The Restructuring of Private Credit: The Theory and Application of Protocolizing Real-World Assets (RWA) Based on Blockchain

Abstract

The private credit market is plagued by inherent structural frictions, including severe illiquidity, opaque valuations, high transaction costs, and rigid capital lock-up structures. Under macroeconomic headwinds, these deficiencies are sharply amplified, as evidenced by the recent structural predicaments in the Asian credit market, where traditional fund models have revealed significant vulnerabilities in handling high leverage, structurally subordinated debt, and cross-border enforcement, leading to severe erosion of Internal Rate of Return (IRR) and significant Net Asset Value (NAV) markdowns. This paper introduces a five-stage "Protocolization" model—Asset Identification & Legal Engineering, Validation Oracles & Dynamic Due Diligence, Tokenomics & Mechanism Design, Liquidity Solutions & Market Design, and Derivatives & Structured Product Development—aimed at systematically addressing the inefficiencies of the traditional market. This paper analyzes the application of this model in Direct Lending, Mezzanine, Secondaries, Distressed, and Portfolio Financing. By reducing information asymmetry (Akerlof, 1970), enhancing market completeness (Arrow-Debreu, 1954), optimizing capital structure, and enabling dynamic risk management, RWA protocolization offers a viable technological path to resolve the current structural dilemmas of the private credit market, thereby reshaping the market microstructure and capital formation paradigm of private credit.

1. Introduction: The Rise of Private Credit, Structural Dilemmas, and the Disruptive Potential of RWA

1.1. The Rise of Private Credit and the Evolution of Financial Intermediation

Private Credit, as an emerging and rapidly growing alternative asset class, has played an increasingly important role in global capital markets in recent years. According to statistics, the global private credit market has expanded rapidly over the past five years at a compound annual growth rate of about 17%. Unlike traditional bank loans, private credit is typically provided directly to companies by non-bank financial institutions (such as asset management firms, private equity funds, etc.), including various forms like direct lending to SMEs, mezzanine loans to large corporations, and distressed debt financing. This disintermediated financing method provides borrowers with new sources of capital and offers investors attractive returns.

Since the 2008 Global Financial Crisis (GFC), the structure of financial markets has undergone a profound transformation. The reshaping of the regulatory framework, particularly the strict capital adequacy requirements imposed on traditional banks by the Basel III Accord, significantly increased the cost for banks to hold Risk-Weighted Assets (RWA), leading to Credit Rationing, especially in the middle market and leveraged finance sectors. This Regulatory Arbitrage created a huge market vacuum, driving the rise of Private Credit. The private credit market covers a wide range of strategies, including direct lending, mezzanine financing, distressed debt, and special situations financing, with its global Assets Under Management (AUM) exceeding $1.7 trillion and expected to continue its strong growth.

From the perspective of financial intermediation theory, the rise of private credit represents a shift in the function of financial intermediaries. According to Diamond's (1984) Delegated Monitoring model, financial intermediaries exist to reduce the costs of information production and monitoring. Private credit fund managers (GPs), through professional due diligence, customized loan covenants, and active post-investment monitoring, have taken on the information-intensive lending functions previously performed by banks.

The appeal of private credit to institutional investors (LPs) mainly stems from the excess returns it offers compared to public fixed-income products. This excess return is often attributed to an Illiquidity Premium and the Alpha generated by managers through their expertise and network. The expected return of private credit, E[R_pc], can be conceptualized as:

E[R_pc] = R_f + β_pc * (E[R_m] - R_f) + Π_L + α

where R_f is the risk-free rate, β_pc is the systematic risk of private credit, E[R_m] is the expected market return, Π_L is the illiquidity premium, and α is the manager-specific alpha.

1.2. Inherent Structural Frictions and Efficiency Bottlenecks

However, high returns are often accompanied by structural challenges such as low liquidity and information opacity. According to an investor survey by Coalition Greenwich, the majority of institutional investors believe that insufficient liquidity, operational inefficiency, and low transparency are the main factors preventing them from increasing their allocations to private credit. This means that despite the attractive returns of private credit, many investors remain concerned about the inability to buy and sell at any time, high fees, and inadequate information disclosure.

The underlying infrastructure supporting this vast market remains outdated and inefficient, fraught with structural frictions. These frictions not only limit the efficiency of capital allocation but also amplify systemic risks when the market is under stress.

Severe Illiquidity and Maturity Mismatch: Private credit instruments are typically customized bilateral or syndicated loans, lacking standardized contract terms, which results in an extremely underdeveloped secondary market. The standard closed-end fund structure, typically with a 7-10 year life, creates a severe maturity mismatch for LPs. Capital is locked up for long periods, making it difficult for LPs to dynamically adjust their portfolios in response to changes in the macroeconomic environment. The fund's J-Curve Effect—where capital is heavily invested in the early years while returns are realized later—further exacerbates the liquidity pressure on LPs.

Valuation Opacity and Information Asymmetry: The valuation of private loans is inherently subjective. According to ASC 820 guidelines, private credit assets are typically classified as Level 3 assets, whose fair value depends on the GP's internal models and subjective judgments rather than observable market prices. This leads to Net Asset Value (NAV) Smoothing and Staleness. GPs have an incentive to delay the recognition of losses to maintain a good track record. This severe information asymmetry creates an adverse selection problem (Akerlof, 1970) between GPs and LPs, as well as between buyers and sellers in the secondary market.

High Transaction and Intermediation Costs: Private credit transactions involve complex legal due diligence, loan origination, post-investment management, and settlement processes, which are highly dependent on intermediaries such as lawyers, accountants, and rating agencies, generating significant Agency Costs and Transaction Costs.

Inefficient Capital and Concentration Risk: The customized nature of loan origination limits the speed of capital deployment and the diversification potential for smaller managers. Furthermore, even if the underlying assets perform well and generate cash flow, the capital remains locked up, which represents a macro-inefficiency in resource allocation.

1.3. The Emergence of Structural Predicaments: The Case of the Asian Credit Market

In recent years, the deterioration of the macroeconomic environment, particularly the Federal Reserve's rapid interest rate hike cycle and credit risk exposure in specific regions (such as Asia, especially the Chinese real estate market), has laid these structural deficiencies bare. We have observed that many Asian credit funds established in 2019-2020 have seen a sharp decline in performance, revealing the fragility of the current model.

In emerging markets like China, the discussion of combining private credit with RWA is also heating up. On one hand, China's private credit market has been tested by liquidity crises and credit risk events in recent years—such as a large number of real estate bond defaults and the tightening of financing for local government financing vehicles (LGFVs)—which has put significant pressure on the cash flow recovery and valuation of private credit funds. An Asian direct lending fund (Loan Fund IV), established in 2019 to invest in large loans and private bonds, saw its portfolio suffer severe impairment under the dual impact of global interest rate hikes from 2021 to 2023 and the deteriorating credit environment in China. By the end of 2023, the fund's Total Value to Paid-In (TVPI), which is '(cumulative distributions plus current net value) divided by capital called,' had fallen below 1.0x, and its Internal Rate of Return (IRR) turned negative at -1.0%. By the first half of 2024, its IRR had further declined to approximately -1.6%, meaning investors were facing paper losses. This phenomenon is not an isolated case; several Asian private credit and distressed asset funds established during the same period have experienced IRRs close to zero or even negative.

For example, the Loan Funds and Special Situations Funds of some large asset management institutions, due to their combined strategies of high leverage, structural subordination, and cross-border enforcement, are facing sharp NAV markdowns amidst macro shocks. Data shows that for some funds established in 2020, their IRR has plummeted from early positive values (e.g., +6.00%) to negative values (e.g., -1.60%), with a Multiple below 1.0x (e.g., 0.97x). This occurring 4-5 years after the fund's inception is clearly not a normal J-curve phenomenon but a reflection of deep structural impairment.

The core of this predicament lies in the fatal combination of "high exposure investment, low recovery rate." High leverage amplifies losses; structural subordination puts creditors in an extremely disadvantaged position in the event of a default. And the difficulty of cross-border enforcement—"strong on-paper rights, weak real-world recovery"—results in extremely low actual recovery rates (often below 5%). This is not just a failure of investment strategy, but a failure of market structure and enforcement mechanisms. In an environment of tightening liquidity, traditional exit paths are blocked, and a liquidity crisis quickly evolves into a solvency crisis. Behind this are reasons of drastic changes in the macro environment (such as the Fed's interest rate hikes causing financing costs to soar, and liquidity contraction in emerging markets), as well as factors related to the structure of private credit assets themselves (high leverage, subordinated structure, cross-border legal enforcement difficulties, etc.), leading to low asset recovery rates, blocked exits, and continuous NAV markdowns.

The aforementioned real-world predicaments highlight a problem: the private credit market suffers from structural illiquidity and exit difficulties. Under the traditional model, investors are often locked in for many years and cannot liquidate in a timely manner, and the lack of a secondary market means they have to sell their positions at a significant discount when they need to exit.

1.4. The Disruptive Potential of RWA Tokenization and the Contribution of This Paper

Recent developments indicate that combining Real-World Assets (RWA) with blockchain technology holds the promise of providing new solutions to the aforementioned problems. RWA refers to representing real-world financial assets (such as loans, accounts receivable, bonds, real estate equity, etc.) in token form on the blockchain, allowing them to be circulated and traded on-chain. Proponents argue that RWA tokenization can achieve asset fractionalization and 24/7 global trading, thereby enhancing the liquidity of traditionally illiquid assets and reducing transaction friction and intermediation costs. This idea has generated strong interest in the private credit sector. On-chain private credit RWA attempts to represent private loans, mezzanine debt, etc., in the form of digital tokens, allowing them to be held or traded by more investors like public market securities. This not only promises to broaden the investor base for private credit and lower financing costs, but can also improve operational efficiency and transparency through smart contracts.

Against this backdrop, the concept of Real-World Asset (RWA) tokenization, as an emerging technological paradigm, offers a potential solution to the structural predicaments of the private credit market. RWA tokenization refers to the use of Distributed Ledger Technology (DLT) to map the ownership and related rights of traditional financial assets onto the blockchain, represented in the form of digital tokens. This process goes beyond mere Digitization; it achieves "Financialization" and "Protocolization" through smart contracts, thereby enabling automated, transparent, and composable financial interactions.

Currently, private credit is gradually becoming one of the frontrunners in the on-chain RWA market. Data from the 2025 Real-World Assets in On-Chain Finance report indicates that among all real-world assets brought on-chain, the total size of RWA (excluding stablecoins) is approximately $24 billion, of which private credit accounts for about $14 billion, making it the largest segment at around 58% (approximately $14 billion of $24 billion). This market has "grown by about 380%" since 2022. The market has shown explosive growth in the last two years: in 2022, the total on-chain RWA size was only about $5 billion, but by mid-2025, it had grown to $24 billion, achieving an increase of about 380%. It is worth noting that stablecoins are not included in these statistics; otherwise, the overall scale of RWA would be even larger. A large number of major traditional financial institutions have begun to enter this field, including the world's leading asset management companies and banks, who are actively experimenting with bringing some of their credit assets on-chain. For example, renowned institutions such as BlackRock, JP Morgan, and Apollo have already started deploying capital on the blockchain, aiming to merge traditional finance with on-chain finance. These signs indicate that the on-chain RWA wave is moving from small-scale startup experiments to a new stage of mainstream institutional participation.

The core argument of this paper is that RWA infrastructure is not merely about digitizing existing assets; by providing a trusted, transparent, and programmable execution environment, it can fundamentally restructure the transaction processes, capital structures, and risk management mechanisms of the private credit market. RWA is not a panacea; it cannot transform a non-performing loan (NPL) into a performing asset. However, it can radically change how these assets are managed, traded, and financed.

We further argue that the most profound and immediate impact of RWA will be felt on the liability side of the private credit ecosystem. In the context of systemic distress, RWA offers sophisticated tools for liquidity management, capital structure optimization, and risk tranching. By creating mechanisms for fractional ownership, automated securitization (e.g., on-chain Collateralized Loan Obligations - CLOs), and permissioned liquidity pools, RWA protocols can provide much-needed liquidity solutions for distressed funds, improve price discovery, and reduce the frictional costs embedded in the current market structure. On-chain RWA is expected to provide innovative solutions for these problems on the liability (creditor) side.

This paper aims to provide a systematic theoretical framework for the tokenization of private credit instruments as Real-World Assets (RWA) and to propose an architecture for a fundamental restructuring of the private credit market. We argue that by leveraging distributed ledger technology, it is possible to address the deep-seated structural inefficiencies currently plaguing this asset class—namely, the lack of liquidity, information asymmetry, and capital friction. The analysis of this paper is divided into three parts. First, we conduct a granular examination of the various sub-strategies of private credit, including direct lending, mezzanine financing, distressed debt, secondary market trading, and portfolio financing, and identify unique on-chain application scenarios for each strategy. Grounded in a case study of underperforming Asian credit funds, we root our theoretical analysis in real-world market challenges. Second, we construct a five-step protocol architecture for bringing these assets on-chain, detailing the key legal, validation, tokenomic, liquidity, and derivative layers. We introduce novel applications of Decentralized Identity (DID) and Verifiable Credentials (VC) to mitigate information asymmetry and propose a hybrid liquidity model tailored to the unique properties of illiquid assets. Third, we explore the attendant legal, regulatory, and systemic risk considerations. We conclude that while the on-chain migration of private credit is complex, it offers the potential for a paradigm shift in capital markets towards greater transparency, efficiency, and broader accessibility.

The contribution of this paper lies in providing a rigorous theoretical framework that combines principles of financial economics (market microstructure, information economics, contract theory) with blockchain technology to deeply analyze the potential and limitations of RWA in various sub-categories of private credit. We propose a five-stage model for on-chain private credit deployment and particularly emphasize how, in the current market environment, RWA can provide liability-side solutions for stressed credit markets, maintaining the depth and precision of elite academic research. This paper will delve into how various segments of private credit (direct lending, mezzanine loans, secondary market trading, distressed debt, portfolio financing, etc.) can be combined with RWA to achieve on-chain asset transformation and liquidity enhancement, as well as the inherent challenges and mechanism design. Based on financial theory and blockchain technology principles, we will analyze the application scenarios and potential gains of RWA in private credit, including how to reduce NAV discounts through on-chain trading, raise capital through tokenization, introduce on-chain liquidity providers, and utilize smart contracts and oracles to automate due diligence and profit distribution. At the end of the article, we will also provide a step-by-step implementation framework, explaining the complete process from asset identification, off-chain verification, token design, liquidity bootstrapping, to derivative development. This series of studies aims to show that although RWA is not magic and cannot eliminate the credit risk of the underlying assets, appropriate on-chain design is expected to partially alleviate the liquidity pain points of private credit and create new value by integrating traditional finance with decentralized finance.

2. Theoretical Foundations: The Microstructure of Private Credit Markets, Information Asymmetry, and Agency Costs

To fully understand the transformative potential of RWA tokenization, we must first ground our analysis in established theories of financial economics that explain the sources of inefficiency in the current private credit landscape. This section will delve into the application of market microstructure theory, information economics, and agency theory in the context of private credit and analyze how RWA interacts with these theories.

2.1. Market Microstructure and the Sources of the Illiquidity Premium

The illiquidity premium (Π_L) demanded by private credit investors is a significant component of their excess returns. The size of Π_L depends on the microstructural characteristics of the underlying market. Market microstructure theory studies how trading mechanisms affect price formation and market liquidity.

2.1.1. Search Costs and the Over-the-Counter (OTC) Market Model

The private credit market is a classic over-the-counter (OTC) market. According to the search-theoretic model of Duffie, Gârleanu, and Pedersen (2005), in an OTC market, investors must spend time and resources to find a counterparty. The search cost, C_search, depends on the degree of asset standardization, the number of market participants, and the efficiency of information dissemination. In private credit, C_search is extremely high due to the heterogeneity of assets and the opacity of the market. This leads to low trading frequency and large bid-ask spreads.

RWA tokenization significantly reduces search costs by providing a centralized, standardized trading platform (a decentralized exchange, DEX). By aggregating potential counterparties, RWA protocols increase the matching efficiency between market participants.

2.1.2. Transaction Costs and Inventory Risk

In the high-friction market model described by Amihud and Mendelson (1986), transaction costs (C_transaction) and inventory risk form a wedge between the reservation prices of buyers and sellers. In private credit, C_transaction includes high legal fees, administrative burdens, and GP consent procedures. Inventory risk is the risk faced by intermediaries (market makers) from holding illiquid assets. Due to insufficient market depth, they demand a higher premium to compensate for this risk.

RWA tokenization significantly reduces C_transaction by automating the trading and settlement process through smart contracts. Atomic settlement eliminates counterparty risk. While inventory risk still exists, it can be distributed among a broader group of liquidity providers through mechanisms like Automated Market Makers (AMMs).

2.1.3. The Compression Effect on the Illiquidity Premium

The theoretical implication is that RWA tokenization will lead to a compression of the illiquidity premium. If tokenization successfully enhances liquidity, the equilibrium Π_L should fall.

∂Π_L / ∂(Liquidity) < 0

This compression represents a transfer of value. On one hand, it may lower the overall expected return for new investments in the asset class, benefiting borrowers with a lower cost of capital. On the other hand, it increases the realized return for existing investors by reducing the liquidity discount applied to their holdings. This is a potential Pareto improvement. However, it is important to note that enhanced liquidity may also lead to higher realized volatility, as valuations will more promptly reflect market information and sentiment, rather than the smoothed valuations provided by GPs.

2.2. Information Asymmetry, Adverse Selection, and Signaling

Information asymmetry is a core feature of the private credit market. The GP possesses private information about the quality and valuation of the underlying assets, while LPs and secondary market buyers are at an informational disadvantage. This leads to severe adverse selection and moral hazard problems.

2.2.1. Adverse Selection and the "Market for Lemons" Problem

Akerlof's (1970) "market for lemons" model explains how information asymmetry can lead to market failure. In the private credit secondary market, buyers fear that sellers are offering low-quality assets ("lemons"), especially during periods of market stress. Unable to distinguish between high-quality and low-quality assets, buyers will demand a significant discount, the adverse selection discount (D_as). This discount further exacerbates illiquidity and leads to high NAV discounts.

D_as = f(Information Asymmetry, σ_valuation)

where σ_valuation is the uncertainty of valuation.

2.2.2. Subjectivity of Valuation and NAV Smoothing

The valuation of private credit assets (Level 3 assets) is highly dependent on subjective judgment. The calculation of NAV typically uses a discounted cash flow (DCF) model:

NAV = Σ [ E(CF_t) / (1 + r_d)^t ] - Liabilities

where the determination of both the expected cash flows E(CF_t) (which depends on the probability of default, PD, and loss given default, LGD) and the discount rate r_d involves subjective assumptions. Research shows that private market NAVs exhibit significant serial correlation and smoothing. This stickiness of NAV makes it difficult for LPs to accurately assess the true risk profile of a fund. In a market downturn, this lagged valuation adjustment can lead to a sudden eruption of risk.

2.2.3. RWA's Mechanisms for Mitigating Information Asymmetry

RWA protocols can mitigate information asymmetry through the following mechanisms:

Immutable Audit Trail: DLT provides a verifiable record of the entire process from loan origination to every interest payment and ownership change. This increases the transparency of asset performance.

Standardized Data Disclosure: RWA protocols need to define standardized data structures and disclosure requirements, reducing the difficulty of evaluating and comparing different assets.

Decentralized Validation & Oracles: Through a decentralized network of validators and oracles (see Section 4.2), off-chain information can be credibly transmitted on-chain, reducing reliance on GPs' subjective reporting.

By increasing transparency and standardization, RWA tokenization brings the private credit market closer to the state described by the Efficient Market Hypothesis, thereby reducing the adverse selection discount D_as.

2.3. Agency Costs and Mechanism Design

The GP/LP structure is inherently susceptible to agency costs (Jensen and Meckling, 1976). The GP's compensation structure (management fees and carried interest) can lead to a misalignment of their incentives with those of the LPs, giving rise to moral hazard and conflicts of interest.

2.3.1. Moral Hazard and Risk Shifting

GPs may engage in risk-shifting behavior. For example, if a fund's performance is below the hurdle rate for carried interest, the GP might take on excessive risk in hopes of a high return (similar to a call option). Alternatively, they might deploy capital too aggressively early in the fund's life, leading to a decline in credit standards.

2.3.2. Zombie Fund Behavior and Fee Extraction

GPs may hold onto underperforming assets to continue collecting management fees (Fee Extraction), rather than liquidating the fund and realizing losses, leading to the phenomenon of "Zombie Funds."

2.3.3. Smart Contracts and Automated Governance

Tokenization introduces the possibility of embedding governance and incentive mechanisms directly into the asset itself through smart contracts. This falls within the field of mechanism design (Hurwicz, 1973). Smart contracts can automatically execute covenants, reducing monitoring and enforcement costs.

Automated Waterfall Models: Smart contracts can automatically calculate and distribute cash flows (waterfall payments), ensuring the transparency and accuracy of distributions and reducing the GP's discretion.

Dynamic Fee Structures: The calculation of management fees can be based on real-time, on-chain verified NAV, rather than the GP's reported quarterly NAV, thus better aligning incentives.

Automated Covenant Enforcement: Smart contracts can automatically execute predefined restructuring steps or trigger governance votes in the event of a default.

By reducing agency costs (C_agency), RWA protocols can enhance investor confidence and improve the efficiency of capital allocation.

2.4. Cross-Border Enforcement and Legal Friction

In cross-border private credit transactions, legal friction and enforcement risk are major challenges. As observed in the Asian private credit market, even when contracts provide strong "on-paper rights," enforcing these rights in foreign jurisdictions can be extremely difficult and costly. This involves sovereign risk, differences in legal systems (e.g., common law vs. civil law), and the complexities of local bankruptcy laws.

The enforcement cost, C_enforcement, and enforcement time, T_enforcement, are very high in these situations, leading to actual recovery rates being far below expectations.

While RWA tokenization cannot directly solve these macro-legal problems, it can indirectly improve enforcement efficiency by increasing transparency and coordination among creditors (see Section 5.3). By providing a shared, immutable registry of claims, DLT can simplify complex capital structures and facilitate the collective bargaining power of creditors. However, DLT cannot replace an effective judicial system.

3. Application and Impact Analysis of RWA in Various Private Credit Sub-Categories

This section aims to lay the groundwork for our analysis: while the private credit market has experienced exponential growth, with assets under management exceeding $2 trillion, it continues to be plagued by structural inefficiencies. We will introduce the core argument of this paper, which is that each sub-strategy within private credit presents a unique set of problems that can be addressed through a tailored tokenization approach. The private credit business covers various sub-types, including direct lending, mezzanine financing, secondary market debt trading, distressed debt investing, and structured financing for asset portfolios. Different types of private credit vary in their risk-return characteristics and liquidity, and their points of integration with RWA also differ. The following will analyze the on-chain opportunities in each area one by one.

Note: In some sections, to integrate the content of the two documents, the section titles and numbering may differ slightly from the original files, but all content has been preserved.

3.1. Direct Lending: The Core of Tokenized Private Credit

3.1.1. Market Background and Business Overview

Direct lending is the dominant strategy in the private credit market, characterized by providing floating-rate, senior secured loans to middle-market companies. The global market size is enormous, estimated to be over $1 trillion in the US alone, with strong growth forecasts. These loans provide predictable cash flows, making them ideal candidates for tokenization. In business terms, direct lending typically refers to bilateral loans provided directly to companies by private credit funds or other non-bank institutions, primarily targeting medium-sized enterprises that cannot easily access financing through banks or public bond markets. These loans are mostly senior secured loans, with floating interest rates, and stipulate periodic interest payments and principal repayment at maturity, resulting in relatively stable cash flows. However, traditional direct lending is a non-standardized, non-publicly traded asset. Loan contracts are often negotiated on a one-to-one basis, and there is no active secondary market. Once investors participate in a direct lending fund, they usually have to hold the loan until maturity, suffering from severe illiquidity. An early exit may require selling the stake in an over-the-counter transaction at a significant discount.

3.1.2. On-Chain Value Proposition and Opportunities

Direct lending is the most direct and highest-potential application area for RWA tokenization. Its goal is to improve operational efficiency, lower the cost of capital, and expand the investor base.

Tokenization can transform these loans into divisible, yield-bearing digital assets. This process involves representing loan shares as fungible tokens (e.g., following the ERC-20 standard). Bringing direct lending assets on-chain can enhance their liquidity and investability through tokenization. Specifically, with a blockchain platform, the beneficial interest in a single loan can be fractionalized into digital tokens, allowing multiple investors to participate in a large loan with smaller amounts of capital, thus forming an on-chain "syndicate." This, on one hand, lowers the barrier to entry and concentration risk for individual investors, and on the other, broadens the funding sources for borrowing companies. In the on-chain market, direct lending projects that were previously accessible only to a few institutions could attract more qualified investors globally, improving the efficiency of capital matching. Its main advantages are:

Enhanced Liquidity: Creates a secondary market for previously illiquid loan assets. At the same time, tokenized loan shares can be freely transferred on-chain, allowing investors to sell their shares in the secondary market to gain liquidity without waiting for the loan to mature. If there is no immediate buyer, investors can also pledge their loan tokens in a decentralized lending protocol to obtain liquidity, for example, by using them as collateral to borrow stablecoins, achieving an effect similar to repo financing. This mechanism of providing on-chain liquidity based on collateral helps alleviate the lock-up predicament of traditional direct lending.

Composability: Allows these yield-bearing tokens to be used as high-quality collateral in the broader Decentralized Finance (DeFi) ecosystem, functioning similarly to today's liquid staking tokens (LSTs).

Transparency: The on-chain record of interest payments and principal repayments provides unprecedented transparency for investors.

The traditional syndicated loan process is manual, lengthy, and costly (settlement times are often T+20 or longer). RWA protocols can revolutionize this process in the following ways:

Standardization & Automation: Utilize standardized templates for loan agreements (embedded in smart contracts) to automate documentation and due diligence processes.

Efficient Allocation & Settlement: Achieve rapid allocation and near-real-time settlement (T+0) of loan shares through tokenization.

Broader Participation: Enable smaller institutions and high-net-worth individuals to participate in syndicated loans.

The significant reduction in transaction costs (C_t) will increase the overall efficiency of the market. The validation and oracle layer (Layer 2) facilitates real-time monitoring of financial covenants. Smart contracts can automatically enforce covenant terms, enabling proactive risk management.

Dynamic Interest Rate Adjustments: If a borrower's credit profile changes (e.g., leverage ratio increases), a smart contract can automatically adjust the interest rate.

Automated Cash Flow Sweeps: If a covenant is breached, a smart contract can automatically initiate a cash flow sweep mechanism to protect the interests of the lenders.

GPs can tokenize their existing portfolios to provide liquidity to LPs or to refinance through on-chain CLOs. This addresses the inherent maturity mismatch problem of closed-end fund structures.

3.1.3. Deeper Logic and Causal Links

The significance of tokenizing direct loans is not just about creating a tradable asset, but more about building a new type of "DeFi-native" base-layer collateral. The logical chain is as follows: First, direct loans are typically senior secured and have predictable cash flows, which makes their risk profile much easier to understand and evaluate than volatile crypto-native assets. Second, current DeFi lending protocols (like Aave, Compound) are overly reliant on volatile crypto assets as collateral, which leads to high over-collateralization ratios and creates systemic risk during market downturns. A stable, yield-bearing tokenized direct loan, backed by a real-world asset, can serve as a superior form of collateral. Therefore, the third-order effect is that tokenizing the largest part of private credit could significantly reduce the risk and increase the stability of the entire DeFi ecosystem, thereby attracting more risk-averse institutional capital into the space.

3.1.4. Challenges and Real-World Progress

A key feature of the direct lending market is its customized nature. Excessive standardization could undermine the alpha that GPs create through structuring and covenant design. RWA protocols need to strike a balance between standardization (to enhance liquidity) and customization (to meet specific needs). The use of SFTs (like ERC-3525) can partially address this challenge.

There have been multiple attempts to bring the direct lending business onto the blockchain. One category is on-chain lending platforms built by fintech companies, such as Figure Technologies, which has tokenized over $10 billion in loan assets through its proprietary blockchain, accounting for about 75% of the current private credit RWA market. Another category is Decentralized Finance (DeFi) protocols, like Maple Finance, a direct lending platform running on public chains such as Ethereum, which had issued a cumulative total of $3.3 billion in loans by mid-2025, with a current active loan balance of about $777 million. Platforms like Maple initially focused on borrowers from the crypto industry but have recently begun to expand into credit for traditional enterprises. Large asset management institutions have also joined the exploration: KKR issued shares of its healthcare-themed growth credit fund on the Avalanche chain in 2022, and Hamilton Lane also tokenized shares of its "Senior Credit Opportunities Fund (SCOPE)" through the Securitize platform in 2023, issuing them successively on chains like Ethereum, Polygon, and Solana. These cases show that the on-chaining of direct lending assets has moved from proof-of-concept to actual implementation, with institutional investors hoping to expand their funding sources and enhance trading flexibility. In the future, as the coordination between legal structures (such as SPV trust structures) and smart contracts improves, on-chain direct lending is expected to become a new channel for SMEs to obtain capital and for investors to achieve stable returns.

3.2. Mezzanine and Subordinated Debt: Deconstructing Hybrid Instruments

Mezzanine financing, due to its hybrid nature (debt and equity features) and structural subordination, presents more complex challenges for tokenization.

3.2.1. Market Background and Business Overview

Mezzanine financing fills the gap between senior debt and equity, typically combining debt features (fixed coupon) with equity-like upside potential (such as warrants or conversion rights). It is a sizable and growing market, estimated to be over $200 billion. The hybrid nature of these instruments makes them structurally complex and extremely illiquid. Mezzanine financing is a transitional form of financing between debt and equity, with typical examples including subordinated loans, unsecured high-yield notes, convertible bonds, and loans with warrants. Mezzanine capital is often used to support leveraged buyouts (LBOs) or the expansion of growth companies, with a higher risk than senior debt but lower than pure equity. Investors receive higher coupon returns for taking on greater default risk, often with annualized returns in the low double digits or even higher. However, the claim priority of mezzanine debt is subordinated. In the event of a borrower default, mezzanine holders can only receive a share of the remaining assets after senior creditors have been paid, resulting in a higher loss given default. Similar to direct lending, mezzanine financing is usually conducted through private placements, lacks public market trading, and has long investment tenors and very poor liquidity.

3.2.2. On-Chain Value Proposition and Opportunities

A single mezzanine instrument can be "deconstructed" on-chain into two distinct tokens:

Fungible Debt Token (DT): Represents the claim on the contractual cash flows (interest and principal). This token behaves like a zero-coupon or fixed-coupon bond on-chain.

Non-Fungible or Fungible Equity Option Token (EOT): Represents the warrants or conversion rights. This token can be a Non-Fungible Token (NFT) if the options are unique, or a fungible token if the rights are standardized, which can be traded on a specialized on-chain options market.

The on-chaining of mezzanine loans is attractive to both investors and borrowers. On one hand, by tokenizing mezzanine debt, borrowing companies can access a broader group of potential investors—for example, qualified investors globally seeking high-yield opportunities—thereby increasing the success rate of financing and potentially lowering the cost of capital. On the other hand, investors can flexibly adjust their positions through the on-chain market: once tokenized mezzanine debt becomes tradable, investors can partially liquidate when needed, unlike traditional private mezzanine where capital is locked up for years. This reduction in the liquidity premium is expected to lower the risk premium demanded by investors, which in turn can reduce the interest burden for the borrower. From a product design perspective, mezzanine debt tokens can be packaged with senior debt to form on-chain structured products (similar to mini-CLOs), representing different risk tranches with different classes of tokens for subscription by investors with varying preferences. For example, in one financing, a senior token could correspond to a lower interest rate but higher payment priority, while a mezzanine token would correspond to a higher interest rate but a first-loss position. Through this on-chain tranching design, risk and return are reallocated, allowing more investors to find what they need.

Smart contracts can precisely encode the complex terms of mezzanine financing.

Payment-in-Kind (PIK) Interest: PIK interest can be automatically calculated and distributed in the form of new tokens, improving the accuracy and transparency of the calculation.

Warrants: Warrants can be issued, traded, and exercised as separate tokens (e.g., ERC-1155). Smart contracts can automatically execute exercise conditions and price adjustment mechanisms.

Tokenization can facilitate the creation of structured products that finely slice the risk of mezzanine exposure. For example, a mezzanine loan can be split into a fixed-income component and an equity-like component, and sold separately to different investors. This allows for more efficient risk management and capital allocation.

3.2.3. Deeper Logic and Causal Links

Tokenization enables the independent pricing and risk management of the different components within a hybrid credit instrument, which is not possible in the current opaque market. The underlying logic is this: traditional mezzanine investors have to price both the debt and equity components simultaneously, which leads to inefficient valuation. By deconstructing them on-chain, the market can price each component independently. A credit-focused DeFi protocol could value and trade the Debt Token (DT), while an equity derivatives protocol could value and trade the Equity Option Token (EOT). This separation enables more efficient capital allocation. Investors seeking stable yield can buy the DTs, while venture-style investors seeking high-risk upside can buy the EOTs. The end result is a more complete market that attracts a wider range of capital and provides more accurate price discovery for complex financial instruments.

3.2.4. Challenges and Implementation Considerations

Compared to senior loans, the on-chaining of mezzanine debt must address higher credit risk and complexity. One challenge is information asymmetry and credit assessment: mezzanine investment relies heavily on in-depth due diligence of the borrower's operating conditions, and on-chain investors may find it difficult to obtain sufficient information. This requires the introduction of on-chain verification mechanisms for off-chain due diligence reports (e.g., using oracle networks like Chainlink to provide audited financial metrics or credit rating data) to enhance investor confidence. Furthermore, if the mezzanine loan includes options (such as convertibility) or equity kickers, the token contract needs to be designed with corresponding clauses to ensure that on-chain investors receive the appropriate equity when an equity conversion or profit-sharing event is triggered. This may require a combination of on-chain and off-chain legal arrangements. For example, the borrower's equity could be held in an SPV, and when conversion conditions are met, an oracle would trigger the token holders' receipt of equivalent equity or additional tokens. Overall, bringing mezzanine financing on-chain can provide investment channels for higher-yield assets, but to control risk, credible credit assessment and settlement mechanisms must be established on-chain, and it must be ensured that the interests of issuers and investors are aligned (e.g., the issuer retains a portion of the mezzanine tokens as a junior tranche to show they have "skin in the game"). Only then can on-chain mezzanine financing provide flexibility and returns while managing risk effectively.

The valuation of mezzanine instruments is highly sensitive to enterprise value and equity volatility, often requiring the use of complex option pricing models (like the Black-Scholes-Merton model). A dynamic valuation mechanism is crucial here.

Decentralized Valuation Models: RWA protocols can integrate decentralized valuation models that use oracles to provide real-time inputs on enterprise value, volatility, and market comparable data.

Increased Transparency: Although valuation remains challenging, the transparency of on-chain data and models can reduce information asymmetry (D_as) and improve the credibility of valuations.

3.3. Distressed Debt and Non-Performing Assets

The distressed loan space is one of the most challenging but also most transformative areas for RWA application. It is characterized by high risk, complex legal procedures, and extreme information asymmetry. The core value of RWA lies in improving coordination mechanisms and enforcement efficiency.

3.3.1. Market Background and Business Overview

Distressed credit refers to investing in the debt of financially troubled companies, including trading discounted bonds, providing bankruptcy restructuring financing (like DIP loans), and acquiring non-performing loan portfolios. This type of investment is extremely high-risk because the target companies are often already in default or on the brink of it, and recovery rates are highly uncertain. However, if the restructuring is successful or the economy improves, the returns on distressed debt can be substantial (sometimes referred to as "vulture investing"). Traditionally, the distressed debt market is dominated by a few specialized investment institutions with expertise in law, restructuring negotiations, and other areas. The asset disposal cycle can last for several years, and liquidity is extremely low. Within the framework of a private equity fund, LPs often have to wait until the end of the fund's life to know the final return, and exiting early is very difficult.

The underperformance of funds is not just due to poor asset selection, but a combination of structural factors: (1) macro shocks (Fed rate hikes, China's real estate crisis); (2) the structurally subordinated position of mezzanine/distressed debt; and (3) the critical challenge of cross-border enforcement, where "on-paper rights" are strong, but real-world recovery capabilities are weak. This is a common theme faced by Asia-focused distressed funds. The distressed debt market is large, although its fundraising activity is cyclical.

3.3.2. On-Chain Value Proposition and Opportunities

RWA tokenization cannot turn a bad asset into a good one. However, it can create a transparent and efficient market for the claims on that asset. By tokenizing a distressed loan, a protocol can create an immutable and auditable record of the claim, linked to all relevant documentation. This token can then be traded in a global, 24/7 market. Although distressed assets are extremely complex, there are still some promising directions for on-chaining. First, the blockchain can be used for the public auction of non-performing assets (NPAs). For example, banks or asset management companies can auction off NPA portfolios via smart contracts, with qualified investors bidding on-chain, and the winner receiving a tokenized certificate for the corresponding debt. Such a system could lower the barriers and intermediary costs of traditional auctions, enabling global investors to participate in bidding, or improve the price discovery efficiency for NPA disposal. Second, for NPAs requiring long-term restructuring, tokenized special purpose vehicles (SPVs) could be considered, packaging multiple claims and issuing tokens representing different tranches of equity. For example, an SPV holding claims on several distressed companies could issue two classes of tokens: senior and junior. Senior holders would have priority in receiving future recoveries but with a lower return cap; junior holders would receive the remaining proceeds after the senior tranche is paid, bearing greater loss risk but sharing in potential high returns. This is similar to traditional NPA securitization, but it uses the blockchain to distribute tokens, allowing more investors to participate. Such a structure can, to some extent, diversify the risk of individual debts and allow investors to invest in distressed assets in a portfolio manner.

When a company defaults, the valuation of its debt becomes highly uncertain. Tokenization can facilitate the trading of distressed debt claims (bankruptcy claims) by creating a standardized platform.

Increased Liquidity: Allows investors to cash out early during a lengthy restructuring process.

Transparent Price Discovery: Increases market transparency, which helps to more efficiently allocate capital to the investors most capable of carrying out a restructuring.

The restructuring process involves complex negotiations among multiple creditors. The traditional restructuring process is lengthy and expensive, and prone to "free-rider" problems and "holdout" strategies. We propose the concept of "Workout DAOs," which are decentralized autonomous organizations composed of creditors who use tokenized debt claims to vote and coordinate actions.

Decentralized Governance: Smart contracts can automate the voting process, making restructuring decisions more efficient and transparent.

Incentive Alignment: The mechanism design of the DAO can incentivize creditors to cooperate to maximize the overall recovery value.

Improved Coordination Efficiency: Reduces the reliance on centralized coordinators (like restructuring advisors), lowering costs.

Companies undergoing restructuring often need DIP financing to maintain operations. RWA protocols can facilitate the provision of DIP financing by tokenizing DIP loans and distributing them to a wider range of investors. The transparency and enforceability provided by smart contracts can reduce the risks associated with DIP financing.

3.3.3. Deeper Logic and Causal Links

Tokenization transforms the distressed debt problem from an opaque, bilateral negotiation process into a transparent, multilateral price discovery process. The logical deduction is as follows: First, the core problem with non-performing assets in private credit in China is not just the distressed state of the asset itself, but the uncertainty of its recovery value due to the opacity of the enforcement process. Second, a global limited partner (LP) has extremely limited information on how to enforce a claim within a specific Chinese jurisdiction. This information asymmetry leads the fund manager (GP) to apply conservative or even punitive markdowns when assessing the net asset value (NAV). Third, tokenizing the claim and posting it on a global ledger allows specialists (e.g., local Chinese law firms, specialized distressed asset funds) to analyze and bid on the token based on the same set of facts (the on-chain documents). These specialists have an informational advantage in assessing the true probability of recovery. Their bidding activity creates a market price for the claim that is more accurate than the GP's quarterly NAV markdown. Thus, the RWA protocol acts as a global matching engine, connecting distressed assets with the capital best equipped to price and manage them, ultimately leading to a better outcome for the selling LP.

3.3.4. Challenges, Solutions, and Real-World Cases

Tokenizing distressed debt with RWA faces a series of unique challenges. Legal enforcement is the primary hurdle: regardless of how a claim is brought on-chain, its collection still requires offline legal procedures (such as court judgments, bankruptcy proceedings, etc.). The actual rights of on-chain token holders need to be represented and enforced by an offline trustee or agent. Therefore, the legal arrangements behind the token must be clear, for example, by signing a trust agreement where a trustee holds the underlying debt and acts in the interest of the token holders. Once there is a settlement or restructuring plan, the trustee will distribute the cash flows to the token holders as pre-agreed in the smart contract. Second is information asymmetry and pricing: the value of distressed assets is highly uncertain and affected by factors like due diligence and the macro environment, so their on-chain trading price may fluctuate dramatically. Without sufficient information, investor participation will be limited. Therefore, it is necessary to use oracles to publish information such as court announcements, restructuring progress, and corporate operating data on-chain, ensuring that token holders are kept up-to-date and that smart contracts are automatically triggered to distribute funds or update token rights at important nodes (e.g., when the debtor sells assets to repay debt). Finally, there is the issue of coordination and governance: when a claim is converted into tokens held by dispersed investors, how can a unified opinion be reached in restructuring negotiations? One idea is to use DAO (Decentralized Autonomous Organization) governance, allowing token holders to vote on which restructuring plan to accept or what action to take against the defaulting company. This requires careful design of voting weights (which could be related to the number of tokens held and seniority) and precautions against coordination problems. But if it can be achieved, collective decision-making by on-chain holders would replace the role of the few creditor committees of the past, giving global investors the opportunity to participate in debt restructuring.

It must be emphasized that RWA tokenization cannot solve the fundamental legal challenges associated with enforcing claims in complex jurisdictions. As observed in the Asian private credit market, cross-border enforcement risk is a major obstacle.

The Persistence of Off-Chain Legal Reality: Smart contracts cannot automatically seize off-chain collateral or navigate complex bankruptcy proceedings. RWA is not a substitute for professional legal and restructuring expertise.

Indirect Improvement: However, by improving efficiency and coordination, RWA may enhance the collective bargaining power of debt holders and indirectly increase recovery rates. For example, by providing a shared, immutable registry of claims, it can simplify complex capital structures and reduce disputes.

Currently, on-chain distressed investing is in a very early exploratory stage. Some DeFi protocols have tried to venture into high-risk debt in emerging markets, such as the Goldfinch platform providing liquidity to fintech loans in developing countries, which resulted in some loan defaults, forcing the platform to scale back its operations. This shows that no matter how advanced the technology, the underlying credit risk always exists, and "even with tokenization, asset quality is still everything." Therefore, what RWA can do is improve the way assets are traded and held, not eliminate the risk itself. It is conceivable that in future market cycles, when large-scale distressed asset opportunities arise, there may be specialized "distressed asset DAOs" that raise funds from qualified investors to purchase and manage non-performing debt through on-chain mechanisms. Whether such a model can succeed depends on multiple factors, including the legal framework, participant trust, and project execution. Under permissive regulation and mature technology, on-chain distressed credit could become a complementary force to traditional vulture funds, opening up new channels for resolving non-performing financial assets.

3.4. Private Credit Secondaries: Solving the "Market for Lemons" Problem

The private credit fund secondary market is one of the most promising areas for RWA application. RWA can revolutionize this market by addressing the fundamental problems of illiquidity, information asymmetry, and high transaction costs.

3.4.1. Market Background and Business Overview

The private credit secondary market is experiencing explosive growth, with annual transaction volume projected to exceed $50 billion. Transactions are primarily divided into two categories: LP-led transactions (selling fund stakes) and GP-led transactions (setting up continuation funds). A key feature of this market is the significant discount to Net Asset Value (NAV), with discount rates often in the mid-to-high single digits or even higher, even for portfolios of well-performing senior loans. Secondary market transactions in private credit typically involve two scenarios: one is a limited partner (LP) selling their fund stake during the fund's life (i.e., exiting before the fund is liquidated); the other is the direct over-the-counter transfer of a single private loan or debt claim. Due to the lack of public market quotations and low information transparency for private funds and loans, buyers in the secondary market often demand a considerable discount to compensate for liquidity and information asymmetry risks. This often forces sellers to offload their assets at a price significantly below Net Asset Value (NAV). For example, during an economic downturn or when a fund's performance is poor, the trading price of a private debt fund stake might be only 80% of its nominal net value, or even lower, reflecting a huge NAV discount. This lack of liquidity not only deters investors but also limits the flexibility of private credit managers in managing their portfolios and optimizing their balance sheets.

3.4.2. Theoretical Framework: Akerlof's "Market for Lemons"

We will formally apply George Akerlof's theory of information asymmetry to analyze the private credit secondary market.

The Problem: The seller (LP) knows more about the true quality of the underlying loan portfolio of the fund they hold than the buyer. The buyer, aware of this, worries they will end up with a "lemon" (i.e., a fund with hidden credit problems).

The Result: The buyer will price all LP stakes as if they are of average quality, offering a price below the true value of high-quality ("peach") portfolios. This discount is a direct cost of information asymmetry. Sellers of high-quality assets are unwilling to sell at this discount, leading to market inefficiency.

The NAV discount (Discount = (NAV - Price) / NAV) is a function of the illiquidity premium (Π_L) and the adverse selection discount (D_as). RWA tokenization significantly reduces this discount through the following mechanisms:

Increased Liquidity: An efficient secondary market reduces search costs and transaction costs, compressing Π_L.

Increased Transparency: Standardized data disclosure and dynamic valuation mechanisms reduce information asymmetry, compressing D_as.

We anticipate that with the application of RWA in the secondary market, the NAV discount will converge significantly.

∂(Discount) / ∂(Liquidity) < 0

∂(Discount) / ∂(Transparency) < 0

3.4.3. On-Chain Value Proposition and Opportunities

A tokenized secondary market can directly solve this problem. If a fund's underlying loans have already been tokenized, the performance of the entire portfolio is transparent and verifiable on-chain. A buyer of a tokenized LP stake can directly audit the payment history, collateral status, and covenant compliance of every single loan in the portfolio. Introducing blockchain technology can establish a more efficient secondary market for private debt. A possible model is to represent private fund shares or loan claims as transferable tokens and list them for trading on a regulated on-chain trading platform. This way, fund shares that were originally locked up for 10 years would have the opportunity to be matched with other investors on-chain, providing a mid-term exit channel. Since global investors can participate in bidding via the internet, asset prices are expected to move closer to fair value, and the discount margin may narrow. For example, for a direct lending fund share with good asset quality, if there are dozens of potential buyers competing on-chain, the final transaction price might be only a small discount below the latest NAV, rather than being forced to accept a significant impairment as in traditional secondary transactions. This is beneficial for both the original holder and the new buyer: the former improves liquidation efficiency, and the latter acquires a quality asset at a fair price.

Tokenization automates the transfer process of LP interests, subject to predefined rules embedded in smart contracts (e.g., KYC/AML checks, GP consent). This reduces transaction costs (C_t) and settlement times (from weeks or months to minutes). Tokenized LP interests become fungible, facilitating easier trading and integration with DeFi infrastructure. For example, they can be used as collateral in lending protocols, further improving capital efficiency.

GP-led secondary transactions often involve conflicts of interest and valuation challenges. RWA protocols can optimize this process by providing transparent mechanisms for valuing assets and executing transactions. Utilizing decentralized valuation models and the ability for LPs to vote on transactions via a DAO can mitigate conflicts of interest and ensure fair pricing.

3.4.4. Deeper Logic and Causal Links

On-chain transparency acts as a credible "signaling mechanism," allowing sellers of high-quality portfolios to prove their quality, thereby breaking the information asymmetry and reducing the NAV discount. The mechanism works as follows: First, the current NAV discount in the secondary market is essentially a proxy for the cost of due diligence and the risk of buying a "lemon." Second, tokenizing the underlying assets creates an immutable, real-time audit trail. This dramatically reduces the due diligence cost and time for a potential buyer. A seller of a "peach" portfolio can point to the on-chain data as irrefutable proof of its high quality. The buyer can therefore price that specific portfolio accurately, rather than based on a market average. This should lead to a narrowing of the bid-ask spread and a compression of the NAV discount for high-quality assets. The third-order effect is that a more efficient secondary market increases the ex-ante attractiveness of private credit as an asset class for all LPs, as it provides a more reliable path to liquidity.

3.4.5. Market Depth, Mechanisms, and Case Prospects

It is worth noting that tokenization does not automatically guarantee liquidity. Many current RWA tokens have long holding periods and infrequent transactions, remaining in a "buy and hold" state. The reasons for this phenomenon, besides the long-term, low-liquidity nature of the underlying assets, include structural obstacles such as platform restrictions (many RWA markets are limited to whitelisted institutional traders, restricting the investor base), centralized custody (most tokens are held by a few custodians, limiting supply), and opaque valuation (investors have difficulty knowing the true value of assets in a timely manner). To truly improve secondary market activity, efforts are needed on multiple fronts: first, introduce market makers or adopt Automated Market Maker (AMM) mechanisms to improve continuous quoting capabilities; second, enhance the frequency of on-chain information disclosure, for example, by regularly updating key metrics like the underlying asset's cash flow and NAV valuation via oracles to reduce information asymmetry; third, explore cross-protocol collateralization and lending, allowing holders to obtain temporary liquidity by pledging their tokens to borrow funds if they cannot find a buyer. In fact, this collateralized financing function has already appeared in practice: DeFi protocols like MakerDAO accept audited RWA tokens as collateral to provide stablecoin loans (usually at a conservative loan-to-value ratio), which is equivalent to providing a "liquidity buffer" for the secondary market. Taking the Centrifuge platform as an example, over 85% of its issued senior loan tokens have been used as collateral to borrow stablecoins from MakerDAO. This means that even in the absence of active buy orders, token holders can obtain partial funds through DeFi without having to sell their assets at a low price.

Suppose the aforementioned private credit fund maps its still-active loan asset shares into on-chain tokens and introduces a more diverse set of buyers. In that case, the fund's LPs, whose positions were difficult to transfer off-chain, might be able to sell part of their holdings on-chain at a price close to net value, thereby improving interim performance. Not only that, the public transparency of on-chain transaction records can also provide market feedback for valuation, allowing fund managers to adjust their investment strategies accordingly. It is foreseeable that as legal and regulatory clarity gradually emerges (for example, some jurisdictions have already enacted legislation recognizing the legality of on-chain securities transfers), the on-chain secondary market for private debt will further mature. At that time, NAV discounts will no longer be a persistent headache for LPs, and investors will be able to enter and exit more flexibly, thereby increasing the attractiveness of the entire asset class. Of course, even on-chain, the liquidity of complex assets depends on buyer depth and risk appetite. For assets with poor credit quality or complex structures, discounted trading may still exist, but overall, the on-chain market should promote more effective price discovery and lower transaction friction, achieving a gradual improvement in liquidity in the private credit sector.

3.5. Portfolio Financing and Structured Products: Restructuring the Fund's Liability Side

Portfolio financing (NAV loans) provides funds with leverage and liquidity. RWA tokenization can significantly improve the efficiency and security of NAV loans.

3.5.1. Market Background and Business Overview

Private credit funds use a variety of leverage tools on their liability side to enhance returns and manage liquidity. These tools include Subscription Credit Facilities, used early in a fund's life and secured by LP commitments, and Net Asset Value (NAV) Facilities or CLO-like structures, used later in a fund's life and secured by the asset portfolio. These are complex, customized financial instruments intermediated by large banks. Another important form in private credit is structured financing for portfolios, which involves packaging a group of loans or debt claims for credit enhancement and issuing securities with different priority tranches to raise capital. A typical example is the Collateralized Loan Obligation (CLO). In traditional finance, a CLO is held by a special purpose vehicle (SPV) that owns a pool of loan assets and raises funds by issuing tranches of bonds, such as senior and subordinated. Senior investors enjoy lower risk (as the junior tranche acts as a buffer, absorbing losses first) and more stable interest, while junior investors bear the first loss but receive higher returns if the assets perform well. This structure improves overall financing efficiency through risk sharing, allowing high-credit and low-credit investors to each get what they need. A similar structured product can be built entirely on-chain, viewed as a type of RWA: smart contracts replace traditional SPVs and trustees, achieving automatic cash flow distribution and risk tranching.

3.5.2. On-Chain Value Proposition and Practices

If a fund's entire loan portfolio is tokenized, this digital asset portfolio can serve as dynamic, transparent, and verifiable collateral for on-chain lending. A fund manager could deposit their tokenized loan portfolio into a decentralized lending protocol (e.g., a permissioned version of Aave) and borrow stablecoins against it.

The most compelling current example comes from on-chain asset securitization platforms like the Centrifuge protocol. The way it works is: an asset originator sells a series of real-world loans to an SPV entity, which then issues two types of debt tokens (usually a senior tranche and a junior tranche) through the Centrifuge on-chain protocol, backed by the cash flows from this pool of loans. The originator typically holds the junior token (the "first loss" piece) themselves, while selling or pledging the senior token for financing. To control risk, the total value of the senior tokens usually does not exceed 70% of the asset pool's balance. This structure ensures that even if some underlying loans default, the senior holders are highly likely to be fully repaid, as losses are first absorbed by the junior tokens held by the originator. This on-chain CLO can automatically execute complex profit distribution rules: the smart contract, based on the actual repayments from borrowers, first pays the agreed interest to the senior token holders, and after the principal is repaid, distributes the remaining profits to the junior token holders. This process is transparent and efficient, greatly reducing the costs of manual reporting, accounting, and agency in traditional CLOs.

RWA tokenization enables dynamic management of the collateral pool. Tokenized assets can be pledged as collateral in a smart contract, and dynamic valuation mechanisms can be used to monitor the loan-to-value (LTV) ratio in real time.

LTV(t) = Loan Amount(t) / Collateral Value(t)

If the LTV exceeds a predetermined threshold, the smart contract can automatically trigger a margin call or liquidate a portion of the collateral. This reduces the lender's risk (by reducing the loss given default, LGD). Traditional NAV loans rely on stale, GP-reported NAV. RWA provides real-time, verifiable data, allowing lenders to better assess the risk of the underlying portfolio, thus enabling more accurate pricing and higher LTVs. GPs and LPs can obtain NAV loans through DeFi lending protocols, broadening their financing channels and potentially lowering borrowing costs. DeFi lending pools provide a transparent, market-based pricing mechanism.

3.5.3. Deeper Logic and Causal Links

On-chain portfolio financing can create a more efficient, flexible, and real-time "operating system" for fund-level leverage, replacing the static, periodic financing model dominated by traditional banks. The logical evolution is as follows: traditional NAV loans require periodic, manual valuation and reporting to the lending bank, which creates operational friction. In contrast, for a tokenized loan portfolio, the value and performance data (cash flows, default status) are updated on-chain in real time. A smart contract-based lending protocol can use this real-time data to continuously calculate a borrowing base (Loan-to-Value, LTV). This allows fund managers to dynamically draw down and repay capital as needed, without having to negotiate with a bank for each transaction. This transforms fund leverage from a series of discrete financing events into a continuous, real-time capital management process. This could lead to higher capital efficiency, lower borrowing costs (by reducing intermediaries), and enable smaller funds to access leverage tools that were previously only available to the largest players.

3.5.4. Liquidity, Derivative Space, and Comprehensive Outlook

Portfolio tokenization also opens up new possibilities for liquidity. On one hand, the senior and junior tokens themselves can be traded on on-chain markets, allowing investors to adjust their positions according to their risk appetite. However, as of now, the secondary market for such tokens is still not active; for example, many tokens issued by Centrifuge have not yet established active trading markets. Therefore, to improve liquidity, protocol designers often introduce other means: such as allowing senior tokens to be directly used as collateral in DeFi to borrow stablecoins (as mentioned earlier with MakerDAO accepting senior RWA tokens for loans), or by the platform providing buyback support. On the other hand, as the RWA market develops, there is huge innovation space for derivatives based on these underlying tokens. For example, on-chain credit default swap (CDS) contracts could be designed for senior tokens, with third parties providing insurance, allowing senior token holders to further hedge default risk; or leverage tokens could be designed for those with a higher risk appetite to amplify their exposure to junior tokens. Through these derivative tools, market participants can manage risk and return more precisely, improving overall market efficiency. It is also worth mentioning that cross-chain interoperability will enhance the utility of portfolio financing tokens—as technologies like the Chainlink Cross-Chain Interoperability Protocol (CCIP) mature, these RWA tokens can move freely between different public chains, trading on whichever chain has the best liquidity, not limited to a single network.

On-chain structured financing of portfolios represents a direction of deep integration between private credit and DeFi. It retains the essence of traditional structured products (tranching for credit enhancement, risk pricing) while leveraging blockchain technology to lower barriers and increase transparency. Once legally and regulatorily permissible, fund managers could more conveniently convert their loan portfolios into on-chain SPVs to issue tokens, allowing institutional investors to subscribe to the senior tranche, and family offices and high-net-worth clients to subscribe to the junior tranche, achieving rapid financing. For investors, this means access to a richer variety of fixed-income products: both on-chain senior bonds that are close to investment grade, and on-chain junior tokens similar to high-yield debt, which can also be traded in secondary markets or pledged for loans. It must be emphasized that the risk is still real—if the underlying loan pool experiences systemic defaults, investors will still suffer losses even if the on-chain contracts operate as expected. Therefore, the on-chaining of portfolios is not about reducing risk through technology, but about attracting more diverse capital through better risk allocation and liquidity management, thereby lowering financing costs and enhancing market resilience. In the long run, this model could be extended to a wider range of asset types, such as real estate mortgage pools, infrastructure project revenue rights, etc., all of which could achieve securitized financing through on-chain SPVs, heralding a new era of asset securitization.

4. The RWA Protocol Stack and Implementation Framework: The Protocolization of Debt

Transforming private credit assets into on-chain RWA is not a monolithic process. It requires a carefully designed, multi-layered infrastructure stack that combines the legal structures and risk management practices of traditional finance with the advantages of blockchain technology. We propose a five-layer model for implementing RWA protocols in the private credit space, aimed at achieving the "Protocolization of Debt." This model emphasizes how to use technological means to solve the core pain points of the private credit market within a compliant framework and draws inspiration from the "Matryoshka doll" protocol concept to adapt to the evolving regulatory environment.

This section will shift from "what" and "why" to "how." We will follow the five-step framework provided by the user to systematically build a protocol architecture designed to achieve the objectives described in Part 1. Combining the analysis above, we can propose a step-by-step implementation framework for advancing private credit RWA to ensure a smooth landing. In summary, the entire process can be divided into five key steps.

4.1. Layer 1 / Step 1: Asset Identification & Legal Engineering (The Foundational Layer - The Legal Wrapper)

The foundational layer involves identifying specific private credit assets suitable for tokenization and establishing the legal framework that connects the off-chain asset to the on-chain token. This is the legal bedrock of the entire RWA structure, and its core lies in ensuring the legal enforceability of the token holder's rights and bankruptcy remoteness. This is also the most critical step, as it builds a legally robust bridge between the off-chain asset and the on-chain token. The value of the token is entirely dependent on the strength of this connection.

4.1.1. Asset Selection and Preparation

First, it is necessary to select suitable underlying assets to bring on-chain. These are often debts with relatively stable cash flows, clear structures, and simple legal relationships, such as high-quality corporate loans, accounts receivable pools, or specific project financings. The asset originator should conduct thorough due diligence on the candidate assets to confirm that their ownership is clear, there are no legal disputes, and to assess the feasibility of securitizing them. We classify assets based on the predictability of their cash flows, legal clarity, and degree of standardization.

High Feasibility: Senior secured direct loans with clear amortization schedules and strong collateral.

Medium Feasibility: Mezzanine loans, which are more complex due to their structural subordination and potential equity features.

Low Feasibility: Deeply distressed debt, especially in jurisdictions with weak enforcement mechanisms.

At the same time, it is necessary to design an off-chain legal vehicle (such as establishing an SPV or a trust) to hold the assets, preparing for the on-chain issuance. At this stage, regulatory requirements must also be considered: whether the jurisdiction of the asset permits its transfer, and if it involves cross-border transactions, whether it complies with foreign exchange and securities regulations. If necessary, a vehicle company can be established in a region with a more favorable legal environment to reduce subsequent compliance hurdles.

4.1.2. Legal Structure Design: SPV and Bankruptcy Remoteness

The core mechanism is the use of a bankruptcy-remote Special Purpose Vehicle (SPV).

The private credit asset (e.g., a loan agreement) is legally transferred or sold to an SPV.

This SPV is an independent legal entity whose sole purpose is to hold the asset. Its corporate charter restricts it from incurring other debts or liabilities, thus isolating it from the bankruptcy risk of the asset originator.

The SPV then issues on-chain tokens that represent a beneficial interest in or a direct claim on the assets held by the SPV.

To achieve Bankruptcy Remoteness, a Special Purpose Vehicle (SPV) must be established. The SPV acquires the loans from the originator (GP) and issues securities representing the beneficial interest in the assets.

True Sale: The transfer of assets from the originator to the SPV must constitute a "true sale" under applicable law, ensuring the assets are legally isolated from the originator's balance sheet. This requires a legal opinion and must meet a series of criteria, such as the intent of the transfer, the fairness of the consideration, and the degree of control the originator retains over the assets.

Non-Consolidation: It must be ensured that the assets and liabilities of the SPV will not be consolidated with those of the originator in the event of the originator's bankruptcy. This requires the SPV to maintain a separate legal personality, adhere to corporate governance procedures, and avoid excessive commingling with the originator's business.

The rights of the token holders are written into the legal agreements governing the SPV. In the event of a default, token holders, through a trustee, have a direct legal claim on the assets held in the SPV, thereby bypassing any bankruptcy proceedings of the original loan originator. This structure provides a clear path for regulatory compliance. The tokens issued from the SPV can be treated as a securities offering, subject to the regulations of the relevant jurisdiction (e.g., Reg D/S in the United States). This allows the protocol to operate in a permissioned environment, ensuring all token holders have undergone the necessary Know Your Customer (KYC) and Anti-Money Laundering (AML) checks.

The SPV structure is not just a legal shell; it is a foundational mechanism that transforms a bilateral contract (a loan agreement) into a capital markets instrument akin to a bearer instrument (a token), while preserving legal recourse. The underlying logic is this: a loan agreement is a private contract between two parties, and its transfer is cumbersome. Placing it in an SPV legally isolates it. The SPV can then issue standardized securities (i.e., tokens) against this isolated asset. This process is analogous to traditional securitization (e.g., creating mortgage-backed securities), but replaces paper certificates and centralized depositories with programmable, on-chain tokens.

4.1.3. Choice of Jurisdiction and the "Protocolization" Strategy

The choice of jurisdiction for the SPV is crucial, as it affects the legal framework, tax treatment, and regulatory environment.

Cayman Islands / BVI: Traditional offshore financial centers that offer tax neutrality and flexible corporate law, but may face regulatory scrutiny in some cases.

Delaware (USA): Offers a mature legal system and case law, especially Delaware Statutory Trusts (DSTs), which are often used in securitization structures.

Singapore / Hong Kong: Actively developing RWA regulatory frameworks, offering legal certainty and access to Asian markets.

Europe (Luxembourg / Ireland): Offer well-established securitization legal frameworks, but with higher compliance costs.

Traditional financial regulatory frameworks focus on the nature of intermediaries and instruments. However, an emerging, cutting-edge strategy involves the "protocolization" of processes to leverage regulatory ambiguity. By designing the RWA infrastructure as a decentralized protocol (software) rather than a centralized financial entity, it may be possible to circumvent the need for traditional financial licenses (e.g., broker-dealer, investment advisor). The core argument of this strategy is based on the decentralized nature of the technology. If a protocol is sufficiently decentralized, it may not be considered a centralized intermediary. Furthermore, recent regulatory developments, such as the US SEC's adjustments to the classification of certain NFTs and crypto assets (no longer universally deemed securities), provide greater flexibility for this protocolized packaging. If an RWA token is designed with utility functions or uniqueness (using NFT standards), rather than as a purely passive investment tool, compliance costs may be reduced. By "nesting" the concept of private credit within a decentralized protocol and mobilizing a decentralized network to manage and operate it, we can build a self-sustaining ecosystem that bypasses existing licensing regimes. This represents a key avenue for regulatory arbitrage, but it requires careful design at both the legal and technical levels to ensure its legality and sustainability.

4.2. Layer 2 / Step 2: Validation, Oracles, & Dynamic Due Diligence (The Trust Layer - The Information Bridge)

This layer ensures that the on-chain token accurately reflects the status and performance of the off-chain asset, addressing the critical problem of information asymmetry. It is the technical solution to the "market for lemons" problem. The blockchain cannot verify the truth of the external world, known as the "Oracle Problem."

4.2.1. Data Integrity and Oracle Integration

After the asset is selected, data regarding its quality and performance must be brought onto the blockchain. This includes the borrower's credit information, the condition of the collateral, and historical cash flow records. This step is usually accomplished with the help of an oracle network, such as using Chainlink to bring off-chain data on-chain. Oracles are data messengers that securely bring off-chain information on-chain. For private credit, they would be responsible for reporting key data points attested to by trusted third parties (like fund administrators, auditors).

Performance Data: Reporting on interest and principal payments by the borrower.

Valuation Data: Reporting quarterly NAV or updated market values of the underlying assets.

Credit Events: Reporting covenant breaches, defaults, or restructuring events. Chainlink's Proof of Reserve is a relevant existing model for this function.

To ensure data reliability and credibility, a dual verification method can be adopted: an independent third-party institution issues a due diligence report or audit certificate, and then an oracle publishes a hash signature to prove that the report's content has not been tampered with. Additionally, services like Chainlink's Proof-of-Reserve can be utilized to disclose the correspondence between the assets held by the SPV and the issued tokens in real time. If the asset changes dynamically (e.g., the loan ledger constantly has repayments and drawdowns), the oracle needs to regularly update the key status, so that the on-chain token always "anchors" the real-world asset situation. In this process, a credible oracle mechanism is crucial—it acts as a bridge between on-chain investors and the real asset. If it breaks or becomes distorted, investor confidence will be damaged. Therefore, a mature oracle solution should be chosen, and decentralized data sources should be considered to ensure that off-chain events (like borrower repayments, defaults) can be reflected on-chain in a timely, accurate, and highly attack-resistant manner.

4.2.2. Decentralized Validation and Dynamic Valuation

The traditional due diligence process is opaque and centralized. In the RWA model, due diligence can be standardized and its credibility enhanced through a decentralized network of validators.

Validator Roles: Professional credit analysts, law firms, valuation agencies, and auditors act as validators, assessing various aspects of the asset (legal compliance, financial condition, collateral value) and signing their evaluation results on-chain (Attestation).

Incentive Mechanism Design (Cryptoeconomics): Validators are required to stake a certain amount of tokens as a bond. If they provide false information or are negligent, their staked tokens will be slashed. A Reputation System influences their future earnings and participation eligibility.

To ensure the credibility of validation results and prevent single points of failure, it is necessary to utilize Decentralized Oracle Networks (DONs), such as Chainlink. DONs cross-verify the same information through multiple independent nodes and connect to diverse, reliable data sources.

For illiquid Level 3 assets, valuation is a core challenge. RWA protocols can implement dynamic valuation mechanisms to improve the frequency and accuracy of valuations, for example, by using automated valuation models (AVMs) or by leveraging a decentralized appraisal network to form a valuation consensus.

4.2.3. Innovative Application: Decentralized Identity (DID) and Verifiable Credentials (VC)

We propose here a significant innovation that goes beyond simple data oracles. Decentralized Identity (DID) and Verifiable Credentials (VCs) can be used to create a standardized, cryptographically secure, and privacy-preserving due diligence file for borrowers and assets on-chain.

How it works: A borrower (e.g., a middle-market company) is issued a DID, which is a unique on-chain identifier they control. Trusted off-chain entities (auditors, credit rating agencies, law firms) issue VCs to the borrower's DID. A VC is a tamper-proof digital statement.

VC Examples: "KPMG attests that Company X's 2024 financial statements are audited and accurate." "Moody's attests that Company X's credit rating is Baa2." "Law Firm Y attests that this loan agreement is valid and enforceable."

The borrower can selectively present these VCs to the protocol for verification without revealing all their underlying private data. The protocol's smart contract can cryptographically verify the authenticity of the VC (i.e., that it was indeed signed by KPMG).

4.2.4. Deeper Logic and Privacy Preservation

Combining oracles for performance data with DIDs/VCs for static due diligence data creates a "Trust-as-a-Service" layer for private credit, fundamentally reducing information asymmetry and due diligence costs for all market participants. The logical chain is this: The core problem in credit is trusting the information provided by the borrower/originator. Traditionally, this trust is established through expensive, repetitive, and manual due diligence conducted by each investor. DIDs/VCs allow this due diligence to be performed once by a trusted issuer (like an auditor) and then presented in a standardized, verifiable, and reusable digital format. This dramatically lowers the barrier to entry for new investors, enables faster underwriting, and lays the groundwork for a more liquid and efficient secondary market.

Private credit transactions involve a large amount of sensitive financial data. Disclosing this information on a public blockchain would raise privacy concerns and compliance risks (like GDPR). Zero-Knowledge Proofs (ZKPs) technology has a key application value in RWA. ZKPs allow for the verification of information's truthfulness without revealing the underlying data. For example, a borrower can use a ZKP to prove they meet a financial covenant without disclosing their full financial statements. This strikes a balance between protecting business secrets, complying with data privacy regulations, and increasing transparency.

4.3. Layer 3 / Step 3: Tokenomics & Smart Contract Architecture (The Execution Layer - The Financial Logic)

This layer defines the technical specifications of the token, the economic model, and the smart contracts that manage its lifecycle, designing the rules and incentives that govern the protocol and align the interests of its participants. This is where the financial logic of a private credit investment is codified.

4.3.1. Theoretical Framework and Protocol Design

We apply agency theory (Jensen and Meckling) to the design of the protocol. The traditional GP/LP relationship is a classic principal-agent problem. In our protocol, the asset originator (the new GP) is the agent, and the token holders (the new LPs) are the principals. The protocol itself, managed by a Decentralized Autonomous Organization (DAO), must mitigate agency costs.

Governance Token (GOV): A separate token used for voting on protocol parameters (e.g., which asset originators are whitelisted, what types of assets are eligible).

Asset Originator Staking: To be allowed to bring assets to the protocol, asset originators must stake a significant amount of the protocol's GOV tokens. This stake acts as a "bond" that can be slashed if the originator provides fraudulent information or if the assets they originate significantly underperform. This creates "skin in the game."

Fee Sharing: Protocol revenue (e.g., a percentage of the interest paid by borrowers) is distributed to stakers of the GOV token. This aligns the long-term incentives of the protocol's governors with the performance of the assets on the platform.

Addressing "Whale" Risk: We will explore mechanisms like quadratic voting or time-weighted voting (vote-escrowed models) to mitigate the risk of voting power being concentrated in the hands of large token holders, ensuring a more democratic governance process.

4.3.2. Token Structure and Smart Contract Logic

The third step is to design the specific token structure and smart contract logic. This involves several key points:

Token Type Selection: First, decide on the token type, whether a fungible token (ERC-20) is suitable for divisible beneficial interests, or a non-fungible token (ERC-721/NFT) is more appropriate for representing each loan individually. We argue that Semi-Fungible Tokens (SFTs, like ERC-3525) offer the best balance for private credit. SFTs allow for the fractionalization of a unique asset (e.g., a specific loan) while maintaining fungibility between the different shares.

Rights Determination: Second, determine the rights represented by the token: whether it represents a direct claim on cash flows or a beneficial certificate of equity in the SPV. This relates to the legal classification and securities nature of the token.

Smart Contract Functionality: The contract should clearly define the rules for distributing the underlying asset's cash flows to the holders, as well as the handling of situations like default, prepayment, etc. Smart contracts automate the entire lifecycle of the loan:

Origination and Issuance: Automatically mint tokens upon successful financing and verification.

Cash Flow Distribution (Waterfall Model): The smart contract automatically calculates and distributes interest and principal to token holders according to a predefined waterfall logic.

Covenant Monitoring & Enforcement: Automatically check for compliance with financial covenants based on data inputs from Layer 2 and automatically trigger predefined actions.

Default Management & Restructuring: The smart contract can manage the voting process among token holders and execute the agreed-upon restructuring plan.

Fee Model and Audit: The fee model (such as how service fees, management fees are collected) should also be specified in the contract. Finally, ensure that the smart contract is fully tested and audited to be logically correct and free of vulnerabilities.

4.3.3. Deeper Logic and Causal Links

Tokenomics allows for the programmatic enforcement of incentive structures that can only be crudely approximated by legal contracts (like the Limited Partnership Agreement, LPA) in traditional finance. In a traditional fund, aligning the interests of the GP and LP relies on fee structures and legal covenants, which are slow and expensive to enforce. In a tokenized protocol, incentive alignment can be enforced by code. An asset originator's ability to earn future revenue is directly and automatically tied to their staked capital and the real-time performance of their past assets. This creates a more direct and powerful feedback loop that punishes bad actors and rewards good ones more efficiently than the traditional model.

4.4. Layer 4 / Step 4: Liquidity Solutions & Market Design (The Trading Layer - The Marketplace)

This layer focuses on creating a functional secondary market for the tokenized credit assets, addressing the core challenge of illiquidity in private credit.

4.4.1. Liquidity Bootstrapping and Market Building

Once you have tokens, the key is to establish their trading and pricing mechanisms on-chain.

Choosing a Trading Venue: The project team typically needs to choose a suitable trading venue, which could be creating a trading pool on a decentralized exchange (DEX) or listing on a compliant security token trading platform. Given regulatory constraints, the initial phase will primarily adopt a Permissioned DeFi model, restricting access through a KYC/AML whitelist mechanism.

Cultivating Early Liquidity: Consider introducing market makers or providing liquidity incentives.

Encouraging Information Transparency: Continuously disclose asset dynamics through oracles and on-chain announcements, allowing potential investors to assess the investment value of the token.

Exploring DeFi Integration: Integrate the token into decentralized lending platforms as collateral, or join DAO governance systems to increase the token's use cases.

4.4.2. AMM Innovations for Illiquid Assets

Standard Automated Market Makers (AMMs) (like Uniswap V2's x*y=k model) are designed for highly liquid, frequently traded assets and are not suitable for RWA, where low trading frequency and a slow pricing heartbeat would cause liquidity providers (LPs) to earn minimal fees and suffer certain impermanent loss. Novel AMM designs are needed to accommodate the characteristics of RWA:

Concentrated Liquidity (like Uniswap V3): Allows LPs to deploy capital within specific price ranges, improving capital efficiency.

Dynamic AMMs (DAMMs) with Oracle Integration: Adjust the bonding curve based on external price inputs (e.g., a dynamic NAV) to reduce impermanent loss.

Interest-Bearing Asset AMMs: Design AMM models that can automatically capture and distribute accrued interest.

Hybrid Models (CLOB + AMM): Combine a central limit order book (CLOB) with an AMM liquidity pool to provide flexibility and market depth.

4.4.3. Deeper Logic and Market Challenges

There is no one-size-fits-all liquidity solution for RWA. The optimal design requires segmenting the market based on participant type and trade size and creating tailored mechanisms for each segment. Institutional LPs and retail users have different liquidity needs. A hybrid model recognizes this reality. A Request-for-Quote (RFQ) system or an order book caters to the institutional need for price negotiation on large block trades, while a specialized AMM caters to the retail user's need for "always-on" liquidity for smaller trades. This layering creates a more robust and efficient overall market structure.

The transparency of on-chain trading introduces new challenges, such as market manipulation and Maximal Extractable Value (MEV). MEV-resistant mechanisms, such as Frequent Batch Auctions, need to be designed to protect the fairness of the market.

4.5. Layer 5 / Step 5: Derivatives & Structured Products (The Advanced Financialization Layer - The Financial Engineering)

This section looks ahead to a future state where on-chain private credit assets become the building blocks for more complex financial products, leveraging the Composability of DeFi protocols to achieve advanced financial engineering and risk management.

4.5.1. On-Chain Derivatives and Advanced Feature Development

Once the underlying spot market is robust, one can consider building derivative instruments and more complex financial products around the RWA tokens.

On-Chain Securitization (CLOs): A pool of tokenized direct loans can be deposited into a "securitization smart contract" that issues new tokens of different tranches, creating a fully transparent, on-chain Collateralized Loan Obligation (CLO). The payment waterfall would be automatically executed by the smart contract. Compared to traditional CLOs, on-chain CLOs offer advantages of real-time transparency, automated administration, flexibility and customization (Micro-CLOs).

Credit Derivatives: With transparent, real-time data on credit events, the creation of decentralized Credit Default Swaps (CDS) becomes possible. A user could pay a premium to a protocol to receive a payout in the event of a default on a specific tokenized loan.

Interest Rate Derivatives & Yield Stripping: An on-chain Interest Rate Swap (IRS) market would allow investors to hedge against interest rate volatility. Furthermore, yield stripping techniques can be used to separate the yield of an RWA token into a principal component and an interest component, which can be traded separately.

Leveraged Products: Tokenized private credit assets can be used as collateral in DeFi lending protocols to obtain leverage. This improves capital efficiency but also introduces systemic risks.

The existence of derivatives can enrich the strategies of market participants, such as hedging, speculation, and arbitrage, thereby enhancing market depth and pricing efficiency. However, the development of derivatives must also be conducted within a regulatory framework, paying particular attention to preventing excessive leverage and interconnected risks.

4.5.2. Deeper Logic and Causal Links

The composability of DeFi allows for the rapid, permissionless creation of structured products that would take months and millions of dollars in legal fees to create in traditional finance. In traditional finance, creating a CLO is a complex process. On-chain, its core logic (asset pooling, cash flow tranching) can be encoded in a reusable smart contract template. In theory, an asset manager could create a customized on-chain CLO in a fraction of the time and at a fraction of the cost. This would democratize access to financial engineering tools and could spark a new "Cambrian explosion" of customized credit products.

4.6. Five Practical Routes for On-Chaining Private Credit

The following summarizes the five main practical routes for bringing private credit on-chain and their engineering objectives.

The first route is the combination of an asset originator with a "permissioned chain/compliant market." The typical practice is to digitize the entire off-chain loan process on a permissioned chain oriented towards financial institutions: customer acquisition and underwriting are still handled by teams familiar with the industry, but after approval, the loan generates a traceable "native ledger entry" on-chain. It then enters the pooling and securitization phase, listed for bidding on a compliant digital asset trading system for institutions and brokers who have passed KYC/AML. After the transaction, servicing and collection data are fed back on-chain as a standardized event stream, forming an automated closed loop for reconciliation, distribution, and auditing.

The second route is the DeFi-style "on-chain direct lending" protocol. Its core is the "credit manager/pool administrator" model: a trusted professional underwriter is responsible for pre-loan due diligence, pricing, and post-loan management. They set up a funding pool on-chain and publish an investment memorandum and risk terms. Qualified investors subscribe to pool shares with stablecoins or tokens. After the funds are locked on-chain, they are disbursed to the off-chain borrower according to the contract. Repayments are remitted by the trusted institution at set intervals and automatically split into principal, interest, and fees by a smart contract before being redistributed to the LPs.

The third route is the prototype of an "RWA asset securitization platform" and "on-chain CLO." The common structure involves an originator making a true sale of a basket of loans to an SPV. The platform then issues two classes of debt tokens on-chain: a senior tranche corresponding to a lower yield but enjoying priority of payment, and a junior tranche serving as a first-loss buffer. A smart contract codifies the cash flow waterfall: senior interest and principal are paid first, and the remaining profit is distributed to the junior tranche. Default losses first reduce the net value of the junior tranche, and only affect the senior tranche after a trigger threshold is reached.

The fourth route is tokenized "private credit fund/fund-of-funds" shares. Instead of bringing individual loans on-chain, this directly digitizes the LP shares of a fund, issuing compliant tokens to qualified investors. The on-chain system maintains a holder registry, subscription/redemption records, and dividend distributions. To provide controlled liquidity during the lock-up period, a common technique is to embed a redemption pool in the contract, capped at a percentage of NAV, while also opening monthly or quarterly windows for larger redemptions.

The fifth route is to integrate "on-chain private credit" into the larger DeFi liquidity network. Senior debt tokens, due to their risk characteristics being similar to stable cash-flow notes, can be accepted as collateral by major stablecoin protocols. Permissioned RWA lending markets allow stablecoin lenders to allocate idle funds to real-world loan pools. Cross-chain technology and oracles publish audit certificates, ledger balances, and event notifications of off-chain assets on-chain, maintaining a one-to-one correspondence between the "on-chain certificate" and the "off-chain asset."

At the pain point level, these routes correspond to the same set of engineering objectives: on the fundraising side, to expand the reach to qualified investors; on the liquidity side, to inject a "controllable liquidity gate" for long-term assets; on the operational side, to replace manual accounting with contractual distribution; and on the risk pricing side, to make risk appetite and loss absorption transparent upfront through tranching and cash flow waterfalls. For managers, these approaches are not mutually exclusive: the same portfolio can have its native accounting and asset registration done on a permissioned chain, while the settlement and collateralization of its shares are handled on a public chain.

If one intends to quickly implement their own direct lending, mezzanine, or portfolio financing according to the ideas above, the practical process usually starts with asset selection and legal vehicle setup: screen for targets with clear cash flows and well-defined rights, and establish an SPV or trust to complete a true sale or transfer of beneficial rights. Next, agree on data publication and validation frequency with auditors, rating agencies, or data service providers, and convert it into an on-chain-compatible data structure. Then, on the contract side, determine the token form and the rights it represents. In parallel, select liquidity entry points and counterparty networks. Finally, proceduralize the operational aspects to ensure the consistency of "cash, certificate, and accounts." After completing this engineering process, the private credit asset is migrated from a heavy off-line process to a track of "contract automation + compliant distribution + controlled liquidity," retaining the professional judgment of underwriting and post-loan management while gaining the infrastructure capabilities of on-chain transparency, composability, and cross-border accessibility.

5. The Liability-Side Revolution: The Impact of RWA on Capital Formation, Liquidity Management, and Risk Reshaping

While the application of RWA on the asset side is significant, we argue that its most profound impact on the private credit market will occur on the liability side. It will fundamentally change the financing models, capital structures, and risk management methods of GPs. Especially in the current context where the private credit market faces structural predicaments, innovation on the liability side is particularly urgent.

5.1. Liability-Side Strategies to Address the Current Credit Predicament: Lessons from the Asian Market

Facing the predicament of NAV markdowns, declining IRRs, and delayed exits, GPs need to take active measures to manage liquidity, stabilize fund performance, and restore LP confidence. RWA provides a new toolbox on the liability side to manage the consequences of distress, rather than trying to fix the underlying asset quality problems.

5.1.1. Liquidity Release and Re-securitization of Quality Assets (Avoiding Fire Sales)

Even in a stressed fund, there are some well-performing assets that can generate stable cash flows ("crown jewels"). GPs can package and tokenize these quality assets for re-securitization.

Mechanism: Isolate the quality assets into a new on-chain structure (e.g., a mini on-chain CLO) and issue new tokens. The GP can sell some of the senior tokens to raise capital or use the tokens as collateral to obtain financing in the DeFi lending market.

Purpose: The liquidity obtained can be used to repay fund-level debt, meet LP redemption requests (providing partial liquidity), or provide capital for the restructuring of distressed assets (Workout Financing).

Advantage: This avoids the need to sell quality assets at fire-sale prices, preserving long-term upside potential. This helps to improve the fund's interim IRR and DPI (Distribution to Paid-In Capital) and stabilize LP confidence.

5.1.2. Isolation and Disposal of Non-Performing Assets (On-Chain Side Pockets and NPL Auctions)

For non-performing assets that are already in default or facing severe distress ("toxic assets"), RWA provides an efficient mechanism for isolation and disposal.

Tokenization of Side Pockets: GPs can isolate the non-performing assets into a side pocket and tokenize the shares of the side pocket, distributing them to existing LPs. This allows the NAV of the main fund to more clearly reflect the value of the quality assets.

Liquidity Option: LPs can choose to sell these side pocket tokens in the secondary market to achieve a quick exit, although they may have to accept a higher discount. This allows specialized distressed asset investors willing to take on high risk to enter.

On-Chain NPL Auctions: Conducting auctions of non-performing loan (NPL) portfolios through an RWA platform (e.g., a Dutch auction) can attract specialized investors globally, improving disposal efficiency and recovery rates. The transparency of on-chain auctions helps ensure fair pricing and reduces information asymmetry in the disposal process.

5.1.3. Structured Financing and Risk Tranching (Meeting Different Appetites)

GPs can use RWA to build on-chain structured products to meet the needs of investors with different risk appetites. Through customized risk exposure, LPs can choose the level of risk they wish to assume (senior, mezzanine, junior). This helps to attract a wider range of capital sources and optimize the fund's capital structure.

5.2. A Paradigm Shift in Capital Formation: From Discrete to Continuous

Traditional private credit funds adopt a discrete financing model: GPs raise a new vintage fund every few years, and LPs make a capital commitment at the fund's inception. This model has significant limitations: high pressure for capital deployment, severe liquidity mismatch, and long fundraising cycles. RWA tokenization makes a shift from a discrete to a continuous model of capital formation possible.

5.2.1. Tokenization and Feasibility of Evergreen Funds

Evergreen funds have no fixed term and allow investors to subscribe and redeem on a regular basis. This is difficult to achieve in the traditional private credit market because the underlying assets are illiquid. Tokenization can significantly improve the operational efficiency and feasibility of evergreen funds.

Real-Time Subscriptions and Redemptions: Investors can achieve real-time subscriptions and redemptions by buying or selling fund tokens on the secondary market, or through direct transactions with the fund (based on a dynamic NAV).

Dynamic Valuation: On-chain data supports dynamic NAV calculation, providing a fair price basis for subscriptions and redemptions and reducing arbitrage opportunities.

Liquidity Management Tools: GPs can manage the fund's liquidity through AMMs, DeFi lending markets, and cash reserves to cope with redemption pressure without being forced to sell underlying assets. Smart contracts can automatically execute liquidity management measures such as redemption gates or anti-dilution levies.

5.2.2. Continuous Fundraising and Dynamic Capital Deployment

GPs can continuously raise capital by issuing new tokens through an RWA platform, without having to wait for the next fund vintage. This allows GPs to seize market opportunities more flexibly and adjust their investment pace according to capital inflows. The inflow and deployment of capital can be more closely matched, reducing cash drag.

5.2.3. Dynamic Capital Structure Management and Optimization

GPs can use RWA tools to dynamically adjust the fund's capital structure to optimize the cost of capital and manage risk.

Flexible Application of Leverage: When market interest rates are low, leverage can be increased by issuing senior tokens or utilizing DeFi lending protocols; when market volatility is high, leverage can be reduced by repurchasing tokens or repaying debt.

Smart Contract Execution: Smart contracts can automatically execute these capital structure adjustment operations, improving efficiency and transparency.

5.3. On-Chain Securitization (CLO) as a Core Liability-Side Tool

On-chain securitization (CLO) is one of the most powerful applications of RWA on the liability side. It is not just a financing tool, but also a means of risk management and capital optimization.

5.3.1. Mechanism and Advantages of On-Chain CLOs

On-chain CLOs automate the process of asset pooling, tranching, and cash flow distribution through smart contracts. Their core advantages lie in cost efficiency, transparency, and speed.

Sources of Cost Efficiency: Significantly reduces the high legal fees, rating agency fees, trustee fees, and administrative costs involved in traditional securitization.

Impact of Transparency: Real-time transparency reduces information asymmetry for investors, allowing them to assess risk more accurately and thus lowering their demand for a risk premium. This helps to reduce the overall cost of financing.

Speed and Flexibility: The reduction in execution time allows GPs to respond more quickly to market changes and to recycle capital more frequently.

5.3.2. Strategic Application in Distressed Scenarios: Refinancing and Liquidity Creation

In distressed scenarios, on-chain CLOs can be used as a strategic tool to refinance a portion of the portfolio and create liquidity.

Attracting Risk-Averse Capital: By creating low-risk senior tranches with high credit enhancement (e.g., over-collateralization, reserve accounts), GPs can attract risk-averse investors seeking stable returns (including DeFi stablecoin holders).

Unlocking Liquidity: The proceeds from selling the senior and mezzanine tranches provide immediate liquidity that can be used to meet redemption pressure or make new investments.

Retaining Upside Potential: The GP retains the equity tranche, preserving the upside potential if the assets perform better than expected.

5.4. Intelligent and Dynamic Risk Management

RWA provides more advanced risk management tools, shifting risk management from a passive, post-hoc response to a proactive, dynamic process.

5.4.1. Real-Time Monitoring and Embedded Covenants

Smart contracts can monitor the performance of underlying assets in real time. If a preset risk threshold is triggered (such as a covenant breach), the smart contract can automatically take risk mitigation measures.

Embedded Covenants: Embedding the terms of loan covenants into smart contracts enables automatic enforcement, reducing default risk and enforcement costs.

5.4.2. Dynamic Collateral Management and Automated Liquidation

Smart contracts can dynamically manage the value of collateral and LTV ratios. By connecting to real-time price data for the collateral via oracles, automated mark-to-market and liquidation mechanisms can be implemented. This is particularly important in NAV loans and secured direct loans.

5.4.3. Integration of On-Chain Risk Hedging Tools

On-chain derivatives markets (CDS, interest rate swaps) provide efficient risk hedging tools for GPs and LPs. GPs can use these tools at the fund level to manage systematic and idiosyncratic risks. For example, they can hedge the credit risk of a specific borrower by purchasing an on-chain CDS, or hedge interest rate volatility risk through an interest rate swap.

5.5. The Evolution of the Competitive Landscape and the Future of GPs

The reshaping of the liability side by RWA will profoundly affect the competitive landscape of the private credit market.

New Entrants and Disruption: Technology-driven RWA platforms and DeFi protocols will become important market players, challenging the dominance of traditional GPs. Decentralized Credit Protocols may emerge, directly connecting borrowers and lenders.

Differentiation and Specialization of GPs: GPs who can effectively use RWA tools to optimize their capital structure, enhance liquidity, and manage risk will gain a significant competitive advantage. The core competitiveness of GPs will shift from pure capital-raising ability to technology integration capability, risk management capability, and asset management expertise.

Empowerment of LPs and Demand for Transparency: LPs will gain greater flexibility, control, and transparency. They will be able to more easily adjust their portfolios, manage liquidity, and more effectively monitor GPs. The increase in transparency will allow LPs to more clearly compare the performance of different GPs, leading to fee pressure and increased competition.

6. Potential Gains, Challenges, and Risk Considerations

6.1. Potential Gains of On-Chain Private Credit

In summary, combining private credit assets with blockchain technology is expected to bring numerous positive effects, from micro-level transaction efficiency improvements to macro-level market structure optimization. Below, we summarize the potential gains from the perspectives of liquidity, cost, transparency, and risk diversification:

Enhance Liquidity, Reduce Liquidity Premium: The most direct benefit of bringing private credit on-chain is the improvement of asset liquidity. As mentioned earlier, various tokenization mechanisms introduce trading and financing channels for previously long-term locked-up debt. According to classic financial theory, the expected return demanded by investors includes compensation for liquidity risk. When an asset cannot be readily liquidated, investors often demand a higher rate of return (i.e., a liquidity premium). Research shows that in the public stock market, about 1% to 2% of excess returns annually can be attributed to compensation for illiquidity; in more opaque markets like private debt, this premium could be even higher. If tokenization can substantially increase the trading activity of such assets, investors may be willing to participate at a lower yield, thereby reducing the financing costs for borrowers. Higher liquidity also allows portfolio managers to flexibly adjust their positions, reducing the opportunity cost of missing other opportunities due to being locked in.

Expand Investor Base, Increase Capital Supply: On-chain RWA breaks down geographical and channel barriers, allowing qualified investors worldwide the opportunity to participate in originally niche private credit transactions. This means that borrowers or fund managers are no longer solely reliant on a few traditional LPs for funding but can tap into a broader range of capital sources. For example, a direct loan project for a medium-sized enterprise might only receive financing interest from a few local credit funds offline, but by issuing tokens on-chain, family offices and wealth management institutions from around the world could potentially subscribe. The expansion of the available capital pool will increase capital allocation efficiency and may alleviate regional or structural financing shortages. At a macro level, RWA introduces a vast amount of traditional assets into the crypto space: the total size of global real-world assets is estimated to be over $400 trillion, more than a hundred times the current crypto asset market cap. Even if only a small fraction of this is brought on-chain, it will greatly propel the expansion of the DeFi ecosystem. For the traditional financial system, this means more diverse financing channels and more abundant capital liquidity.

Improve Efficiency, Reduce Operational and Intermediation Costs: The automation and programmability of the blockchain can significantly simplify the back-office processes of the private credit business. Traditional private loan origination and management involve cumbersome manual operations, legal document exchanges, and multiple layers of intermediaries (brokers, administrative agents, custodians, etc.). Through smart contracts, these steps can be automated and partially replaced. For example, a contract can automatically transfer funds to token holders in proportion after a borrower pays interest, eliminating the need for manual reconciliation and distribution. In addition, standardized token issuance templates can be reused, reducing case-by-case design costs. Higher operational efficiency will ultimately be reflected in lower management and transaction fees. Reduced fees benefit investors by increasing their net returns and also make this channel more attractive to borrowers.

Enhance Transparency and Real-Time Monitoring: Unlike traditional closed-end funds that require quarterly reports, on-chain platforms can provide near-real-time data sharing and oversight. The status of each loan (e.g., repayment, default) can be recorded on-chain, and investors can view the performance of the underlying asset pool at any time. Oracle networks can periodically upload borrowers' financial data, collateral values, fund NAVs, and other information on-chain. This transparency helps to reduce systemic risk in the entire system, as all parties can identify problems more promptly and take countermeasures. For example, if the default rate on real estate loans in a certain region rises, on-chain investors can immediately observe a drop in the price of related tokens or an oracle alert, allowing them to reassess their risk exposure.

Risk Diversification and Innovative Financial Instruments: The RWA system makes the reallocation and hedging of private credit risk more flexible. Through token tranching, investors with different risk profiles can each get what they need. Furthermore, standardized on-chain tokens provide a foundation for developing various derivative products. For example, investors could buy a decentralized credit derivative on a private loan pool to hedge the default risk within it, or participate in an RWA index token that includes loans from multiple regions and industries to gain more diversified exposure. As RWA develops, we expect more indices, options, swaps, and other products based on private credit assets to emerge, enriching the tools for risk management.

6.2. Challenges, Limitations, and Risk Considerations

Despite the promising outlook, RWA tokenization still needs to overcome a series of technical, operational, legal, and market challenges before it can achieve large-scale adoption.

6.2.1. Legal and Compliance Hurdles

Deploying RWA protocols in the highly regulated private credit industry will inevitably intersect with complex legal and regulatory frameworks. The clarity and stability of the regulatory environment are prerequisites for the large-scale application of RWA.

Applicability of Securities Law: A core regulatory issue is the legal classification of RWA tokens. In most jurisdictions, private credit tokens are likely to be classified as securities and will need to comply with the corresponding securities regulations. In the United States, the Howey test is the core standard for determining an investment contract (a type of security): an investment of money in a common enterprise with a reasonable expectation of profits to be derived from the efforts of others. Tokenized private credit assets typically meet this definition. We will analyze how tokenized credit instruments would almost certainly be classified as securities under frameworks like the Howey test in the US. This would require them to be issued within a compliant framework (e.g., Reg D/S) and traded on regulated platforms or in permissioned DeFi environments.

Legal Challenges of the "Protocolization" Strategy: The "protocolization" strategy aims to challenge traditional regulatory frameworks through decentralization. Its core argument is that if a protocol is sufficiently decentralized, the "efforts of others" prong of the Howey test may not be met. However, regulators often adopt a "substance over form" principle. If the economic substance of the tokenized assets is that of a security, they are likely to be subject to securities regulation, regardless of the technological wrapper.

Evolution of the Regulatory Environment: Current financial regulations are primarily designed for traditional securities and loans, and the legal status of on-chain tokens is still being explored. Many jurisdictions have not yet explicitly recognized the validity of on-chain debt transfers. However, the regulatory environment is changing. For example, in 2025, US securities regulators began to reassess the classification of some digital assets, taking a more open stance on NFTs backed by physical assets. If this policy shift continues, it will reduce the compliance costs of implementing RWA. However, until the regulations are clear, project teams will still need to operate on a "dual-track" basis, meeting both off-chain and on-chain regulatory requirements.

Cross-Border Enforcement and Jurisdictional Challenges: RWA tokenization does not automatically solve the challenges of cross-border enforcement. The persistence of off-chain legal reality is a major limitation for RWA applications. Different jurisdictions have different legal classifications and regulatory requirements for RWA tokens. In the event of a default, ensuring that an on-chain judgment is enforced off-chain is a huge challenge. The global nature of the blockchain conflicts with the national nature of securities regulation, which poses significant challenges for cross-border distribution. International regulatory coordination needs to be strengthened to establish uniform regulatory standards and legal frameworks.

Limitations of Smart Contracts vs. Legal Contracts: Smart contracts cannot replicate the flexibility and nuance of legal contracts. In complex restructuring scenarios, the rigidity of a smart contract could be a limitation. Hybrid models that combine the automation of smart contracts with off-chain legal procedures need to be designed. We will explore the potential conflicts between the automated, immutable logic of smart contracts and the discretionary, rehabilitative nature of bankruptcy law.

Enforceability in Bankruptcy Proceedings: We will draw on legal analysis of how crypto assets are treated in bankruptcy. For RWA, the key question is whether a bankruptcy court will respect the on-chain ownership records and the bankruptcy-remote status of the SPV.

6.2.2. Technical and Operational Risks

Technical Maturity and Infrastructure: High gas fees and limited transaction throughput (TPS) restrict the application of RWA. The development of Layer 2 scaling solutions and new-generation public chains is key. RWA protocols are currently fragmented across different blockchains, lacking uniform standards and interoperability. More advanced formal verification and security audit techniques need to be developed to ensure the security of smart contracts.

Smart Contract and Operational Risks: Blockchain smart contracts themselves are vulnerable to bugs and hacker attacks. If the contract managing cash flows is attacked, funds could be stolen. In addition, on-chain operations involve the coordination of multiple parties, such as correct oracle feeds and consistency between on-chain and off-chain data. If an oracle provides incorrect information, it could lead to erroneous contract execution.

Operational Challenges for Institutional Adoption: Institutional investors require secure and compliant custody solutions; the loss of private keys could lead to the permanent loss of assets. Data privacy needs to be protected while ensuring transparency, using privacy-enhancing technologies. Integrating the RWA protocol stack with the existing financial infrastructure and legacy systems of GPs and LPs is a complex operational challenge.

Complexity of Underlying Asset Conversion: Transforming real-world loan agreements into on-chain tokens is not a purely technical issue but also involves a significant re-engineering of business processes. For example, how do borrowers accept and cooperate with this form of financing? When legal action needs to be taken against a borrower, how do on-chain investors exercise their rights through an offline agent? Some RWA projects use a "two-layer structure": an off-chain traditional SPV holds the assets, while on-chain tokens represent the beneficial rights in the SPV. While this ensures a legal connection, it also sacrifices decentralization to some extent and increases operational costs.

6.2.3. Credit Risk and Investor Protection

RWA cannot magically eliminate the credit risk of the underlying assets. "A bad loan does not become good just because it is on-chain." For high-risk lending, expanding the investor base via the chain also means spreading the risk more widely, which raises new requirements for investor protection. Generally, investors in private credit funds are professional institutions or qualified investors who can assess risk themselves. But if on-chain platforms attract a wider crowd, how can it be ensured that they understand the potential losses? Therefore, project teams need to set up access mechanisms (such as KYC whitelists, minimum investment amounts, etc.) to screen for appropriate investors and clearly disclose the risks in their information disclosures.

6.2.4. Market Risk and the Illusion of Liquidity

Liquidity Risk: Although tokenization aims to increase liquidity, actual liquidity depends on the development of a robust secondary market. If trading volume remains low, the expected benefits of increased liquidity may not be realized (the illusion of liquidity). Even if technical and legal issues are resolved, the success of RWA also depends on the acceptance of market participants. If there are not enough investors and counterparties, an asset might remain "priced but not traded" even after being brought on-chain.

Valuation Risk: Dynamic valuation mechanisms rely on models and data inputs and may not always accurately reflect the true economic value of the underlying assets, especially in distressed scenarios.

6.2.5. Systemic Risk and Financial Stability

The integration of the private credit market with the DeFi ecosystem introduces new forms of systemic risk that require close attention from regulators.

Protocol Risk and Cascading Failures: A vulnerability in a smart contract could lead to huge financial losses. The interconnectedness of protocols (composability) could lead to cascading failures. For example, the failure of one RWA protocol could affect a lending protocol that uses its tokens as collateral.

Oracle Risk and Market Manipulation: The failure or manipulation of an oracle could lead to incorrect valuations, improper liquidations, and systemic instability. Oracles are the Achilles' heel of RWA systems.

Liquidity Spirals and Volatility Contagion: Under market stress, enhanced liquidity could lead to faster price declines and liquidity spirals. Automated liquidation mechanisms in DeFi lending protocols could exacerbate this situation. The volatility of the crypto market could be transmitted to traditional financial markets through RWA channels.

Accumulation of Leverage and Contagion Effects: The high leverage and complex interdependencies in the DeFi ecosystem could lead to excessive risk-taking and the accumulation of hidden leverage. When the opaque, traditionally siloed private credit market becomes interconnected with the highly reflexive, transparent DeFi ecosystem, new contagion pathways may emerge.

The Benefits of Transparency: On the other hand, the real-time transparency provided by the blockchain can give regulators an unprecedented view into the leverage and risk concentrations within the private credit market, potentially enabling intervention earlier than is possible today.

6.3. Future Research Directions

This emerging field of RWA tokenization offers a rich agenda for future research:

Empirical Study of Illiquidity Premium Compression: Empirical research is needed to quantify the impact of tokenization on the illiquidity premium (Π_L) of private credit assets.

Optimal AMM Design and Market Microstructure for Illiquid Assets: Research into the optimal design of Automated Market Makers (AMMs) for RWA, and how these designs affect price discovery and market stability.

Modeling the Impact of Transparency on Adverse Selection and Agency Costs: Theoretical and empirical research is needed to model the relationship between the enhanced transparency provided by RWA protocols and the reduction in the adverse selection discount (D_as) and agency costs (C_agency).

Legal and Regulatory Implications of the "Protocolization" Strategy: In-depth research into the legal basis, feasibility boundaries, and challenges to the existing securities law framework posed by the "protocolization" strategy.

Study of the Effectiveness of On-Chain Restructuring and Workout DAOs: In-depth case studies on the use of Workout DAOs in distressed debt restructuring to evaluate their effectiveness in managing complex legal procedures and coordinating creditor actions.

Systemic Risk Analysis and Macroprudential Policy: Research into the systemic risks introduced by the integration of the private credit market with the DeFi ecosystem, and the development of a corresponding macroprudential policy framework.

Research on Decentralized Valuation Models: Explore the use of machine learning, big data analytics, and decentralized incentive mechanisms to improve the accuracy and credibility of Level 3 asset valuations.