Key takeaways

• HYPE trades below $59 after recording a second consecutive day of gains.
• The Hyperliquid Policy Center and trade[XYZ] have submitted recommendations on pre-IPO perpetual markets to the SEC.
• The proposed instruments would provide price exposure before a company lists publicly without granting shares or investor rights.

Hyperliquid (HYPE) trades above $58 on Wednesday, extending its recovery for a second consecutive session as buyers target a breakout above the psychological $60 level.

The decentralized exchange’s native token maintains a broadly bullish technical structure above its major moving averages. Momentum indicators are also improving without suggesting that the rally has become excessively stretched.

The advance comes as the Hyperliquid Policy Center and trade[XYZ] urge the US Securities and Exchange Commission to establish rules that would allow American investors to access pre-IPO perpetual markets.

Hyperliquid submits pre-IPO market proposal to SEC

The Hyperliquid Policy Center and trade[XYZ], a prominent deployer of perpetual markets on Hyperliquid, jointly submitted a comment letter responding to the SEC’s request for proposals to modernize the Initial Public Offering process.

Their letter highlighted the pricing history of at least five trade[XYZ] pre-IPO perpetual, or IPOP, markets that completed their full lifecycle on Hyperliquid.

The organizations argued that these markets can provide transparent, continuously updated price signals before a company’s shares begin trading publicly.

They also outlined regulatory questions the SEC would need to address before permitting similar products in the United States.

An IPOP is a financial instrument that allows traders to take a directional position on a company’s expected valuation ahead of a scheduled stock market listing.

The contract provides price exposure during the period before the company’s shares become publicly tradable. Prices update continuously based on market demand, potentially offering investors and issuers an early indication of expected listing value.

However, an IPOP is not equivalent to owning pre-IPO equity.

Contract holders do not receive actual shares, allocation rights or voting power. They also have no direct claim against the company referenced by the instrument. The product is designed solely to provide exposure to anticipated price movements ahead of a public listing.

Hyperliquid’s policy organization said American investors are unable to access price opportunities available to traders in other jurisdictions.

It cited SpaceX as an example, saying its pre-IPO perpetual market was priced at $135 before the company listed at $150.

According to the organization, the market provided a visible pricing signal, but US investors had no regulated way to trade it.

Under a new SEC framework, Hyperliquid argued, both American investors and issuers could benefit from the price discovery offered by pre-IPO markets.

Supporters may view such instruments as a way to broaden market access. However, the products could expose retail traders to substantial risks, including leverage, uncertain valuation, limited disclosure and price manipulation before public-market data becomes available.

HYPE maintains bullish structure above major EMAs

HYPE trades at approximately $58.73, retaining a constructive technical outlook. The token remains above its 50-day, 100-day, and 200-day Exponential Moving Averages (EMAs). 

This bullish alignment places all three indicators below the current price and provides several potential layers of support.

The Moving Average Convergence Divergence indicator has moved firmly into positive territory, signaling strengthening upside momentum.

Meanwhile, the Relative Strength Index stands near 56. The reading indicates steady buying pressure but remains well below the conventional overbought threshold of 70, leaving room for additional gains.

Immediate support sits at the 50-day EMA around $58.33. Holding this level would preserve HYPE’s near-term bullish structure and support another attempt to clear $60.

Below it, the 100-day EMA at $56.76 represents the next support area. A deeper decline could bring the 200-day EMA at $51.68 into focus as the more important longer-term bullish threshold.

On the upside, a descending resistance trendline remains the main structural obstacle. A sustained daily close above this trendline and the $60 region could confirm a breakout and allow HYPE to extend its recovery.

Failure to clear the resistance zone could encourage profit-taking and push the token back toward the clustered EMA support levels.

For now, the stacked moving averages and positive momentum indicators favor buyers, but HYPE requires a confirmed trendline breakout to strengthen its broader bullish outlook.

Australian tech firm Apate deploys a vast array of AI-bot characters worldwide that play the role of gullible scam victims to waste millions of hours of con artists’ time each month.

Hilariously, one of the company’s monthly performance metrics is how many times frustrated scammers swear at the idiot ‘victims’ who are playing dumb and stringing them along.

“I think we’re the only company in the world that is actually keeping as part of their KPIs the number of F-words that scammers are dropping at them,” Apate founder Dali Kaafar tells Magazine with a chuckle. 

The company has a stable of almost 200,000 AI characters that are able to hold convincing phone conversations and to chat on social media and messaging platforms.

”I can tell you that we’re basically servicing, as we call them, hundreds of thousands of calls a day, and pretty much hundreds of thousands of conversations on the other channels,” he says. 

Every hour of a con artist’s time they waste is another hour they’re not scamming a member of the public. In the six weeks up to the end of 2025, Apate’s bots engaged in 600,000 scam calls for a single telco called TPG in Australia. 

“Essentially, we wasted more than five hundred days of scammers’ time,” he explains. “That roughly equates to somewhere around thirteen million dollars being saved.”

The bots’ other goal is to elicit actionable intelligence for banks and telcos to combat scam rings across Australia, Asia, Africa and the UK and Europe.

Apate bots deal with scammers via chat. Source: Apate

Scam baiting at scale with AI victims

Kaafar says he got the idea when he received a scam call while having a picnic with his family in Sydney back in November 2021.

To his wife’s annoyance, but his kids’ delight, he strung the scammer along for 44 minutes by pretending to be a gullible rube falling for the scam. 

“What followed was really literally a full comedy show for my kids,” he says, adding that during the call he’d also learned a lot of potentially useful information about the mechanics of the scam and the tactics used.   

“As I hung up that call, I remember thinking very clearly: if I could do that just for fun, imagine what technology can do at scale.”

Working as a professor at Macquarie University at the time, he raised the idea with some of his doctoral students working on AI and security.

“I said, ‘Guys, there has to be a much better way of doing this. Let’s build something that is really automating this whole process of engaging scammers at scale, but also, perhaps most importantly, extracting all sorts of intelligence from these conversations.’ And that’s literally how it started.”

Related: AI-powered bot stands in for absent candidate in Virginia debate

Within a few months they’d secured funding from the Office of National Intelligence to research the idea, and the project was spun off from the university into Apate in 2023. The company now works with most of the big banks in Australia, as well as numerous banks in the UK, South Africa and South East Asia. 

Apate is far from the only company scam baiting fraudsters using AI bots — though they are doing it on a greater scale than most. United Kingdom telco O2 rolled out an AI Granny campaign last year, which frustrates scammers by taking up hours of their time talking about her 28 cats. It was as much an ad campaign to warn the public about the dangers of scam calls as anything else.

O2’s highly entertaining AI Granny. Source: 02

Creating the perfect AI victims

Apate launched with 120 different personas across different genders, ages and personality types, and now have 197,000 personas with identifiable vocal tics, accents, and they make the same noises people make when they’re trying to think of what to say. 

“We spent a lot of time refining and building these AI bots that sound exactly like you and I and our neighbors,” he says. 

The AI models were trained on “hundreds and hundreds” of hours of recorded conversations between human scam baiters and scammers, so they can employ counter strategies.

“They know that they’re talking to bad guys, if you like, and they really navigate the conversations so that it sounds really very, very realistic to any scammer out there, even if a scammer is skeptical about things.”
The bots get sent out on WhatsApp and Telegram to act as honeypots for scammers. While the old cliché that you can’t scam an honest man is not true, it’s still very possible to exploit the scammer’s desire for money. 

“They are cybercriminals, really. I think we just very often forget that they’re cybercriminals who are trying to get people’s life savings. And so that element of greed is sometimes what our bots also exploit.”

Bots collect valuable intel from each scam call

In the crypto industry, Apate works for “one of the leaders in blockchain analysis,” which may or may not be Chainalysis. They aren’t interested in wasting scammers’ time — they want intelligence on which wallets and methods scammers are using so they can track the flow of funds. 

“These bots, as they engage across different conversations, extract new crypto wallet addresses by the hundreds and by the thousands,” he says. “It’s data and intelligence that is coming literally before their damage happens.”

Scamming is big business, and the call centers are “pretty much corporate organizations,” Kaafar explains. 

“This data is very, very important because, literally, that’s the new account or the new wallet where you really need to pay extreme attention to. Because this is where these… scammer compounds are collecting their money or their funds with.”

“Think about it literally as being always ahead of the scammer’s tactics. And the more you know before the money gets transferred, the better it is.”

In July, Apate’s bots uncovered a marketplace for brokers soliciting verified bank accounts in India, offering commissions of up to 5% paid in USDT on the proceeds from scams passing through the accounts.

Apate’s human staff in Sydney. Source: Apate

AI arms race between good guys and bad guys

Scammers are increasingly using AI bots themselves, and it won’t be too long before AI scammers are as ubiquitous as spam emails. Scamming people is a $1.24 trillion business, so the industry can afford the compute required to scale up operations.
Apate’s research suggests that about 20% to 30% of scam text conversations employ AI already, but Kaafar isn’t too worried about the outcome of anti-scam bots fighting scam bots.
He says their researchers believe that AI bots playing defense have an advantage, according to game theory, because they’re trying to extract intelligence, while the scam bots are trying to get the other AI to perform an action.

“You can also demonstrate mathematically that that is to the advantage of a defender because it becomes easier to extract intelligence from the attacker’s AI model,” he says.

“We can imagine a world where scammers become a lot more sophisticated and deploy such technology. But that also means that if they do, they’re actually deemed to lose the game, which is great news in the fight against scams.”

Magazine: Agent wastes 14 hours of scammers’ time, LLMs ‘poisoned’ by Iran — AI Eye

Centrifuge has expanded its tokenized-fund liquidity options by adding Symbiotic’s Liquid Lane to three of its offerings, enabling eligible holders to exchange fund positions for USDC. The upgrade is aimed at making redemptions more immediate for users, while the funds’ standard redemption process can occur separately.

The integration covers Janus Henderson’s JAAA, an AAA-rated collateralized loan obligation (CLO) strategy; Janus Henderson’s JTRSY, a short-duration US Treasury strategy; and New York Life Investment Management’s HYB, a US high-yield corporate bond strategy. Together, these funds represent about $1.6 billion in assets under management, according to the announcement.

Key takeaways

• Centrifuge added Symbiotic’s Liquid Lane to three tokenized funds to provide another path for eligible holders to receive USDC.
• Liquid Lane uses an onchain request-for-quote (RFQ) marketplace, allowing market makers to source liquidity from vaults to meet redemption demand.
• Investors can receive USDC immediately, while the underlying tokenized fund redemption can be processed separately through the issuer or via RFQ.
• Centrifuge already offered instant redemptions through partnerships such as Wintermute and other liquidity arrangements, and Liquid Lane focuses on the transaction capital structure.
• The project’s broader thesis is that aggregating redemption flow across issuers and asset classes could improve liquidity economics as tokenized assets see wider onchain use.

How Symbiotic’s Liquid Lane changes the redemption workflow

Symbiotic’s Liquid Lane is built around an onchain RFQ marketplace. When redemption requests are placed, market makers can access liquidity from Symbiotic vaults to fill those requests. After acquiring the fund tokens through the RFQ interaction, market makers may then redeem the tokens with the issuer or transfer/sell them via another RFQ transaction.

This design matters because it decouples the user’s immediate liquidity outcome from the slower mechanics of traditional redemption cycles. In the Centrifuge setup described, eligible investors are able to receive USDC right away while the funds’ normal redemption process proceeds on its own schedule.

Symbiotic did not position Liquid Lane as the only redemption route; instead, it’s presented as an additional liquidity pathway designed to increase participation and improve execution for tokenized-fund holders.

Why Centrifuge and these specific funds

Centrifuge is an asset tokenization and vault platform where asset managers issue and manage tokenized funds. The three products now integrated with Liquid Lane represent a meaningful slice of Centrifuge’s institutional coverage, spanning structured credit, short-duration Treasuries, and high-yield corporate exposure.

Janus Henderson has been a significant contributor to Centrifuge’s growth, particularly through its JAAA and JTRSY products—an expansion that earlier coverage tied to Centrifuge’s progress in attracting institutional demand, including milestones reported by Cointelegraph (see Centrifuge surpasses $1B TVL in institutional demand).

By December 2025, Token Terminal estimated Centrifuge had attracted around $1.3 billion in new inflows, driven primarily by Janus Henderson’s two funds. Token Terminal also reported that JAAA alone accounted for roughly $1 billion in total value locked and was among the largest tokenized funds in the market.

Liquid Lane alongside existing instant-liquidity routes

Liquid Lane is not the first liquidity solution connected to Centrifuge’s tokenized funds. Felix Lutsch, head of Symbiotic ecosystem, told Cointelegraph that the network is not attempting to replace earlier approaches, emphasizing instead that multiple liquidity routes can coexist.

According to Centrifuge’s own disclosures, a partnership with Wintermute announced in February 2025 supported 24/7 instant redemptions for JTRSY. Separately, HYB launched in June under a different arrangement targeting near-instant redemptions.

Lutsch said the differentiation of Liquid Lane is not primarily about speed, but about the capital structure used to execute redemption demand. In his description, Liquid Lane’s RFQ marketplace can involve multiple market makers and curators without requiring every market maker to pre-fund and carry inventory for specific assets.

That distinction connects to a broader market constraint Lutsch highlighted: while tokenized asset markets can offer settlement benefits, historical low trading volumes have reduced market makers’ incentives to commit capital. He argued that routing and aggregating redemption demand across issuers and asset classes could improve liquidity economics as tokenized funds increasingly function as collateral and financing assets in onchain markets.

From an investor perspective, the practical implication is that users may have more execution options as liquidity providers face less inventory burden and can scale their participation across assets—potentially reducing friction when demand for redemptions rises.

What to watch next

As Centrifuge extends Symbiotic’s Liquid Lane to more fund products and as tokenized-fund liquidity competes across multiple RFQ and instant-redemption mechanisms, investors should watch whether trading and redemption volumes grow enough to attract and sustain market-maker participation—since Liquid Lane’s thesis depends on improving flow-driven liquidity economics.

For centuries, lending has depended on one fundamental question: Can I trust the borrower to repay me?

Traditional financial institutions answer that question through credit scores, collateral requirements, employment records, legal contracts, identity verification, and centralized intermediaries. These systems can work, but they are expensive, slow, geographically limited, and often exclude people who lack conventional financial histories.

Decentralized finance (DeFi) introduces a different approach: trustless lending.

Instead of relying primarily on a bank or lending company to determine who can borrow, trustless lending uses blockchain infrastructure, smart contracts, collateral, transparent rules, and automated liquidation mechanisms. The goal is not to eliminate trust, but to replace dependence on trusted intermediaries with verifiable rules and economic incentives.

That shift creates a completely different economic model for lending.

What Does “Trustless” Lending Actually Mean?

The term trustless can be misleading.

A DeFi lending protocol still requires users to trust that the underlying smart contracts work as intended, the blockchain remains secure, and external data such as price feeds is accurate.

What changes is where trust is placed.

In traditional lending, participants may trust:

• Banks
• Credit bureaus
• Loan officers
• Legal enforcement
• Centralized databases
• Custodians

In a trustless lending system, much of that trust is moved toward:

• Smart contracts
• Cryptographic verification
• On-chain collateral
• Transparent protocol rules
• Decentralized networks
• Economic incentives

The important innovation is therefore not “zero trust.”

It is minimizing the amount of human discretion required to execute financial agreements.

The Basic Economics of DeFi Lending

A typical decentralized lending market connects two sides:

Lenders provide capital → borrowers provide collateral → smart contracts manage the loan.

Suppose a borrower deposits $150,000 worth of ETH into a lending protocol and borrows $75,000 in stablecoins.

The borrower has a 50% loan-to-value ratio.

If ETH falls substantially and the collateral ratio crosses the protocol’s liquidation threshold, the smart contract can automatically liquidate part or all of the collateral.

No loan officer is deciding whether to call the borrower.

There is no collections department.

There is no negotiation over whether the collateral should be sold.

The protocol follows predetermined rules.

This automation dramatically changes the cost structure of lending.

Collateral Replaces Much of the Traditional Credit Infrastructure

One of the biggest economic differences between traditional finance and DeFi is the role of collateral.

Traditional lending can be credit-based.

A bank may lend because it believes a borrower has sufficient income, assets, credit history, and repayment capacity.

DeFi lending is generally much more collateral-based.

The borrower demonstrates financial credibility by locking assets into a smart contract.

This creates an important trade-off.

The advantage

Collateral can make lending accessible without requiring:

• Credit scores
• Employment verification
• Banking relationships
• Geographic approval
• Extensive paperwork

The disadvantage

Borrowers often need to provide more assets than they receive.

This is known as overcollateralization.

If someone wants to borrow $10,000, they might need to deposit $15,000 or $20,000 worth of crypto.

That may seem inefficient, but economically it serves an important purpose: the collateral absorbs credit risk.

Why Overcollateralization Exists

Imagine a lending protocol that allows users to borrow $1 for every $1 of collateral.

If the collateral suddenly loses 30% of its value, the protocol could become undercollateralized.

That creates losses for lenders.

Overcollateralization provides a buffer.

For example:

$20,000 collateral → $10,000 loan

The protocol begins with a 200% collateralization ratio.

If the collateral falls by 30%, it is still worth approximately $14,000 against a $10,000 loan.

The system therefore has additional room to absorb volatility.

This is one reason DeFi lending is particularly suited to volatile digital assets—but also one reason why crypto lending has not completely replaced traditional unsecured credit.

Interest Rates Become a Market Signal

Another major economic feature of trustless lending is algorithmic or market-driven interest rates.

In traditional finance, banks typically determine lending and deposit rates based on monetary policy, funding costs, risk models, competition, and other factors.

In DeFi, interest rates can respond directly to supply and demand for liquidity.

When demand for borrowing rises:

More borrowers → greater demand for liquidity → borrowing rates tend to increase.

When liquidity becomes abundant:

More lenders → greater available capital → borrowing rates tend to decrease.

This creates a continuously adjusting market.

Interest rates therefore become more than simply a price for borrowing.

They become a real-time signal of capital demand within a specific on-chain market.

The Economics of Liquidity

Liquidity is the engine of lending.

Without available capital, borrowers cannot borrow.

Without attractive returns, lenders have little reason to supply capital.

This creates a feedback loop:

More lenders → deeper liquidity

→ better borrowing conditions → more borrowers → more interest paid → stronger incentives for lenders.

But the opposite can also happen.

Lower liquidity → higher borrowing costs → fewer borrowers → lower lender returns → declining liquidity.

This makes liquidity management one of the most important economic challenges for lending protocols.

A protocol isn’t successful simply because it has billions of dollars deposited.

It needs productive liquidity.

Capital that sits idle provides little economic value.

Capital Efficiency Is the Bigger Challenge

Traditional finance can offer unsecured and undercollateralized loans because institutions have access to extensive information about borrowers.

DeFi has historically struggled with this.

The blockchain can tell a protocol what assets a wallet owns.

It can track transactions.

It can verify collateral.

But determining whether a real-world individual will repay a loan is much harder.

This creates an important economic problem:

How can DeFi move from overcollateralized lending toward more capital-efficient credit?

Several approaches are emerging, including:

• • On-chain credit scoring
  • Reputation systems
  • Decentralized identity
  • Real-world asset collateral
  • Institutional credit markets
  • Under-collateralized lending
  • Credit delegation
  • Zero-knowledge identity and financial credentials

Liquidation Is an Economic Feature, Not Just a Safety Mechanism

Liquidations are one of the most important components of DeFi lending.

When collateral falls below a required threshold, the protocol needs a mechanism to protect lenders.

Liquidators step in by purchasing or taking control of collateral, often at a discount.

This creates an economic incentive:

Protocol needs risk protection → liquidators receive an opportunity → unhealthy loans are removed.

The system effectively creates a decentralized risk-management workforce.

However, liquidations also introduce risks.

During extreme market volatility, collateral prices can fall faster than positions can be liquidated. Blockchain congestion, oracle failures, and sudden liquidity shortages can make the process more difficult.

So while automation reduces dependence on human intervention, it does not eliminate market risk.

Oracles Become Part of the Trust Equation

Here’s the uncomfortable truth about trustless lending:

Smart contracts cannot know the real-world price of an asset by themselves.

They need oracles.

If ETH is trading at $3,000 but a lending protocol receives an incorrect price of $2,000, collateral calculations can become distorted.

A faulty price feed could potentially trigger unnecessary liquidations or allow borrowers to take excessive loans.

This means the economics of DeFi lending depend not only on smart contracts but also on reliable information infrastructure.

In many ways, oracles are the sensory system of decentralized finance.

The Cost Advantage of Automation

One of the strongest economic arguments for trustless lending is reduced operational overhead.

Traditional lending involves high costs:

• Loan processing
• Compliance
• Administration
• Credit analysis
• Custody
• Settlement
• Collections
• Legal enforcement

Smart contracts can automate many of these functions.

Once deployed, the same lending logic can potentially serve thousands or millions of users without requiring a proportional increase in administrative staff.

This creates the possibility of software-driven financial scale.

The marginal cost of executing another transaction can be dramatically lower than the cost of manually processing another traditional loan.

But Smart Contracts Introduce New Costs

Automation doesn’t mean lending becomes free.

The cost structure simply changes.

DeFi participants must account for:

• Smart-contract risk
• Oracle risk
• Blockchain transaction fees
• Governance risk
• Liquidity risk
• Market volatility
• Economic attacks
• Bridge or infrastructure risk

A bank might spend money maintaining compliance teams and branches.

A DeFi protocol may instead spend resources on audits, security infrastructure, oracle systems, bug bounties, governance, and monitoring.

The economic question is therefore not:

“Is DeFi cheaper?”

It is:

“Which costs are removed, and which new risks and costs replace them?”

Governance Has an Economic Value

Many lending protocols are governed by decentralized organizations or token holders.

Governance can influence parameters such as:

• Interest-rate models
• Collateral factors
• Supported assets
• Liquidation thresholds
• Risk parameters
• Treasury allocation
• Protocol upgrades

This creates another economic layer.

A lending protocol is not merely a collection of smart contracts.

It is also a risk-management institution encoded in software and governance mechanisms.

Poor governance can create enormous losses.

Good governance can improve capital efficiency while maintaining system stability.

That makes governance quality an economic asset.

The Network Effect of Lending Markets

Lending protocols can also benefit from powerful network effects.

More assets supported → more borrowing opportunities.

More borrowers → greater demand for liquidity.

More liquidity → better execution.

Better execution → more users.

More users → stronger incentives for developers and liquidity providers.

This can create a reinforcing cycle.

However, network effects can also create concentration risk.

If too much liquidity becomes dependent on one protocol, one blockchain, one stablecoin, or one oracle infrastructure provider, a failure could have consequences across the broader ecosystem.

Decentralization therefore needs to be evaluated at the system level, not simply by looking at the number of smart contracts involved.

Stablecoins Are Critical to Lending Economics

Stablecoins have become especially important to DeFi lending because they provide a relatively stable unit of account.

A borrower can deposit volatile crypto collateral while borrowing a stablecoin.

For example:

ETH collateral → stablecoin loan → stablecoin repayment

This lets users access liquidity without necessarily selling their underlying assets.

Stablecoins also allow lending markets to express interest rates in units that are easier to understand than volatile crypto-denominated returns.

As stablecoin adoption grows, their role in decentralized credit markets could become increasingly important.

Trustless Lending Could Expand Global Access to Credit

Perhaps the most significant long-term economic implication is accessibility.

A person does not necessarily need to live in a major financial center to interact with a blockchain-based lending market.

They may only need:

• An internet connection
• A compatible wallet
• Digital assets
• Access to the relevant blockchain

This does not solve every problem.

People without crypto assets may still struggle to access overcollateralized loans. Regulatory restrictions can also affect availability.

But the architecture creates an important possibility:

Financial infrastructure can become globally accessible rather than geographically dependent.

That is a profound economic shift.

The Future: From Trustless Lending to Programmable Credit

The next evolution of DeFi lending may not simply be about borrowing more money.

It could be about making credit programmable.

Imagine loans that automatically adjust according to:

• Collateral quality
• Market volatility
• Reputation
• Cash-flow data
• On-chain activity
• Real-world assets
• Risk scores
• Liquidity conditions

Instead of one-size-fits-all lending, decentralized credit markets could eventually offer dynamically priced financial products.

That would move DeFi closer to a financial operating system.

Final Thoughts

The economics of trustless lending are built around a simple but powerful idea:

Replace institutional trust with transparent rules, collateral, incentives, and cryptographic verification wherever possible.

This can reduce intermediaries, automate risk management, improve accessibility, and create global markets for capital.

But trustless lending is not riskless lending.

Smart-contract vulnerabilities, oracle failures, volatile collateral, liquidity shocks, governance mistakes, and market manipulation remain serious challenges.

The real breakthrough will come when decentralized lending becomes not only trust-minimized, but also capital-efficient, resilient, secure, and accessible.

If that happens, DeFi could evolve from an alternative financial experiment into a fundamental layer of the global credit economy.

The future of lending may not be about asking, “Who do I trust?”

It may increasingly be about asking:

“What rules can everyone verify?” 🔐

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