Aave Founder: What is the Secret of the DeFi Lending Market?

marsbitОпубліковано о 2026-02-10Востаннє оновлено о 2026-02-10

Анотація

Chain-based lending, which began as an experimental concept around 2017, has evolved into a market exceeding $100 billion, primarily driven by stablecoin borrowing backed by crypto-native collateral like Ethereum and Bitcoin. This system enables liquidity release, leveraged strategies, and yield arbitrage. The key advantage of on-chain lending lies not in technological novelty but in its elimination of financial inefficiencies, offering lower costs (around 5% for stablecoins) compared to centralized crypto lenders (7-12%) due to open capital aggregation, transparency, and automation. On-chain lending is structurally due to permissionless markets that excel in capital pooling and risk pricing, fostering competition and innovation without intermediaries. This model reduces operational costs, replacing manual processes with code, and benefits both capital providers and borrowers. However, the current limitation is not a lack of capital but a shortage of diverse, borrowable collateral. The future of on-chain lending depends on integrating real-world economic value with crypto-native assets, moving beyond abstract financial strategies to serve broader adoption. Traditional lending remains expensive due to inefficiencies in loan origination, risk assessment, and servicing, where misaligned incentives and manual processes inflate costs. Decentralized finance can disrupt this by automating end-to-end operations, ensuring transparency, and reducing expenses. When on-chain lending ...

Author: Stani.eth

Compiled by: Ken, Chaincatcher

On-chain lending began around 2017 as a fringe experiment related to crypto assets. Today, it has grown into a market exceeding $100 billion, primarily driven by stablecoin lending, largely collateralized by crypto-native assets like Ethereum, Bitcoin, and their derivatives. Borrowers use it to release liquidity through long positions, execute leverage loops, and engage in yield arbitrage. The key is not creativity, but validation. The behavior over the past few years has shown that automated lending based on smart contracts had genuine demand and true product-market fit long before institutions began to take notice.

The crypto market remains volatile. Building a lending system on top of the most dynamic existing assets forces on-chain lending to immediately address risk management, liquidation, and capital efficiency issues, rather than hiding them behind policies or human discretion. Without crypto-native collateral, it would be impossible to see just how powerful fully automated on-chain lending can be. The key is not cryptocurrency as an asset class, but the cost structure transformation brought about by decentralized finance.

Why On-Chain Lending is Cheaper

On-chain lending is cheaper not because it's new technology, but because it eliminates layers of financial waste. Today, borrowers can access stablecoins on-chain at a cost of around 5%, while centralized crypto lending institutions charge interest rates of 7% to 12%, plus fees, service charges, and various surcharges. When conditions favor the borrower, choosing centralized lending is not only not conservative, it's irrational.

This cost advantage does not come from subsidies, but from capital aggregation in an open system.Permissionless markets are structurally superior to closed markets in pooling capital and pricing risk, because transparency, composability, and automation drive competition. Capital moves faster, idle liquidity is penalized, and inefficiencies are exposed in real-time. Innovation spreads immediately.

When new financial primitives like Ethena's USDe or Pendle emerge, they absorb liquidity from the entire ecosystem and expand the use of existing primitives like Aave, all without sales teams, reconciliation processes, or back-office departments. Code replaces management costs. This is not just an incremental improvement; it is a fundamentally different operating model. All cost structure advantages are passed on to capital allocators and, more importantly, to borrowers.

Every major shift in modern history has followed the same pattern. Heavy-asset systems become light-asset systems. Fixed costs become variable costs. Labor becomes software. Centralized scale replaces local duplication. Excess capacity is converted into dynamic utilization. Changes initially look bad. They serve non-core users (e.g., lending for cryptocurrency, not mainstream use cases), compete on price before quality improves, and don't look serious until they scale to a point where incumbents can't cope.

On-chain lending fits this pattern perfectly. Early users were mostly niche cryptocurrency holders. The user experience was poor. Wallets felt alien. Stablecoins didn't touch bank accounts. None of that mattered because the cost was lower, execution was faster, and access was global. As everything else improved, it became more accessible.

What Happens Next

During bear markets, demand falls, yields compress, revealing a more important dynamic. Capital in on-chain lending is always in competition. Liquidity does not stagnate due to quarterly committee decisions or balance sheet assumptions. It is constantly repriced in a transparent environment. Few financial systems are as relentless.

On-chain lending does not lack capital, it lacks collateral available for lending. Most on-chain lending today just recycles the same collateral for the same strategies. This is not a structural limitation, but a temporary one.

Cryptocurrency will continue to generate native assets, productive primitives, and on-chain economic activity, thereby expanding the scope of lending. Ethereum is maturing into a programmable economic resource. Bitcoin is solidifying its role as an economic energy store. Neither is a final state.

If on-chain lending is to reach billions of users, it must absorb real economic value, not just abstract financial concepts. The future lies in combining autonomous crypto-native assets with tokenized real-world rights and obligations, not to replicate traditional finance, but to operate it at an extremely low cost. This will be the catalyst for replacing the backend of old finance with decentralized finance.

What's Wrong with Lending

Lending is expensive today not because capital is scarce. Capital is abundant. Quality capital clears at 5% to 7%. Risk capital clears at 8% to 12%. Borrowers still pay high interest rates because everything surrounding capital is inefficient.

The loan origination process is bloated with customer acquisition costs and lagging credit models. Binary approvals cause quality borrowers to overpay, while subprime borrowers receive subsidies until they default. Servicing remains manual, compliance-heavy, and slow. Incentives are misaligned at every layer. Those who price risk rarely actually bear it. Brokers don't bear default risk. Loan originators sell exposure immediately. Everyone gets paid regardless of the outcome. The flaw in the feedback mechanism is the real cost of the loan.

Lending has not been disrupted because trust trumps user experience, regulation stifles innovation, and losses mask inefficiencies until they explode. When lending systems fail, the consequences are often catastrophic, reinforcing conservatism over progress. As a result, lending still looks like an industrial-era product clumsily grafted onto digital capital markets.

Breaking the Cost Structure

Unless loan origination, risk assessment, servicing, and capital allocation become fully software-native and on-chain, borrowers will continue to overpay, and lenders will continue to rationalize these costs. The solution is not more regulation or marginal UX improvements. It is breaking the cost structure. Automation replaces processes. Transparency replaces discretion. Certainty replaces reconciliation. This is the disruption decentralized finance can bring to lending.

When on-chain lending becomes demonstrably cheaper end-to-end than traditional lending, adoption is not a question, it is inevitable. Aave exists in this context, poised to serve as the foundational capital layer for a new financial backend, serving the entire lending landscape from fintech companies to institutional lenders to consumers.

Lending will become the most empowering financial product, simply because the cost structure of DeFi will allow fast-moving capital to flow into the applications that need it most. Abundant capital will create abundant opportunity.

Пов'язані питання

QWhat is the core reason why on-chain lending is cheaper than traditional lending according to the article?

AOn-chain lending is cheaper not because it is new technology, but because it eliminates layers of financial waste. Its cost advantage comes from capital aggregation in an open system, where transparency, composability, and automation drive competition.

QWhat does the article identify as the main limitation for the growth of on-chain lending?

AThe main limitation is not a lack of capital, but a lack of borrowable collateral. Most current on-chain lending recycles the same collateral for the same strategies, which is a temporary constraint.

QHow does the article describe the fundamental operational difference that DeFi's cost advantage is built upon?

AThe advantage is built on a fundamentally different operating model where code replaces management costs. Automation replaces processes, transparency replaces discretion, and determinism replaces reconciliation, breaking the traditional cost structure.

QWhat future development does the article suggest is necessary for on-chain lending to reach billions of users?

ATo reach billions of users, on-chain lending must absorb real economic value, not just abstract financial concepts, by combining autonomous crypto-native assets with tokenized real-world rights and obligations.

QAccording to the article, why is traditional lending expensive despite capital being abundant?

ATraditional lending is expensive because everything surrounding the capital is inefficient. The processes of loan origination, risk assessment, and servicing are bloated with costs, lagging models, manual work, compliance burdens, and misaligned incentives.

Пов'язані матеріали

The "Impossible Triad" Is Fundamentally a Pseudo-Problem

The article argues that blockchain's fundamental limitation is not the scalability trilemma (decentralization, scalability, security), which has been largely solved, but the lack of **privacy** and, until recently, clear **legitimacy**. Blockchain is described as a slow, expensive, globally shared computer whose core value is censorship resistance and verifiability. While ideal for native digital assets like money (e.g., stablecoins), its default transparency acts as a **tax**, exposing all transactions and enabling MEV extraction, which deters serious institutional capital. Simultaneously, its permissionless nature created regulatory ambiguity. The piece contends that **privacy** is the missing critical feature. It rejects the false choice between total transparency and complete anonymity. Modern cryptography (like zero-knowledge proofs) enables **compliant privacy**: users can prove facts (solvency, KYC status, compliance) without revealing the underlying sensitive data (specific holdings, identities). This preserves auditability for regulators and eliminates the leak of financial information. With recent regulatory progress (e.g., the GENIUS Act) addressing legitimacy, adding default, provably compliant privacy becomes a pure upgrade. It transforms blockchain from a costly, public ledger into a confidential settlement layer, finally bridging the gap to mainstream institutional and individual adoption of on-chain finance.

链捕手1 год тому

The "Impossible Triad" Is Fundamentally a Pseudo-Problem

链捕手1 год тому

Optical Chips: Collective Capacity Expansion

The global optical chip industry is experiencing a massive wave of expansion driven by surging AI data center demand. Major players across the US, Japan, Europe, and China are aggressively investing to ramp up production capacity. In the US, Coherent is expanding its 6-inch Indium Phosphide (InP) semiconductor fab in Texas, supported by CHIPS Act funding and a $2 billion strategic investment from NVIDIA. Lumentum is building a new factory for InP optical devices, and Nokia is scaling its advanced photonic chip packaging and testing capabilities. NVIDIA's investments aim to secure future supply of critical lasers and optical interconnect products for AI infrastructure. Japan's JX Advanced Metals, a leading InP substrate supplier, plans a multi-billion yen investment to increase its capacity 7-10 times, strengthening its grip on the crucial upstream materials market. In Europe, IQE and Tower Semiconductor settled a patent dispute and signed a multi-year InP epitaxial wafer supply agreement, highlighting that next-generation silicon photonics platforms will integrate high-performance InP components. STMicroelectronics and Sivers Semiconductors are also expanding silicon photonics production and partnerships. China is rapidly building out its domestic supply chain. Dongshan Precision's subsidiary, Source Photonics, announced a $12 billion project to expand optical chip and module production. Companies like Sanan Optoelectronics and Yunnan Germanium are scaling up InP chip manufacturing and substrate production, moving towards vertical integration from materials to modules. While debate continues around the exact future architecture—whether CPO (Co-Packaged Optics), NPO, or pluggables will dominate—analysts like Morgan Stanley argue the underlying driver is unchangeable: the explosive growth in bandwidth demand. This will inevitably increase the volume of optical engines, lasers, and related content per GPU, regardless of the final technical path. The competition for "more light" in the AI era has intensified into a global, full-chain capacity race.

marsbit4 год тому

Optical Chips: Collective Capacity Expansion

marsbit4 год тому

Stablecoins Finally Find Real Yield: An In-Depth Look at On-Chain Reinsurance Re | A Conversation with Re Founder Karan Saroya

Stablecoin Real Yield Found: A Deep Dive into On-Chain Reinsurance with Re's Karan Saroya As stablecoin supply exceeds $170 billion, the search for sustainable, non-speculative yield intensifies. Re, an on-chain reinsurance platform, provides an answer: connecting stablecoin capital to the trillion-dollar traditional reinsurance market. Re operates as a regulated reinsurer, accepting stablecoin deposits as collateral to back US insurance companies. These insurers pay premiums, generating yield that flows back to on-chain depositors. Currently supporting 35 insurers and underwriting $500 million, Re projects scaling to over $1 billion soon. Key insights from a Bankless podcast with founder Karan Saroya and investor Avichal of Electric Capital: 1. **Uncorrelated, Real-World Yield:** Re offers stablecoin holders access to reinsurance returns (targeting 12-14%+), an asset class entirely separate from crypto or equity markets. 2. **Operational Efficiency via Smart Contracts:** Re replaces traditional, labor-intensive capital fundraising with smart contracts, allowing a ~12-person team to compete with industry giants. 3. **Regulatory Leverage:** For every $1 of collateral, regulations allow backing $5-7 in written premiums. This leverage amplifies returns from the underlying risk-free rate. 4. **DeFi Integration:** Depositors receive receipt tokens, which can be used in protocols like Morpho for "looping," potentially pushing yields to 18-20%+. 5. **The "DeFi Mullet" Model:** A compliant front-end (regulated reinsurer) paired with a decentralized back-end (smart contracts, DeFi capital markets). 6. **RE Governance Token:** Modeled on Lloyd's of London, the token governs the central capital pool's allocation, counterparty acceptance, and parameters. 7. **Real Economic Impact:** Capital funds real-world productivity (factories, clinics, businesses) via insurance, moving beyond crypto's internal loops. The discussion highlights a pivotal moment: DeFi's supply-side infrastructure is now met by real demand for productive yield, potentially kickstarting a flywheel where vast on-chain stablecoin capital seeks these real-world returns.

链捕手5 год тому

Stablecoins Finally Find Real Yield: An In-Depth Look at On-Chain Reinsurance Re | A Conversation with Re Founder Karan Saroya

链捕手5 год тому

1996 or 1999? Walsh's First Test is 'How to View AI'

"1996 or 1999? Wall's First Big Test Is 'How to View AI'" Federal Reserve Chairman Wall's initial challenge is not whether to raise or cut rates, but a more fundamental judgment: what kind of boom is the current AI boom? This will determine the Fed's policy path and define his legacy. Economics is split between two opposing views, according to reporter Nick Timiraos. One sees imminent productivity gains that will increase supply and cool inflation, allowing the Fed to hold steady. The other argues that while productivity benefits are distant, demand shocks are here now, and waiting for data confirmation risks missing the intervention window, forcing sharper rate hikes later. Wall has signaled a leaning toward the first view, echoing 1996-era Alan Greenspan, who embraced strong, productivity-driven growth without fear of inflation. However, Wall faces a different macro environment than Greenspan did, with tariff pressures, expanding fiscal deficits, and diminishing globalization benefits, which could force more significant inflation pressures even if AI benefits materialize. Wall's logic, expressed before taking office, is that AI-driven productivity gains won't show in official data for years. If the Fed waits for confirmation, it might mistakenly tighten policy and choke off the very growth that could suppress inflation. This argues for using forward-looking narratives over lagging data. Chicago Fed President Austan Goolsbee presents a key counter-argument. He distinguishes between expected and unexpected productivity booms. A widely anticipated boom, like the current AI wave, can cause people to spend future wealth gains in advance, overheating the economy before productivity actually rises, thus requiring preemptive rate hikes. He cites rising costs for AI data centers as evidence of such overheating. Fed Governor Christopher Waller offers a rebuttal to Goolsbee, noting the "expected spending" mechanism only works if people can borrow against future income, which many households cannot do due to borrowing constraints. Wall also faces a paradox related to his desire to reduce the Fed's use of "forward guidance" (pre-announcing policy moves). This practice was established in 1999 when Greenspan began signaling hikes to avoid market shocks. If the economy follows a less optimistic path, Wall may be forced to choose between using the guidance he wants to abolish or risking market volatility by staying silent. The ultimate question defining Wall's first major test remains: Is this 1996 or 1999?

marsbit6 год тому

1996 or 1999? Walsh's First Test is 'How to View AI'

marsbit6 год тому

Торгівля

Спот
Ф'ючерси
活动图片