Fintech vs. DeFi: Which Financial System is More Competitive?

Original Title: Report: Is Fintech or DeFi a better financial system?
Original Author: LEX SOKOLIN, MARIO STEFANIDIS, AND JON MA
Translation: Peggy, BlockBeats

Editor's Note: For a long time, Fintech and DeFi have been seen as two separate and unrelated financial systems: one compliant, centralized, and valuative; the other open, on-chain, more like public infrastructure. Fintech excels at turning traffic into revenue, while DeFi excels at maximizing efficiency. With tokenization, stablecoins, and on-chain transactions increasingly permeating the traditional system, the integration is now irreversible. So, for the future of finance, is it about establishing toll booths on the open road, or letting toll booths eventually learn to walk the open path?

This article compares Fintech and Onchain Protocols in terms of income, scale, user base, and fee rate, attempting to answer whether DeFi will win or Fintech will win?

The following is the original text:

Good morning, Fintech architects, today we bring you a truly heavyweight piece.

We have partnered with the analytics company Artemis (referred to as the "Bloomberg Terminal of the digital finance industry") to officially release the first-ever comparative analysis of key indicators (KPIs) between Fintech and DeFi.

If you have ever been torn between: which is a better investment, Robinhood or Uniswap, then you are in the right place.

Abstract

We have put fintech stocks and crypto tokens on the same "table" for a truly meaningful side-by-side comparison.

Covering multiple tracks such as payments, digital banking, trading, lending, prediction markets, etc., we compared income, user base, fee rate (take rate), industry key metrics, and valuation metrics.

The results are quite surprising:

Hyperliquid's trading volume has exceeded 50% of Robinhood's

The lending volume of the DeFi protocol Aave has surpassed that of the Buy Now, Pay Later platform Klarna

The growth rate of stablecoin payment channels far outpaces that of traditional payment service providers

The user base of wallets such as Phantom and MetaMask is now comparable to that of new-age banks like Nubank and Revolut

We find that valuations truly reflect this tension: crypto assets are either heavily discounted due to the lack of clarity on "how they will monetize in the future," or they are given an extreme premium due to high expectations.

Ultimately, we pose a fundamental question about "integration": will the crypto world learn to set up tollbooths, or will fintech eventually embrace the open payment and settlement rails of crypto?

Entities Mentioned

Block, PayPal, Adyen, Tron, Solana, Coinbase, Robinhood, Uniswap, Aave, Affirm, Klarna, Polymarket, DraftKings

Two Financial Systems

For years, we have always seen the crypto world and fintech as two parallel universes: one regulated, audited, and traded on NASDAQ, while the other is a permissionless system where assets move between decentralized and centralized exchanges.

They use the same set of languages—revenue, volume, payments, lending, trading—but with entirely different "accents." And this landscape is changing.

With Stripe acquiring Bridge, Robinhood launching prediction markets, and PayPal starting to issue its own USD stablecoin, the boundaries between these two systems are becoming increasingly blurred.

The real question is: when these two worlds truly collide and clash, how should they be juxtaposed and compared on the same chart?

Comparing a brokerage with a DEX on the same chart. Purple represents crypto assets, green represents stocks. Robinhood leads in trading volume, but second is Hyperliquid...

So, we decided to conduct an experiment.

We took familiar fintech companies—encompassing payment processors, digital banks (neobanks), BNPL firms, and retail brokerages—and juxtaposed them with their respective crypto-native counterparts one by one.

In the same chart group, we compare using familiar fintech metrics (such as P/S, ARPU, TPV, user count, etc.): Green bars represent stocks, purple bars represent tokens.

Thus, a picture of two financial systems gradually emerges: On-chain financial protocols, in terms of transaction volume and asset scale, often can match or even exceed their fintech peers; however, the economic value they capture is only a small part of it; compared to comparable fintech companies, the pricing of crypto assets is either extremely overvalued or significantly undervalued, with hardly any "middle ground"; and in terms of growth rate, the gap between the two is even more stark.

Payments: The "Pipeline" of Fund Flows

Let's start with the largest track in fintech in terms of volume — moving money from point A to point B.

On the green side, there are some true giants:

PayPal: processing a $1.76 trillion payment volume annually

Adyen: processing $1.5 trillion

Fiserv: the "infrastructure company that nobody talks about at parties," processing $320 billion

Block (formerly Square): driving $255 billion in fund flows through Cash App and its merchant network

These companies constitute the most mature and stable "fund pipes" in the traditional fintech system.

Comparison of Total Payment Volume (TPV) between Blockchain and Fintech. For the blockchain part, we estimate its B2B payment volume based on Artemis's research; for public companies, we extract TPV data from Adyen, Fiserv, and Block's public financial reports.

On the purple side, there is the annualized B2B payment volume estimated by the Artemis stablecoin team:

Tron: Stablecoin transfer volume of $680 billion

Ethereum: $412 billion

BNB Chain: $186 billion

Solana: around $65 billion

In absolute terms, the two sides are not in the same league. The total stablecoin transfer volume on all major public chains is roughly equivalent to only 2% of the fintech payment processor's scale. If you squint at that market share chart, the purple bars are almost just a rounding error.

But the real interesting part is — the growth rate.

PayPal saw only a 6% increase in total payment volume last year

Block saw 8% growth

Adyen, the European darling, achieved a 43% growth — quite strong by fintech standards

Now, looking at blockchain:

Tron: 493% growth

Ethereum: 652% growth

BNB Chain: 648% growth

Solana: 755% year-over-year growth, the fastest

Again, these figures are from the Artemis data team based on McKinsey research estimates of B2B payment volumes.

TPV Growth Rate: Our calculation method is to take the trailing-twelve-month (TTM) TPV and divide it by the previous year's TTM TPV.

The results are quite clear: the growth rate of stablecoins on this "payment rail" system is far outpacing that of traditional fintech payment systems.

Of course, their starting point is also much smaller.

Next, the question becomes: who is truly capturing economic value?

Fiserv: Extracts 3.16% for every dollar it handles

Block: Extracts 2.62%

PayPal: Extracts 1.68%

Adyen: Due to its lower-margin enterprise model, only takes 15 basis points (0.15%)

These are all real, existing businesses, with their revenue directly and steadily tied to payment volume.

On the blockchain side, the take rate for stablecoin transfers and broader asset transfers is much lower, typically around 1–9 basis points (bps). Tron covers stablecoin transfer costs by charging users in TRX, while Ethereum, BNB Chain, and Solana charge end users gas fees or priority fees.

These public blockchains are very strong in facilitating transfers and driving asset movement, but they extract a much smaller percentage compared to traditional payment service providers. Avoiding interchange fees and merchant fees is a key reason why blockchain can claim significant efficiency advantages over the existing payment system.

Of course, there are also many on-chain payment orchestrators willing to continue layering fees on top of base fees — providing a significant opportunity for "facilitators" to build economic value on top of it.

Neobanks: Wallets Becoming the New Bank Accounts

In the fintech arena of digital banking, there are true banks (or "license-as-a-service" banks), such as Revolut, Nubank, SoFi, Chime, Wise. These institutions have licenses, deposit insurance, and compliance departments.

On the crypto side, we see wallets and yield protocols, such as MetaMask, Phantom, Ethena, EtherFi. They are not, of course, "banks," but millions of people entrust their assets here; and more and more people are earning interest on their savings here. Even though the regulatory shell is different, this functional comparison still holds.

Starting with user scale: Nubank has 93.5 million monthly active users (MAU), making it the largest digital bank globally, built upon Brazil's high smartphone penetration and extremely complex local banking context; Revolut has 70 million users in Europe and other regions; next is MetaMask with around 30 million users — a scale that has surpassed Wise, SoFi, and Chime.

Monthly Active Users (MAU) broken down by app. MAU data for Nu, Wise, SoFi, Chime is from company disclosure documents; EtherFi data is from Artemis; Phantom, MetaMask, Revolut data are from their respective public sources.

It is important to note that most MetaMask users are not using the crypto wallet to pay rent but to interact with DEXs or participate in lending protocols. Another top wallet, Phantom, has 16 million monthly active users. Phantom was initially positioned as the best wallet experience in the Solana ecosystem but quickly expanded to multiple blockchains, now offering its own stablecoin $CASH, debit cards, tokenized stocks, and prediction markets.

Now let's see where the money is.

Revolut: Customer Balances $408 Billion

Nubank: $388 Billion

SoFi: $329 Billion

These are real deposits generating net interest income for the institutions.

In the crypto world, there are similar corresponding relationships:

Ethena: This synthetic dollar protocol, which didn't exist two years ago, now holds $79 billion

EtherFi: Scaling to $99 billion

These are not "deposits" but rather staked assets, yield-bearing positions, or liquidity parked in smart contracts—referred to as TVL (Total Value Locked) in industry terms.

However, from a user's perspective, the logic is fundamentally the same: money is placed somewhere and continues to generate returns.

Comparison of Fintech/Crypto Customer Fund Balances. Data for Wise, SoFi, and Nubank is from company financial disclosures; Revolut data is from a public press release; EtherFi and Ethena data is from Artemis.

The real difference lies in how these platforms monetize "base money" and how much they can earn from users.

SoFi: Per-user annual revenue of $264. This is not surprising—SoFi engages in strong cross-selling between loans, investment accounts, and credit cards, and the user base has a higher overall income.

Chime: $227 per user, with revenue mainly coming from interchange fees.

Nubank: Operating in the low GDP per capita Brazilian market, $151 per user.

Revolut: Despite its large user base, only $60 per user.

And EtherFi? $256 per user, almost on par with SoFi.

What disadvantages EtherFi is that its active user base is only about 20,000, while SoFi has 12.6 million.
In other words, this DeFi protocol has achieved monetization efficiency similar to a top-tier digital bank with a massive user base on an extremely small user base.

Last Twelve Months (LTM) Revenue / Funded Account Count. Revenue data for Revolut, Wise, Nu, Chime, and SoFi is from public financial reports; data for Phantom and MetaMask is from Dune.

Looking at it from a different angle, MetaMask generated about $85 million in revenue last year, equating to an ARPU of about $3, even lower than Revolut's early-stage level.

Although Ethena has a TVL of $7.9 billion, its user reach is still only a fraction of Nubank's.

Valuation is a direct reflection of this "growth vs. monetization ability" binary tension.

Revolut's valuation is about 18 times revenue, a pricing that reflects its market positioning and the "option value" of future expansion; EtherFi's valuation is about 13 times; Ethena around 6.3 times, roughly on par with SoFi and Wise.

An somewhat counterintuitive conclusion is emerging: the market, at the valuation level, is treating DeFi / on-chain "banks" and traditional fintech banks in a fairly similar manner.

Market Cap / Sales of Digital Banks and Crypto "On-Chain Banks." Token market cap data is from Artemis, stock market cap data is from Yahoo Finance.

The so-called "convergence thesis" refers to: wallets will ultimately evolve into digital banks.

We have already seen a concrete manifestation of this trend: MetaMask launched a debit card, Phantom integrated fiat on/off ramps. The direction is clear, but we are still on the way.

But when on-chain "digital banks" like EtherFi have per capita income higher than Revolut, the gap between the two is not as narratively significant as it once seemed.

Transaction: On-chain DEX Approaching Traditional Brokerages

Shifting our focus to the capital markets.

What truly surprises us is this: the trading volume on on-chain exchanges has reached a level comparable to traditional brokerages.

Robinhood processed $4.6 trillion in trading volume over the past 12 months, mainly from stocks, options, and crypto assets, with an associated asset under management of approximately $3 trillion (give or take).

Hyperliquid's spot and perpetual contract trading volume is around $2.6 trillion, primarily being crypto-driven, but stocks and commodities are starting to gain market share.

Coinbase saw around $1.4 trillion in trading volume, nearly all from crypto assets.

As a "traditional force," Charles Schwab did not disclose its trading volume in the same manner, but its $11.6 trillion in assets under custody is enough to illustrate the vast difference in scale between new and old money — roughly 40 times that of Robinhood.

This also outlines a clear comparison: on-chain transactions have already approached mainstream brokerages in terms of "transaction volume," but in terms of "existing assets," the traditional system still holds overwhelming dominance.

Transaction volume data sources: Trading volumes for eToro, Bullish, Coinbase, and Robinhood are from company financial disclosures; Spot + perpetual contract trading volume for Hyperliquid, as well as trading volumes for DEXs like Raydium, Uniswap, Meteora, Aerodrome, are sourced from Artemis.

Other decentralized exchanges are equally significant. For example, Uniswap, a protocol that has demonstrated the feasibility of automated market makers (AMMs), has a trading volume close to $1 trillion; Raydium (the leading DEX in the Solana ecosystem) has achieved $895 billion; and Meteora and Aerodrome together have contributed approximately $435 billion.

Overall, the processing scale of major DEXs is now comparable to Coinbase. And three years ago, this was nearly unimaginable.

Of course, we do not know how much of this trading volume is wash trading and how much is legitimate trading. Nevertheless, the trend itself is key. Furthermore, while volume "convergence" is indeed real, DEXs and traditional brokerages differ fundamentally in their take rate.

Traditional Brokerage / Centralized Platforms:

Robinhood: 1.06% per trade, primarily from Payment for Order Flow (PFOF) and crypto spread

Coinbase: Around 1.03%, high spot trading fees are still common in centralized exchanges

eToro: Yet it takes 41 basis points

DEXs, on the other hand, operate in a completely different universe:

Hyperliquid: 3 basis points

Uniswap: 9 basis points

Aerodrome: 9 basis points

Raydium: 5 basis points

Meteora: 31 basis points (a clear outlier)

Decentralized exchanges can achieve very high trading volumes, but due to intense competition among liquidity providers (LPs) and traders, their take rate is significantly suppressed.

This is quite similar to the division of labor in traditional markets: true exchanges (such as NASDAQ, Intercontinental Exchange) and the brokerages bringing clients to the exchange already perform different functions.

Take Rate = Last Twelve Months (LTM) Revenue / Trading Volume. Revenue data for eToro, Coinbase, Robinhood, Bullish is from company financial reports; data for Raydium, Aerodrome, Uniswap, Meteora is from Artemis.

This is the DEX paradox.

DEXs have built a trading infrastructure that can compete head-on with centralized exchanges in terms of volume: running 24/7, almost zero downtime, no need for KYC, and anyone can list tokens. However, at $1 trillion in trading volume, even with a 9 basis point fee, Uniswap can only generate about $900 million in fees, around $29 million in revenue; whereas at $1.4 trillion in trading volume, a 1% take rate allows Coinbase to generate $140 billion in revenue.

On market valuation, this difference is accurately reflected:

Coinbase: 7.1× Sales

Robinhood: 21.3× (relatively high for a brokerage but supported by growth)

Charles Schwab: 8.0× (mature multiple for a mature business)

Uniswap: 5.0× Fees

Aerodrome: 4.8× Fees

Raydium: 1.3× Fees

The conclusion is not complicated: the market has not priced these protocols as "high-growth tech companies," primarily because, compared to traditional brokerages, their fee rates are lower, resulting in less captured economic value.

Market Cap / Last Twelve Months (LTM) Revenue. Market cap data for public companies is from Yahoo Finance, and token market cap data is from Artemis.

From the stock price performance, the direction of market sentiment is clear.

Robinhood has risen approximately 5.7x since the end of 2024, benefiting from a resurgence in retail investing and the rebound in the crypto market; Coinbase has risen about 20% over the same period; meanwhile, Uniswap, the protocol that "spawned thousands of DEX forks," saw its stock price (token) fall by 40%.

Although a significant amount of trading volume continues to flow through these DEXs, the related tokens have not captured an equivalent value, partly because their "utility" as investment vehicles is not clear enough.

The only exception is Hyperliquid. Due to its explosive growth, Hyperliquid's performance has almost mirrored Robinhood's, achieving similar gains during the same period.

Although historically DEXs have often struggled to capture value and have been seen as a public good, projects like Uniswap have begun to open their "fee switch"—using fees for token buybacks and burns. Currently, Uniswap's annualized revenue is around $32 million.

We remain optimistic about the future: as more and more trading volume shifts to on-chain, value is expected to gradually flow back into DEX tokens themselves, with Hyperliquid being a successful example.

However, as of now, until token holders have not experienced a clear and direct value capture mechanism similar to Hyperliquid, the performance of DEX tokens will still lag behind stock from centralized exchanges (CEX).

Lending: Doing "Underwriting" for the Next Financial System

At the lending stage, the comparison becomes even more intriguing.

On one side is the core business of fintech—unsecured consumer credit:

Affirm: Allows you to split a Peloton bike into four installment payments

Klarna: Provides similar installment services for fast fashion

LendingClub: Once pioneered the P2P lending model, later transformed into a true bank

Funding Circle: Underwrites loans for small and medium-sized enterprises

These companies share a highly consistent revenue logic: the interest charged to borrowers is higher than the cost paid to depositors, and they pray that the default rate will not swallow this interest differential.

On the other side is collateralized DeFi lending: Aave, Morpho, Euler

Here, borrowers collateralize ETH, borrow USDC, and pay an interest rate determined by the algorithm; once the collateral's price drops to a risky level, the protocol automatically liquidates—there are no collection calls, nor bad debt write-offs.

These are fundamentally two completely different business models that just happen to be called "lending."

Let's Start with Loan Size

Aave's loan size is $22.6 billion

This already surpasses the sum of the following companies:

Klarna: $10.1 billion

Affirm: $7.2 billion

Funding Circle: $2.8 billion

LendingClub: $2.6 billion

The loan size of the largest DeFi lending protocol has exceeded that of the largest BNPL platform.

Pause for a moment and seriously consider this fact.

Lending Club, Funding Circle, Affirm, Klarna, and Figure's total loan size data is from company financial disclosures; Euler, Morpho, Aave's lending deposit data is from Artemis.

Morpho has additionally added $3.7 billion. Euler, after a vulnerability incident in 2023, has restarted and currently stands at $861 million.

Overall, the DeFi lending system has developed in about four years to a scale large enough to rival the entire listed digital lending industry — but its economic structure is inverted.

On the traditional FinTech side: Funding Circle has a Net Interest Margin of 9.35% (related to its closer-to-private-credit business model); LendingClub is at 6.18%; Affirm, although a BNPL company rather than a traditional lending institution, still manages 5.25%.

These are quite "fat" interest rate spreads — essentially a compensation for credit risk-taking, personal credit assessment, and underwriting they undertake.

While on the crypto side: Aave's Net Interest Margin is only 0.98%; Morpho is at 1.51%; Euler at 1.30%.

Overall, despite having a larger loan volume, DeFi protocols generally earn a lower interest rate spread compared to FinTech lending institutions.

The Net Interest Margin calculation method for Aave, Euler, and Morpho is: Income / Loaned Deposits; the Net Interest Margin of listed companies comes from their financial report disclosures.

DeFi lending is designed to be overcollateralized.

When borrowing $100 on Aave, one typically needs to provide $150 or even more in collateral. The protocol itself does not take on credit risk but takes on liquidation risk — this is an entirely different type of risk.
The fees paid by borrowers are essentially for leverage and liquidity, not for obtaining creditworthiness that was originally unattainable.

FinTech lending institutions, on the other hand, are precisely the opposite. They provide unsecured credit to consumers, meeting the "buy now, pay later" demand; the existence of interest spreads is to compensate for those who will never repay.

This point will be directly reflected in actual loss data caused by defaults, and how to manage these default risks is the core work of credit assessment and underwriting.

The credit loss ratio of listed companies is based on public financial reports.

So, which model is better? The answer depends on what goal you want to optimize for.

Financial technology lending serves those who do not have money at the moment but wish to consume first, thus they must bear real credit and default risks. This is a harsh business. Early digital lending institutions (such as OnDeck, LendingClub, Prosper) have all teetered on the edge of "near-death" multiple times.
Even if Affirm's business itself is doing well, its stock price has dropped by about 60% from its historical high—often because the market prices its credit income using SaaS valuation logic, without fully accounting for inevitable future credit losses.

DeFi lending is essentially a leveraged business.

It does not serve the "poor," but rather users who already hold assets, do not want to sell, and just want to gain liquidity, more like a margin account. There is no traditional credit decision-making here, and the only judgment criterion is the quality of the collateral.

This model is highly capital efficient, with strong scalability, earning a very thin spread on a massive scale; but it also has obvious boundaries—it is only useful for those already on-chain, holding a large amount of assets, hoping to earn returns or additional leverage without selling their assets.

Prediction Markets: Who Knows?

Finally, let's look at Prediction Markets.

This is the latest battlefield between Fintech and DeFi, and also the most peculiar one. For decades, they have always been seen as mere "oddballs" in an academic sense: economists love them, but regulators steer clear.

Iowa Electronic Markets once operated small-scale election predictions; Intrade briefly thrived and was then shut down; more projects have been directly classified as gambling or sports betting.

The idea that "trading the outcomes of real-world events and that these markets can provide better forecasts than polls or pundits" has long remained at the theoretical level.

All of this changed in 2024, accelerating during Trump's second term: Polymarket processed over $1 billion in election bets; Kalshi won a lawsuit against the CFTC, starting to offer political contracts to U.S. users; Robinhood, as always reluctant to miss any trend, quickly launched event contracts; DraftKings, having essentially run a prediction market through daily fantasy sports, watched from the sidelines, holding a $15.7 billion market cap and $5.5 billion in annual revenue.

Prediction markets have finally transitioned from a niche experiment to the central stage of the financial and crypto world.

Kalshi and Polymarket spot volume data is sourced from Artemis; DraftKings' "volume" uses its Sportsbook Handle metric, which is the total amount of user bets settled in its sports betting product.

This race has rapidly moved from a niche experiment to the mainstream in about 18 months—weekly trading volume in prediction markets has reached around $7 billion, hitting a new all-time high.

Over the past 12 months, DraftKings had a trading volume of $517 billion; Polymarket reached $246 billion, about half of DraftKings', yet it remains a crypto-native protocol theoretically not allowed for U.S. users; Kalshi, as a compliant U.S.-based alternative, had a trading volume of $91 billion.

Based solely on trading volume, Polymarket is quite competitive. It has built a liquid, globally covered prediction market on Polygon, while Kalshi is still navigating the courts for compliance.

But when we look at revenue, the comparison starts to skew.

DraftKings achieved $54.6 billion in revenue last year; Kalshi only $264 million; Polymarket, on the other hand, achieved an annualized revenue run rate of around $38 million only after opening up taker fees for 15-minute period crypto markets.

This once again reveals a familiar divide: in terms of "scale," DeFi has caught up; but in terms of "monetization," traditional finance and betting companies still hold overwhelming advantages.

Prediction market revenue comparison. Polymarket revenue from Artemis; Kalshi revenue from public sources; DraftKings LTM revenue from company financials.

The core of the difference lies in the take rate — in the sports betting context, also known as the "hold."

DraftKings: takes a 10.57% cut for every dollar bet. This is a typical sports betting model — bookmakers set the odds, provide odds, and manage the risk to take a substantial cut.

Kalshi: takes a 2.91% cut. As a financialized exchange model, this level is lower and more in line with its positioning.

Polymarket: only 0.15%. With a $246 billion trading volume, the current revenue capture is very limited.

The conclusion is straightforward: the differentiation of prediction markets lies not in "scale" but in "fee structures."

Take Rate = Last Twelve Months (LTM) Revenue / Trading Volume.

This is almost a replay of DEX logic.

Polymarket does not focus on capturing value but instead concentrates on providing infrastructure for prediction markets: matching buyers and sellers and settling contracts on-chain. It does not employ oddsmakers, manage a balance sheet, or stand on the opposite side of your bet. The efficiency is indeed remarkable, but monetization is not the current primary goal.

However, investors evidently believe that Polymarket will eventually achieve monetization, with Polymarket valued at around $9 billion, corresponding to a 240x sales multiple;

Kalshi, valued at $11 billion, with $264 million in revenue trading, around 42x;

The market cap of DraftKings is only 2.9 times its sales.

Venture capital firms can't seem to stop pouring money into these platforms at a rapid pace. Meanwhile, "traditional players" like DraftKings and Flutter Entertainment (owner of FanDuel) see their stock prices continuously under pressure.

This once again confirms a familiar signal: capital is paying a premium for "potential future monetization" rather than footing the bill for current profits.

The market caps of Kalshi and Polymarket are based on their latest round of private valuation; DraftKings' market cap is from Yahoo Finance.

Polymarket's valuation implies one of two possibilities: either it will massively unlock the monetization switch in the future, or it will evolve into something much larger than just a "prediction market." At a revenue multiple of over 200 times, what you're buying is not a mature company but a call option on a brand-new financial lingua franca.

Perhaps, Polymarket will become the default venue for hedging any real-world event; perhaps, it will expand to cover more sports, earnings reports, weather, or any binary outcome event; perhaps, it will increase its fee from 0.15% to a higher level, and its revenue will skyrocket to tens of billions overnight.

This is the purest form of "the convergence": in the future, will it belong to a regulated exchange with a clear fee structure and compliance department? Or will it belong to a permissionless protocol where anyone can bet on anything, anywhere, with the "house" taking minimal cuts?

The Convergence

A few years ago, we couldn't even compare DeFi and Fintech on the same positive note. But now, here we are.

The crypto world has built a set of financial infrastructures that can rival fintech in terms of trading volume, user base, and asset size: the global reach of stablecoin channels exceeds that of traditional payment institutions; Aave's loan volume surpasses Klarna's; Polymarket's trading volume rivals DraftKings'.

The technology is viable, the products have found a large enough user base. But the issue lies in value capture.

In every category we examined, the conclusion was remarkably consistent: compared to traditional fintech, the crypto system has a lower extraction rate, resulting in less captured economic value.

Crypto is building the most efficient, open infrastructure at the cost of distributing value more broadly.

Whether this is a bug or a feature depends on your perspective: if you believe that financial services will ultimately evolve into commoditized public utilities, then crypto is simply accelerating this inevitable process; if you think that companies need to rely on revenue to survive, then most tokens still face significant challenges in capturing value.

Regardless, the convergence is already happening: banks are starting to pilot tokenized deposits; the New York Stock Exchange is exploring tokenized stock trading; the total stablecoin supply has hit a new high of over $300 billion.

Existing fintech giants have recognized the trend—they will not ignore it but instead absorb it.

The question for the next decade is actually quite simple: Will crypto learn toll booth economics, or will fintech learn the crypto way?

Our assessment is: Both will occur.

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