Fintech vs. DeFi: Which financial system is more competitive?

Original Title: Report: Is Fintech or DeFi a better financial system?

Original Authors: LEX SOKOLIN, MARIO STEFANIDIS, AND JON MA

Original Translation: Peggy, BlockBeats

Editor's Note: For a long time, Fintech and DeFi have been seen as two unrelated financial systems: one is compliant, centralized, and can be valued; the other is open, runs on-chain, and resembles public infrastructure. Fintech excels at turning traffic into revenue, while DeFi excels at maximizing efficiency. As tokenization, stablecoins, and on-chain transactions continue to permeate traditional systems, the integration has become irreversible. So, will the future of finance build tollbooths on the open road, or will tollbooths eventually learn to walk the open road?

This article compares Fintech and on-chain protocols across four dimensions: revenue, scale, user numbers, and take rates, attempting to answer whether DeFi will win or Fintech will win.

Here is the original text:

Gm, Fintech architects, today we bring you some truly heavyweight content.

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

If you've ever been torn between investing in Robinhood or Uniswap, you've come to the right place.

Summary

We placed Fintech stocks and crypto tokens on the same "comparison table" for a truly meaningful side-by-side comparison.

Covering multiple sectors such as payments, digital banking, trading, lending, and prediction markets, we compared revenue, user scale, take rates, industry key metrics, and valuation metrics.

The results were quite surprising:

• Hyperliquid's trading volume has reached over 50% of Robinhood's.
• The loan scale of DeFi protocol Aave has surpassed that of buy-now-pay-later platform Klarna.
• The growth rate of stablecoin payment channels far exceeds that of traditional payment service providers.
• Wallets like Phantom and MetaMask have user scales comparable to new banks like Nubank and Revolut.

We found that valuations genuinely reflect this tension: crypto assets are either heavily discounted due to unclear monetization prospects or assigned extreme premiums due to overly high expectations.

Ultimately, we pose a core question about "integration": will the crypto world learn to build tollbooths, or will Fintech eventually adopt the open payment and settlement channels of crypto?

Subjects Involved

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

Two Financial Systems

For years, we have viewed the crypto world and Fintech as two parallel universes: one regulated, audited, and traded on NASDAQ, the other an unlicensed system where assets circulate in decentralized and centralized exchanges.

They speak the same language—revenue, trading volume, payments, lending, trading—but with entirely different "accents." And this pattern is changing.

With Stripe acquiring Bridge, Robinhood launching prediction markets, and PayPal starting to issue its own dollar stablecoin, the boundaries between the two systems are gradually blurring.

The real question is: when these two worlds truly meet and collide, how should they be placed on the same comparison table for analysis?

Comparing brokers and DEXs on the same chart. Purple represents crypto assets, green represents stocks. Robinhood ranks first in trading volume, but second is Hyperliquid…

So, we decided to conduct an experiment.

We selected familiar Fintech companies—covering payment processors, digital banks (neobanks), buy-now-pay-later (BNPL) firms, and retail brokers—and compared them with their respective crypto-native counterparts.

In the same set of charts, we used familiar Fintech metrics for comparison (such as P/S, ARPU, TPV, user numbers, etc.): green bars represent stocks, purple bars represent tokens.

Thus, a picture of the two financial systems gradually emerged: on-chain financial protocols often match or even exceed their Fintech counterparts in trading volume and asset scale; however, the economic value they capture is only a small fraction of that; compared to comparable Fintech companies, crypto assets are either extremely overpriced or deeply discounted, with almost no "middle ground"; and in terms of growth rates, the gap between the two is even more pronounced.

Payments: The "Pipelines" of Capital Flow

Let's start with the largest sector in Fintech—moving money from point A to point B.

On the green side, there are some real giants:

• PayPal: processes $1.76 trillion in payments annually.
• Adyen: processes $1.5 trillion.
• Fiserv: this "infrastructure company no one mentions at parties" processes $320 billion.
• Block (formerly Square): drives $255 billion in capital flow through Cash App and its merchant network.

These companies form the most mature and stable "capital pipeline layer" in the traditional Fintech system.

Comparison of total payment volume (TPV) between blockchain and Fintech. For the blockchain part, we estimated its B2B payment scale based on Artemis's research; for public companies, we extracted TPV data from the public financial reports of Adyen, Fiserv, and Block.

On the purple side, we have the annualized B2B payment scale estimated by Artemis's stablecoin team:

• Tron: stablecoin transfer scale of $68 billion.
• Ethereum: $41.2 billion.
• BNB Chain: $18.6 billion.
• Solana: approximately $6.5 billion.

In absolute terms, the two sides are not on the same scale. The total stablecoin transfer volume across all major public chains is only about 2% of the scale of Fintech payment processors. If you squint at that market share chart, the purple bars are almost just a rounding error.

But the truly interesting part lies in the growth rates.

PayPal's total payment volume grew only 6% last year.

Block grew 8%.

Adyen, the "darling" of Europe, achieved a 43% growth—already quite strong by Fintech standards.

Now, let's look at blockchain:

• Tron: grew 493%.
• Ethereum: grew 652%.
• BNB Chain: grew 648%.
• Solana: grew 755%, the fastest growth.

Again, these data come from Artemis's data team based on McKinsey's estimates of B2B payment scales.

TPV growth rates: our calculation method is to divide the last 12 months (LTM) TPV by the LTM TPV of the same period last year.

The results are very clear: the growth rate of this "payment channel (rails)" for stablecoins far exceeds that of traditional Fintech payment systems.

Of course, their starting points are also much smaller.

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

• Fiserv: takes 3.16% on every dollar it processes.
• Block: takes 2.62%.
• PayPal: takes 1.68%.
• Adyen: due to its lower-margin enterprise model, takes only 15 basis points (0.15%).

These are real commercial companies, and their revenues are directly and stably tied to payment volumes.

As for the blockchain side, its take rates on stablecoin transfers and more broadly on asset transfers are much lower, roughly between 1 to 9 basis points (bps). Tron covers the costs of stablecoin transfers by charging users TRX, while Ethereum, BNB Chain, and Solana charge end users gas fees or priority fees.

These public chains are very strong in facilitating transfers and promoting asset flows, but compared to traditional payment service providers, they take a much smaller percentage. Avoiding fees such as interchange and merchant fees is one of the key reasons blockchain can claim a significant efficiency advantage over existing payment systems.

Of course, there are also many on-chain payment orchestrators willing to layer additional charges on top of the base fees—this precisely constitutes a significant opportunity for "facilitators" to build economic value on top of it.

Digital Banks (Neobanks): Wallets Become New Bank Accounts

In the Fintech sector of digital banking, there are real banks (or "licensed banks"), such as Revolut, Nubank, SoFi, Chime, and Wise. These institutions have licenses, deposit insurance, and compliance departments.

On the crypto side, we see wallets and yield protocols like MetaMask, Phantom, Ethena, and EtherFi. They are certainly not "banks," but millions of people store assets here; and increasingly, more people are earning yields on their savings here. Even if the regulatory shells are different, this functional comparison still holds.

Let's start with user scale: Nubank has 93.5 million monthly active users (MAU), making it the largest digital bank in the world, a scale built on the high smartphone penetration in Brazil and the extremely complex local banking system; Revolut has 70 million users in Europe and beyond; next is MetaMask, with about 30 million users—this scale has already surpassed Wise, SoFi, and Chime.

Monthly active users (MAU) by application. MAU data for Nu, Wise, SoFi, and Chime comes from company disclosures; EtherFi's data comes from Artemis; Phantom, MetaMask, and Revolut's data comes from their public sources.

It should be noted that most MetaMask users are not using the crypto wallet to pay rent, but to interact with DEXs or participate in lending protocols. Another leading 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 public chains and has now launched its own stablecoin $CASH, debit card, tokenized stocks, and prediction market products.

Now, let's look at where the money is stored.

• Revolut: customer balances of $40.8 billion.
• Nubank: $38.8 billion.
• SoFi: $32.9 billion.

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

In the crypto world, there are also highly similar counterparts:

• Ethena: this synthetic dollar protocol that didn't exist two years ago now holds $7.9 billion.
• EtherFi: with a scale of $9.9 billion.

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

But from the user's perspective, the logic is not fundamentally different: money is placed somewhere and continues to generate yields.

Comparison of customer fund balances between Fintech and Crypto. Data for Wise, SoFi, and Nu comes from company financial disclosures; Revolut comes from public press releases; EtherFi and Ethena's data comes from Artemis.

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

• SoFi: average annual revenue of $264 per user. This is not surprising—SoFi strongly cross-sells between loans, investment accounts, and credit cards, and its user base has a higher overall income.
• Chime: average of $227 per user, with revenue mainly from interchange fees.
• Nubank: operates in Brazil, a market with a lower per capita GDP, with an average of $151 per user.
• Revolut: despite its large user base, averages only $60 per user.

What about EtherFi? An average of $256 per user, almost on par with SoFi.

The downside for this crypto newcomer is that EtherFi has only about 20,000 active users, while SoFi has 12.6 million.
In other words, this DeFi protocol has achieved monetization capabilities comparable to top digital banks on a very small user base.

Revenue over the past 12 months (LTM) / number of funded accounts. Revenue data for Revolut, Wise, Nu, Chime, and SoFi comes from public financial reports; Phantom and MetaMask's data comes from Dune.

From another perspective, MetaMask generated about $85 million in revenue last year, translating to an ARPU of about $3, even lower than Revolut's early-stage levels.

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

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

Revolut's valuation is about 18 times revenue, reflecting its market positioning and the "option value" of future expansion; EtherFi's valuation is about 13 times; Ethena is about 6.3 times, roughly at the same level as SoFi and Wise.

A rather counterintuitive conclusion is emerging: the market is treating DeFi/on-chain "banks" and traditional Fintech banks in a remarkably similar way at the valuation level.

Market cap / sales (Marketcap / Sales) of digital banks and crypto "on-chain banks." The market cap data for tokens comes from Artemis, while the market cap data for stocks comes from Yahoo Finance.

The so-called "convergence thesis" refers to the idea that wallets will eventually evolve into digital banks.

We have already seen concrete manifestations of this trend: MetaMask has launched debit cards, and Phantom has integrated fiat on- and off-ramps. The direction is clear, but it is still a work in progress.

However, when on-chain "digital banks" like EtherFi have per-user revenues higher than Revolut, the gap between the two is not as significant as the narrative suggests.

Trading: On-chain DEXs are Approaching Traditional Brokers

Switching the perspective to capital markets.

What truly surprised us is that the trading volume of on-chain exchanges can now be directly compared to traditional brokers.

Robinhood processed $4.6 trillion in trading volume over the past 12 months, primarily from stocks, options, and crypto assets, with corresponding asset scales of about $300 billion (fluctuating).

Hyperliquid's spot and perpetual contract trading volume is about $2.6 trillion, mainly driven by crypto trading, but stocks and commodities are beginning to capture market share.

Coinbase's trading volume is about $1.4 trillion, almost entirely from crypto assets.

As a "traditional player," Charles Schwab has not disclosed trading volume in the same way, but its $11.6 trillion in custodial assets clearly illustrates the scale difference between new and old money—about 40 times that of Robinhood.

This also outlines a clear contrast: on-chain trading is already approaching mainstream brokers in terms of "traffic," but in terms of "stock assets," the traditional system still holds a decisive advantage.

Trading volume data source notes: eToro, Bullish, Coinbase, and Robinhood's trading volumes come from company financial disclosures; Hyperliquid's spot + perpetual contract trading volume, as well as the trading volumes of Raydium, Uniswap, Meteora, and Aerodrome DEXs, come from Artemis.

Other decentralized exchanges are also noteworthy. For example, Uniswap, which proved the viability of automated market makers (AMMs), has trading volumes close to $1 trillion; Raydium (the leading DEX in the Solana ecosystem) has completed $895 billion; Meteora and Aerodrome together contributed about $435 billion.

In total, the processing scale of major DEXs has become comparable to Coinbase. Just three years ago, this was almost unimaginable.

Of course, we do not know how much of this trading volume is wash trading and how much is real trading; but the trend itself is what matters. Additionally, while the "convergence" of trading volumes is real, there are essential differences in take rates (take rate) between DEXs and traditional brokers.

Traditional brokers/centralized platforms:

• Robinhood: takes 1.06% per trade, mainly from payment for order flow (PFOF) and crypto spreads.
• Coinbase: about 1.03%, with high spot trading fees still relatively common in centralized exchanges.
• eToro: even so, takes 41 basis points.

DEXs 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 notable exception).

Decentralized exchanges can generate extremely high trading volumes, but due to intense competition for liquidity providers (LPs) and traders, their take rates are significantly compressed.

This is quite similar to the division of labor logic in traditional markets: real exchanges (like NASDAQ, Intercontinental Exchange) and brokers that bring clients to trading venues inherently have different functions.

Take Rate = Last 12 Months (LTM) revenue / trading volume. Revenue data for eToro, Coinbase, Robinhood, and Bullish comes from company financial reports; data for Raydium, Aerodrome, Uniswap, and Meteora comes from Artemis.

This is the paradox of DEXs.

DEXs have built trading infrastructure that can compete directly with centralized exchanges in terms of trading volume: operating 24/7, almost no downtime, no KYC required, and anyone can list tokens. However, on $1 trillion in trading volume, even with a 9 basis point take rate, Uniswap can only generate about $900 million in fees, approximately $29 million in revenue; while on $1.4 trillion in trading volume, a 1% take rate allows Coinbase to generate $14 billion in revenue.

In market valuations, this difference is accurately reflected:

• Coinbase: 7.1× sales.
• Robinhood: 21.3× (high for brokers, but supported by growth).
• Charles Schwab: 8.0× (mature multiples for mature businesses).
• 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," one important reason being that—compared to traditional brokers, their take rates are lower, and thus the economic value they can capture is also less.

Market cap / Last 12 Months (LTM) revenue. Market cap data for public companies comes from Yahoo Finance, while market cap data for tokens comes from Artemis.

From stock performance, the flow of market sentiment is clear.

Robinhood has risen about 5.7 times since the end of 2024, benefiting from a retail investor rebound and a crypto market recovery; Coinbase has risen about 20% during the same period; while Uniswap, the protocol that "spawned thousands of DEX forks," has seen its stock (token) drop by 40%.

Despite a large volume of trading continuing to flow through these DEXs, the related tokens have not captured value to the same extent, partly because their "utility" as investment tools is not clear enough.

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

Historically, DEXs have often struggled to capture value and have been viewed as a public good, but projects like Uniswap have begun to open their "fee switch"—using fees to buy back and burn UNI tokens. Currently, Uniswap's annualized revenue is about $32 million.

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

But for now, until token holders achieve a clear and direct value capture mechanism like Hyperliquid, the performance of DEX tokens will continue to lag behind that of centralized exchange (CEX) stocks.

Lending: "Underwriting" for the Next Generation Financial System

In the lending segment, the comparison becomes even more intriguing.

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

• Affirm: allows you to break a Peloton bike into four payments.
• Klarna: provides the same installment service for fast fashion.
• LendingClub: once pioneered the P2P lending model, now transformed into a real bank.
• Funding Circle: underwrites loans for small and medium-sized enterprises.

The profit logic of these companies is highly consistent: charge borrowers a higher interest rate than what is paid to depositors and hope that the default rate does not consume this interest spread.

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

Here, borrowers collateralize ETH to borrow USDC and pay an algorithmically determined interest rate; if the collateral price drops to a dangerous level, the protocol automatically liquidates—there are no collection calls, and no bad debt write-offs.

These are essentially two completely different business models, just both called "lending."

Let's start with loan scale

Aave's loan scale is $22.6 billion.

This already exceeds the sum of the following companies:

• Klarna: $10.1 billion.
• Affirm: $7.2 billion.
• Funding Circle: $2.8 billion.
• LendingClub: $2.6 billion.

The largest DeFi lending protocol's loan scale has surpassed that of the largest BNPL platform.

Take a moment to truly feel this fact.

Total loan scale data for Lending Club, Funding Circle, Affirm, Klarna, and Figure comes from company financial disclosures; lending deposit data for Euler, Morpho, and Aave comes from Artemis.

Morpho additionally added $3.7 billion. Euler, after experiencing a vulnerability attack in 2023, has restarted and currently has a scale of $861 million.

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

In traditional Fintech: Funding Circle's net interest margin is 9.35% (related to its business model being closer to private credit); LendingClub's is 6.18%; Affirm, although a BNPL company rather than a traditional lending institution, can still achieve 5.25%.

These are quite "fat" interest spreads—essentially compensation for taking on credit risk and personally conducting underwriting and risk control.

On the crypto side: Aave's net interest margin is only 0.98%; Morpho's is 1.51%; Euler's is 1.30%.

Overall, even with larger loan scales, DeFi protocols generally earn lower interest spreads than Fintech lending institutions.

Net interest margins for Aave, Euler, and Morpho are calculated as: revenue / lending deposits; net interest margins for public companies come from their financial disclosures.

DeFi lending is designed to be over-collateralized.

To borrow $100 on Aave, you typically need to provide $150 or more in collateral. The protocol itself does not bear credit risk but rather liquidation risk—this is a completely different nature of risk.
The fees paid by borrowers are essentially for leverage and liquidity, not for obtaining credit qualifications that they would otherwise not be able to access.

Fintech lending institutions, on the other hand, do the opposite. They provide unsecured credit to consumers, meeting the needs of "buy now, pay later"; the existence of interest spreads is to compensate for those who will not repay at all.

This will be directly reflected in the data on actual losses caused by defaults, and managing these default risks is the core work of underwriting and risk control.

Credit loss ratio data for public companies comes from public financial reports.

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

Fintech lending serves those borrowers who currently have no money but wish to consume first, thus must bear real underwriting and default risks. This is a brutal business. The early batch of digital lending institutions (like OnDeck, LendingClub, Prosper) have often hovered on the "edge of death."
Even if Affirm's business itself operates well, its stock price has still fallen about 60% from its historical peak—often because the market prices its credit income using a SaaS valuation logic without fully accounting for the inevitable future credit losses.

DeFi lending is essentially a leveraged business.

It serves not "cash-strapped individuals," but users who already hold assets but do not want to sell them, only seeking liquidity, more like a margin account. There are no traditional credit decisions here; the only judgment criterion is the quality of the collateral.

This model is capital efficient, highly scalable, earning very thin spreads at a massive scale; but it also has clear applicability boundaries—it only works for those who are already on-chain and hold significant assets, wishing to earn yields or additional leverage without selling their assets.

Prediction Markets: Who Can Say for Sure?

Finally, let's look at prediction markets.

This is the latest battleground between Fintech and DeFi, and also the most peculiar one. For decades, they have merely been academic "oddities": economists love them, but regulators avoid them.

Iowa Electronic Markets once operated on a small scale for election predictions; Intrade briefly thrived before being shut down; more projects have been directly classified as gambling or sports betting.

"The idea that trading the outcomes of real-world events can yield better predictions than polls or commentators"—this concept has long remained theoretical.

All of this changed in 2024 and accelerated during Trump's second term: Polymarket processed over $1 billion in election bets; Kalshi won a lawsuit against the CFTC and began offering political contracts to U.S. users; Robinhood, as always, was eager not to miss any trend, quickly launched event contracts; DraftKings, which has effectively been running a form of prediction market through daily fantasy sports, sat on the sidelines with a market cap of $15.7 billion and annual revenue of $5.5 billion.

Prediction markets have finally moved from the fringes to the center stage of finance and crypto.

Spot trading volume data for Kalshi and Polymarket comes from Artemis; DraftKings' "trading volume" uses its Sportsbook Handle metric, which is the total amount of user bets settled in its sports betting products.

This sector has rapidly transitioned from a niche experiment to mainstream in about 18 months—the weekly trading volume of prediction markets has reached about $7 billion, setting a new historical high.

DraftKings had a trading volume of $51.7 billion over the past 12 months; Polymarket reached $24.6 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. domestic alternative, had a trading volume of $9.1 billion.

From a trading volume perspective, Polymarket is already quite competitive. It has built a liquidity-rich, globally covering prediction market on Polygon, while Kalshi is still navigating the courts for compliance qualifications.

However, when we turn to revenue, the comparison starts to become unbalanced.

DraftKings achieved $5.46 billion in revenue last year; Kalshi only $264 million; Polymarket, after opening taker fees for 15-minute periods in the crypto market, achieved an annualized revenue run rate of about $38 million.

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

Revenue comparison of prediction markets. Polymarket's revenue data comes from Artemis; Kalshi's revenue comes from public sources; DraftKings' LTM revenue comes from company financial reports.

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

• DraftKings: takes 10.57% on every dollar bet. This is a typical sports betting model—setting odds, providing payouts, and managing risks to obtain considerable shares.
• Kalshi: takes 2.91%, which is lower and more aligned with its positioning as a financialized exchange model.
• Polymarket: only 0.15%. With a trading volume of $24.6 billion, the revenue it can capture is currently very limited.

The conclusion is straightforward: the differentiation in prediction markets does not lie in "scale," but in "fee structures."

Take Rate = Last 12 Months (LTM) revenue / trading volume.

This is almost a replay of DEX logic.

Polymarket has not focused on value capture but rather on providing infrastructure for prediction markets: matching buyers and sellers and completing contract settlements on-chain. It does not employ odds makers, does not manage balance sheets, and does not stand on the opposite side of your bets. The efficiency is indeed remarkable, but monetization is not the current core goal.

However, investors clearly believe that Polymarket will eventually achieve monetization, with a valuation of about $9 billion, corresponding to a 240 times sales multiple;

Kalshi, with a valuation of $11 billion and $264 million in revenue, trades at about 42 times;

DraftKings has a sales multiple of only 2.9 times.

Venture capital firms are almost relentless in pouring money into these platforms, while traditional players like DraftKings and Flutter Entertainment (which owns FanDuel) are seeing their stock prices continue to face pressure.

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

Valuations for Kalshi and Polymarket are based on the latest round of private equity valuations; DraftKings' valuation comes from Yahoo Finance.

Polymarket's valuation implies one of two possibilities: either it will massively open the monetization switch in the future, or it will evolve into something much larger than just a "prediction market." At over 200 times revenue multiples, what you are buying is not a mature business, but a call option on a new financial vernacular.

Perhaps Polymarket will become the default trading venue for hedging any real-world events; perhaps it will cover more sports, earnings reports, weather, or any binary outcome events; perhaps it will raise its take rate from 0.15% to higher levels, and revenue could leap to billions overnight.

This is the purest form of the "convergence question": in the future, will it belong to regulated exchanges with clear take rates and compliance departments? Or will it belong to protocols that require no permission, allowing anyone to bet on any event anywhere, with "the house taking almost no cut"?

The Convergence

A few years ago, we could not put DeFi and Fintech on the same table for direct comparison. But now, we stand here.

The crypto world has built a financial infrastructure that can match Fintech in trading volume, user scale, and asset size: the globalization of stablecoin channels exceeds that of traditional payment institutions; Aave's loan scale surpasses that of Klarna; Polymarket's trading volume is comparable to that of DraftKings. The technology is feasible, and the products have found a sufficiently large user base. But the question lies in value capture.

In every category we examined, the conclusions are highly consistent: compared to traditional Fintech, the take rates in the crypto system are lower, and thus the economic value captured is also less.

Crypto builds the most efficient and 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 has merely accelerated this inevitable process; if you believe that businesses must rely on revenue to survive, then most tokens still face severe challenges in value capture.

Regardless, convergence is already happening: banks are starting to pilot tokenized deposits; the New York Stock Exchange is exploring tokenized stock trading; the total supply of stablecoins has reached a new high of over $30 billion.

Established giants in Fintech have recognized the trend—they will not ignore it but will absorb it.

The question for the next decade is actually quite simple: will crypto learn to build tollbooths, or will Fintech learn to walk the crypto path?

Our judgment is: both will happen.