can greatly expand the world of investable assets beyond the listed stocks and bonds that dominate markets today.”
Other large asset managers, including Franklin Templeton and Goldman Sachs, have announced similar efforts to tokenize products within existing regulatory frameworks.
Finally, the strongest evidence that crypto infrastructure is becoming viable at institutional scale comes from the market utilities themselves (the same institutions that enforced these constraints a few years prior). In December 2025, the DTCC announced it is enabling tokenization of a subset of DTC-custodied U.S. Treasury securities, describing tokenized assets as able to move 24/7 within pre-approved ecosystems.
SWIFT’s posture has also evolved. In September 2025, it announced plans to add a blockchain-based ledger to its infrastructure stack. These are the same two utilities that, for decades, enforced slow settlement, batch processing, and rigid market hours. The very constraints that surfaced publicly during episodes like the Robinhood trading halt.
It is clear that crypto-native rails are no longer confined to pilots and instead are being integrated by incumbents where they solve specific coordination problems more efficiently, without compromising risk management or compliance. The same problems that created clearinghouses in the 19th century and central banks in the 20th are now being addressed with different tools.
For a deeper, operator-level analysis of where stablecoins offer order-of-magnitude improvements, particularly in cross-border B2B payments, I recommend Josh Solesbury’s essay “Getting to the Crux of Stablecoin Utility.”
Incumbents can now integrate crypto-native rails without changing their risk posture. As a result, adoption has begun to scale across payments, banking, asset management, and market infrastructure.
V. Capital Markets Have Re-Priced Crypto
I began my career at Accolade Partners, a long-standing allocator to technology focused venture and growth funds. While there, I helped build one of the first crypto fund-of-funds platforms, a useful vantage for watching institutional capital find its footing in a new category.
Capital markets form around new technologies in a predictable sequence. Venture typically comes first when risk is highest and the asset class is illegible to most institutions. Growth equity follows once business models stabilize. Liquid markets, credit, public equities, and structured capital come later once the category is legible enough to underwrite at scale.
Crypto followed this arc. From 2014 to 2019, the first wave of dedicated venture firms emerged. Firms like Pantera, a16z, Blockchain Capital, Multicoin, and CoinFund, among others. These firms were largely founded by technologists and former operators, primarily focused on company formation through Series A. They were also the only reliable source of capital for crypto entrepreneurs.
Between 2020 and 2025, the landscape expanded quickly. Multi-stage firms entered to fund growth rounds, or some of the names mentioned above raised large $1B+ vehicles. Crypto venture went from $5.5B in 2020 to $33B in 2021.
Today, it seems the full stack is forming. Public equity investors, special situation desks, late-stage participants, and crossover investors now operate alongside early stage venture firms.
Crypto Public Equities Matured
Until recently, there were only a handful of ways to express a view on the long-term secular growth of crypto. Today, public investors can access crypto through exchanges, asset managers, stablecoin issuers, custody providers, and ETFs, with some companies already public and others slated to list this year.
The first category is exchanges and trading infrastructure: Coinbase (NASDAQ: COIN), Bullish (NYSE: BLSH), Gemini (NASDAQ: GEMI) and soon Kraken. These businesses have evolved from retail trading proxies into regulated financial infrastructure platforms, earning revenue from stablecoin distribution, custody, staking, and derivatives alongside trading fees.
The second is asset management and merchant banking: Galaxy Digital (NASDAQ: GLXY) and soon Grayscale. These firms provide institutional investment products, principal investing, and advisory services across digital assets.
The third is stablecoin issuers. Circle (NYSE: CRCL) is the clearest case, it issues USDC and earns reserve income on the assets backing the float, net of distribution and operating costs.
The fourth is custody and security infrastructure: BitGo (NYSE: BTGO), Ledger, and Anchorage, which are public, have filed, or are expected to file. These businesses provide the operational backbone that institutions require to hold and move digital assets.
The fifth is ETFs. The approval of spot Bitcoin ETFs in January 2024, followed by Ethereum ETFs, created the first fully regulated, exchange-traded vehicles for passive institutional and retail exposure. Since launch, spot Bitcoin ETFs have attracted nearly $57 billion in cumulative net inflows and now hold over $110 billion in assets, representing roughly 7% of total Bitcoin supply. In 2025, Ethereum ETFs added over $10 billion, nearly four times their 2024 totals.
Then there is a final category that has long existed in public markets, but until recently was not analyzed through the lens of crypto’s secular impact on financial back-end infrastructure. These are fintech and payments companies whose core products are starting to run into, adopt, or be pulled toward crypto-native infrastructure.
This is where the universe expands beyond “crypto companies” and forces generalist financial investors to care about crypto rails.
Payments and merchant acquiring names that historically lived inside card, ACH, and correspondent constraints now face a plausible alternative settlement surface that is always on. Even when a company has not fully migrated flows, the existence of stablecoin settlement changes the cost and speed frontier that customers expect. This is why the set of “crypto-linked” public equities now naturally includes companies that were previously analyzed as conventional fintech or payments compounders including Block (NYSE: SQ), PayPal (NASDAQ: PYPL), Adyen (AMS: ADYEN), Fiserv (NYSE: FI), Toast (NYSE: TOST), Wise (LSE: WISE), Remitly (NASDAQ: RELY), and Western Union (NYSE: WU).
Market infrastructure and financial incumbents also belong in the crypto-linked public universe. Firms such as CME Group (NASDAQ: CME), Intercontinental Exchange (NYSE: ICE), BNY Mellon (NYSE: BK), BlackRock (NYSE: BLK), and Virtu Financial (NASDAQ: VIRT) are increasingly forced to decide how crypto primitives fit within custody, clearing, and collateral workflows.
Finally, there are brokerage and consumer finance platforms such as Robinhood (NASDAQ: HOOD), NuBank (NYSE: NU) and Revolut (2026 IPO candidate). These businesses now occupy a hybrid position, combining consumer distribution with direct exposure to crypto-native infrastructure.
Public market “crypto” is a growing set of businesses that map to different parts of the stack including issuance, custody, trading, settlement, compliance, market data, payments distribution, and even energy-intensive compute.
As this surface area expands, the investor base expands with it. Payment analysts, fintech specialists, bank investors, and special situation desks increasingly have to get literate in stablecoins and crypto rails because the rails are starting to show up in cost structure, product design, and competitive dynamics.
The M&A Reassembly of Financial Infrastructure
A natural byproduct of a broader group of companies being influenced by crypto’s secular growth is heightened M&A. Incumbents increasingly acquire capabilities, licenses, and infrastructure rather than building from scratch. Crypto-native platforms, in turn, are consolidating to expand product scope, deepen liquidity, and buy teams that can accelerate execution.
A few examples to anchor the point:
Stripe acquired Bridge to internalize stablecoin orchestration as infrastructure. The transaction, reportedly valued at over $1 billion, reflects Stripe’s need for settlement efficiency, global reach, and programmable money movement for developers.
Stripe also acquired Privy, a crypto-native identity and wallet infrastructure provider. The deal terms were not disclosed, but the strategic intent was to secure control over authentication, key management, and access layers that sit between users and crypto-native rails.
Coinbase announced a $2.9 billion acquisition of Deribit, including $700 million in cash and 11 million shares of Coinbase stock, bringing derivatives liquidity and risk transfer in-house.
Kraken agreed to acquire retail futures platform NinjaTrader for $1.5 billion, signaling a push to own the licenses and interfaces required to offer a broader menu of regulated products.
Ripple acquired prime broker Hidden Road for approximately $1.25 billion, bringing institutional financing, clearing, and risk management directly onto its balance sheet.
MoonPay acquired Iron, an API-first stablecoin infrastructure platform, to productize stablecoin rails for payments and on-ramps.
The acquisition wave is best understood through the lens of the coordination problems this essay began with. Historically, financial innovation first emerged in environments where constraints are weakest such as lightly regulated markets, smaller customer bases, lower absolute volumes, or domains where failure can be contained without systemic consequences.
The system eventually reaches a point where the new mechanism has been tested long enough to prove it works, and the efficiency gains it offers become too large to ignore. At that moment, the same coordination pressures that reshaped prior financial systems are reasserting themselves and capital markets do their job through a flurry of deal making.
The Emergence of Special Situations
As markets mature, they create their own dislocations. Crypto is now far enough along that some of the most interesting dynamics sit between traditional capital markets and crypto-native assets. Two recent examples of note are 1) Digital Asset Treasury Companies (“DATs”) and 2) Miners.
Beginning with DATs, in 2025, a class of public equities emerged whose defining feature is that digital assets represent a large share of their balance sheets.
These companies are controversial for good reasons. They can behave like levered exposure to the underlying asset. They can trade at premiums or discounts to the value of their holdings. They can finance purchases through equity issuance or convertibles, which can work in rising markets and become fragile when premiums compress. Research-oriented investors have started analyzing these structures explicitly in terms of premiums to NAV and capital structure.
I agree with the critics that most of them are extractive by design. But this has been true in every sector once it reached public market-scale.
Energy produced MLPs and royalty trusts. REITs, shipping companies, miners, and commodity producers all went through phases where financial engineering ran ahead of long-term fundamentals. The primary takeaway is that the assets had become legible enough for capital markets to work on them.
DAT’s existence reflects a market beginning to experiment with how crypto exposure should be held, financed, disclosed, and indexed inside public equities. The debate around premiums to NAV, capital structure, governance, and index classification is the process by which a new asset gets absorbed into institutional frameworks.
I also agree with the critics that many of the hedge funds and special situation desks trading these names are not underwriting crypto’s long-term secular growth. They’re trading the volatility and capital structure but their participation still deepens liquidity, attracts analyst coverage, forces disclosure standards to evolve, and expands the set of investors who are required to form a view. Over time, that activity builds a more sophisticated capital stack around the sector.
A second example would be the repricing of Bitcoin miners and the emergence of what became known as the “power plus compute” trade, a trade that would have generated meaningful PnL in 2024 and 2025 if you were crypto literate and sophisticated enough in capital markets to see the shift occurring.
If you zoom out and look at other foundational technologies like railroads, energy, or telecom. A large part of why these systems became durable was because capital markets developed the ability to price risk and allocate capital across cycles.
The expansion of public equities, the increase in M&A, and the emergence of special sits are all characteristics of a system that has become legible for institutional finance to operate on it.
VI. A Note on AI
This section is explicitly speculative. I include it because the logical case is compelling, but readers should weigh it accordingly.
The transformation in software development is profound. According to Stack Overflow, 84% of developers now use or plan to use AI tools in their workflow. GitHub reports that users of AI coding assistants complete 126% more projects per week than those coding manually. These productivity gains apply directly to financial software. McKinsey estimates that generative AI alone could add between $200 billion and $340 billion annually across global banking.
For founders, this translates into a structural shift in what can be built and how quickly. Lower development costs disproportionately benefit new infrastructure. Building on crypto rails, which are natively programmable, becomes proportionally easier.
A more speculative extension concerns autonomous AI agents. As AI systems become capable of acting independently, scheduling, purchasing, negotiating, and transacting, they will require financial infrastructure that accommodates non-human actors. The constraints of traditional finance were designed for human participants. Bank accounts assume human identity. Credit cards assume human liability. Settlement cycles assume human response times. Operating hours assume human schedules.
Programmable money addresses these constraints. Stablecoins can be held by smart contracts without bank accounts. Settlement is instant and final. Operations run continuously. Permissions can be programmed rather than negotiated.
In September 2025, Cloudflare announced NET Dollar, a stablecoin designed specifically for agentic commerce, alongside the x402 protocol for machine-to-machine payments. This is forward-looking rather than production deployment. However, Cloudflare operates infrastructure for a significant share of global internet traffic, and its assessment of what agentic systems will require is grounded in real usage patterns. If you’re interested in Cloudflare’s focus here, I recommend this conversation with Matthew Prince and Sara Fischer.
There are clear limits to this line of thinking today. Meaningful agent-to-agent transactions are not yet occurring on crypto rails. The timeline is uncertain and more likely measured in years than quarters.
Still, the potential is large enough to warrant attention. If autonomous agents become meaningful economic actors over the next decade, and if they transact primarily on crypto rails, the infrastructure case described here becomes stronger.
VIII. Conclusion
Earlier in this post I referenced Andreessen’s “Software is Eating the World”. In his essay, he offered an explanation on timing. Software had existed for decades, but only once the full stack was in place did it become capable of reshaping the global economy rather than incrementally improving it.
Why is this happening now?
Six decades into the computer revolution, four decades since the invention of the microprocessor, and two decades into the rise of the modern Internet, all of the technology required to transform industries through software finally works and can be widely delivered at global scale.
A similar pattern now applies to financial infrastructure. Crypto has existed for more than a decade. What was missing was reliable settlement at scale, regulatory clarity, institutional participation, and the ability to build real products rather than experiments or speculative games.
Financial infrastructure tends to get replaced when the constraints that shaped its design lift, creating room for systems built on different foundations. The Champagne Fairs were designed for a world without trusted mechanisms to enforce payment at distance, but once banks could settle obligations through centralized ledgers, the fairs gave way. Physical stock certificates persisted because ownership required tangible proof, but once electronic book-entry became reliable, the DTC immobilized paper within a decade.
Delayed settlement persisted because reconciliation required time, until it did not, and Robinhood went from halting trades in 2021 to settling tokenized equities on Arbitrum in 2025.
The conditions now exist to address financial infrastructure directly:
Over the past fifteen years, fintech reshaped user expectations. Consumers and enterprises expect financial products that feel continuous, mobile, and instant, even though the underlying rails were not.
Stablecoins and crypto rails make real-time settlement and native ownership possible. Value moves in seconds rather than days, with finality that does not require clearinghouses. Ownership can be represented onchain rather than through layers of custodial abstraction.
U.S. regulation is becoming a tailwind rather than a headwind. The GENIUS Act, emerging federal market structure legislation, and the repeal of SAB 121 provide the guardrails founders and institutions need to build aggressively within clearer boundaries.
Capital markets have matured and now operate around crypto the way they would around any maturing technology sector, a wider universe of investors, more ways to source capital, more public companies, more M&A.
Advances in AI are compressing the time, cost, and complexity required to build financial applications.
I opened with Hayek’s observation that economics must demonstrate to men how little they know about what they imagine they can design. The history of financial infrastructure is largely a history of unintended consequences, of systems built to solve one coordination problem that created new fragilities requiring further intervention. But Hayek also understood the inverse: “The mind cannot foresee its own advance.” What can be built when these conditions fully converge is not yet visible, even to those building it.
The next decade will likely see more change in how financial services operate than the previous fifty years combined. Builders have the opportunity to design systems that are simpler, more resilient, and more global by default. Investors can finance real businesses built on modern infrastructure rather than abstractions layered on legacy rails. And consumers and enterprises will experience finance less as a source of friction and more as reliable infrastructure embedded in daily activity.
For the first time in decades, this opens meaningful room to redesign financial systems from the ground up.
Really incredible and thought provoking piece. Thank you for sharing it.
Brandon, this was super one. So well explained and put in perspective. Thanks a ton. For a couple of months bow, I have been wondering about Tokenization and what would it lead to. It answers some part of the question