Private credit has been the fastest-growing segment of alternative asset management for the better part of a decade. The global private credit market has expanded from roughly $400 billion in assets under management in 2012 to over $1.7 trillion by the end of 2024, driven by banks’ post-2008 retreat from leveraged lending and middle-market corporate finance, the demand for floating-rate yield in an era of rate uncertainty, and the superior documentation and covenant quality that direct lenders can negotiate compared to broadly syndicated loan markets. When managers quote net returns of 10 to 15 percent on private credit strategies, institutional investors have learned to take those numbers seriously.
Tokenized private credit claims to deliver these same returns — sometimes higher — with improved transparency, faster settlement, and lower minimum investment barriers. The claims deserve examination rather than acceptance. Some are well-founded. Others reflect optimistic underwriting assumptions, structural leverage, or emerging market risk that is inadequately disclosed in headline yield figures.
Why Blockchain Changes Private Credit Economics
Before evaluating individual yield claims, it is worth understanding the structural argument for why tokenization should lower private credit costs and improve transparency — because the argument is real, not merely promotional.
Traditional private credit loan origination involves substantial friction: originator due diligence, legal documentation, syndication costs, participation agent fees, loan servicer fees, and back-office administration costs that collectively add 200 to 400 basis points to the total expense ratio of bringing a private credit instrument to market. For middle-market loans, these costs are manageable relative to the transaction size. For smaller consumer or small business credit — HELOCs, invoice finance, emerging market microloans — they are often prohibitive.
Blockchain-based private credit platforms reduce these costs through programmable loan origination and servicing (reducing manual processing), tokenized loan certificates that can be transferred and traded without legal assignment (reducing documentation costs), on-chain payment waterfalls that eliminate trust company fees, and transparent credit pool accounting that is auditable in real time rather than through quarterly fund reports. The cost reduction thesis is legitimate. The question is how much of the savings flows to investors versus platform operators, and whether improved transparency actually translates into better credit outcomes.
Figure: HELOC Origination at Scale
Figure Technologies is the most mature example of blockchain-based consumer credit at institutional scale. Founded by SoFi co-founder Mike Cagney, Figure uses the Provenance blockchain to originate, service, and securitize home equity lines of credit. By 2024, Figure had originated over $11 billion in HELOCs, making it one of the largest non-bank HELOC originators in the United States.
The investment proposition for Figure HELOC pools is straightforward: senior secured home equity credit, first or second lien, to prime borrowers with average FICO scores of 720+, at interest rates of approximately 8 to 10 percent, with underlying collateral providing significant equity cushion in most markets. The blockchain rail (Provenance) handles loan registration, transfer of ownership, and payment waterfall distribution, reducing the administrative cost structure relative to conventional HELOC securitization.
Observed default rates on Figure’s HELOC pools have been below 1 percent on an annualized basis — a credit performance that compares favorably with conventional prime HELOC programs. The yield to investors — after credit losses, servicing fees, and platform costs — has been approximately 7 to 9 percent, placing Figure in the lower end of the private credit yield range but with a risk profile that most institutional credit analysts would classify as investment-grade equivalent.
Figure’s structural innovation is meaningful: on-chain loan registration creates a verifiable, immutable record of origination that eliminates the documentation fraud risks that surfaced in conventional mortgage securitization — the “robo-signing” scandals and chain of title failures that complicated mortgage servicing in 2010 and 2011. Whether this transparency improvement justifies a meaningful yield premium over conventional HELOC ABS is debatable, but the operational improvement is real.
Maple Finance: Institutional Credit, Post-FTX Resilience
Maple Finance launched in 2021 as an institutional undercollateralized lending protocol — a technically ambitious product that represented the first serious attempt to build traditional credit underwriting on blockchain rails. Borrowers — primarily crypto-native institutions including trading firms, market makers, and exchanges — received USDC loans collateralized by reputation, ongoing financial reporting obligations, and Maple’s on-chain credit scoring system rather than hard asset collateral.
The FTX collapse in November 2022 was a severe test of Maple’s credit underwriting. Several Maple lending pools had extended credit to Orthogonal Trading, a firm with undisclosed exposure to FTX, which subsequently defaulted on approximately $36 million in loans. The default — and Maple’s handling of it, including the public process for pool recovery — exposed both the risks of undercollateralized institutional DeFi lending and the limitations of on-chain credit scoring in detecting concentrated counterparty risk.
Maple’s response was a significant restructuring: the platform shifted toward overcollateralized lending (requiring borrowers to post crypto collateral) for retail-accessible pools, while maintaining undercollateralized institutional credit pools for sophisticated investors who could conduct their own due diligence. By 2024, Maple had rebuilt its AUM to over $200 million and launched Maple Direct — a product targeting institutional investors with a $1 million minimum that resembles a conventional private credit fund with blockchain settlement infrastructure rather than a DeFi protocol.
Current yields on Maple institutional pools range from approximately 10 to 12 percent, reflecting the platform’s positioning in senior secured crypto-institutional credit after its de-risking from the undercollateralized model. The post-FTX Maple is a meaningfully different product from the 2021-era protocol — more conservative in credit underwriting, more institutional in investor targeting, and more transparent about the limitations of on-chain credit assessment.
Centrifuge: Trade Finance and Real Asset Credit
Centrifuge occupies a distinct position in the tokenized private credit landscape: rather than originating credit directly, Centrifuge is a protocol infrastructure layer that allows traditional originators — invoice finance companies, trade receivables platforms, small business lenders, real estate bridge lenders — to tokenize their loan pools and access DeFi liquidity from institutional and semi-institutional investors.
The Centrifuge model creates token pools (Tinlake pools) with a two-tranche structure: DROP tokens (senior, fixed yield, prioritized in payment waterfall) and TIN tokens (junior, residual yield, absorbing first losses). This structure mirrors conventional securitization waterfall economics — similar to a CLO’s AAA and subordinated tranches — but with on-chain payment automation and public pool accounting.
Pool yields on Centrifuge vary substantially by underlying asset type:
| Pool Type | Originator Type | Target Yield (Senior) | Target Yield (Junior) | Observed Default |
|---|---|---|---|---|
| Trade Finance | Invoice Factoring | 4-6% | 8-12% | <0.5% (mature pools) |
| Real Estate Bridge | Private Lender | 5-8% | 10-15% | 1-3% |
| SME Loans | Online Lender | 6-8% | 12-18% | 2-5% |
| Emerging Market | Microfinance | 8-10% | 15-22% | 3-8% |
The wide range reflects genuine credit risk differentiation rather than arbitrary variation. Senior trade finance exposure to factored receivables from creditworthy corporate debtors is fundamentally different from junior exposure to emerging market SME loans, regardless of the shared blockchain infrastructure.
Centrifuge’s most important institutional development has been its integration with MakerDAO, which in 2022 and 2023 deployed over $200 million in DAI liquidity into Centrifuge pools as part of MakerDAO’s Real World Asset strategy. This institutional DeFi capital — from a decentralized stablecoin protocol purchasing senior credit exposure on a blockchain platform — represents a genuinely novel capital formation mechanism with no conventional analog.
Goldfinch: Emerging Market Credit and the High-Yield Reality
Goldfinch Finance takes the Centrifuge model into higher-risk territory: emerging market credit, primarily in Southeast Asia, sub-Saharan Africa, and Latin America. Goldfinch pools target yields of 10 to 15 percent to liquidity providers — the headline numbers that attract investor attention — but these yields are earned against credit risk that is materially higher than the Figure HELOC or Centrifuge trade finance products.
Goldfinch’s underwriting relies on a “Auditor” network — vetted institutional investors who perform due diligence on borrowers and stake their own capital as a first-loss junior tranche before senior liquidity providers commit capital. The model creates alignment of interest between underwriters and investors, but it does not eliminate the fundamental credit risk of emerging market lending to borrowers who often lack conventional credit histories, operate in jurisdictions with limited creditor remedies, and face currency risk that can materially impair repayment capacity in USD-denominated loan structures.
Observed default rates in Goldfinch’s public pools have been higher than in conventional emerging market credit funds: several pools have experienced borrower distress or payment delays, with annualized loss rates in the 3 to 8 percent range for specific pools. Net yields to investors — after credit losses — have been substantially below the headline 10 to 15 percent in stressed pools.
The honest yield-to-risk comparison for Goldfinch places it alongside sub-investment grade emerging market bonds or mezzanine credit rather than senior secured institutional lending. The risk-adjusted return profile — 7 to 10 percent net of losses in realistic scenarios — is competitive with conventional high-yield or emerging market credit, but the blockchain wrapper does not justify a premium valuation above conventional comparables with longer track records and more robust creditor rights.
Yield-to-Risk Analysis: The Framework Institutional Investors Should Apply
Institutional credit investors evaluate private credit on a risk-adjusted basis using frameworks that tokenized private credit platforms have only partially adopted. The relevant metrics:
Gross yield vs. net yield after losses: Headline yields of 10 to 15 percent in tokenized private credit represent gross lending rates before credit losses, platform fees, and servicing costs. Net investor yields, accounting for observed loss rates, are typically 200 to 500 basis points lower than headline rates. For high-default pools, the spread can be much larger.
Collateralization and seniority: Figure HELOCs are secured by real property with first or second lien — recoveries in default can be substantial even in moderately distressed scenarios. Maple undercollateralized institutional loans have limited recovery in default, as the FTX episode demonstrated. Goldfinch emerging market loans have limited practical recovery mechanisms given creditor rights limitations in many jurisdictions.
Concentration and correlation: Many tokenized private credit pools are concentrated in narrow borrower categories — crypto-institutional for Maple, fintech SME lenders for some Centrifuge pools, a single geography for some Goldfinch pools. Concentration risk in a private credit portfolio is the primary driver of catastrophic loss scenarios, not the average default rate.
Liquidity premium: Tokenized private credit instruments generally carry a liquidity premium over comparable public credit instruments. Whether that premium is fairly reflected in headline yields — or whether it is partially absorbed by platform economics — varies by platform and requires careful analysis of fee disclosures.
Operational and smart contract risk: Unlike conventional private credit, tokenized platforms add smart contract risk, oracle failure risk, and governance attack risk to the conventional credit risk stack. These risks are not quantifiable through conventional credit metrics and require separate evaluation.
BDC Comparison: Transparency as the Differentiator
Business Development Companies — SEC-registered closed-end investment companies that provide direct lending to U.S. middle-market businesses — are the conventional retail-accessible private credit vehicle. BDCs like Ares Capital (ARCC), Blue Owl Capital (OBDC), and Golub Capital BDC have delivered net investment income yields of 9 to 12 percent over 2023 and 2024, with portfolio transparency provided through quarterly SEC filings that disclose individual loan positions, valuations, and credit quality metrics.
The transparency comparison between BDCs and tokenized private credit platforms is instructive. The BDC disclosure regime — quarterly 10-Qs with position-level disclosure — provides more consistent, regulated transparency than most tokenized platforms, which offer varying levels of pool-level reporting with limited regulatory mandate. The blockchain-based audit trail that tokenization proponents cite as a transparency advantage is real for payment verification and ownership records, but it does not substitute for the comprehensive portfolio disclosure that regulated fund structures provide.
Where tokenized private credit genuinely exceeds BDC transparency is in real-time pool accounting: investors in Centrifuge or Goldfinch pools can observe outstanding loan balances, payment history, and pool NAV calculations on-chain in near real-time, rather than waiting for quarterly filing cycles. For credit quality monitoring and early warning of portfolio deterioration, this real-time visibility is a meaningful improvement over conventional BDC reporting.
The yield premium of tokenized emerging market credit over BDC senior secured lending — approximately 300 to 600 basis points — reflects the genuine risk difference rather than inefficiency in pricing. Investors attracted by headline yields in tokenized private credit who benchmark against BDC performance without adjusting for credit quality are making a category error that the yield spread does not adequately communicate.
This analysis is for informational purposes and does not constitute investment advice. Private credit investments carry risks including loss of principal. Past performance of credit pools does not predict future returns.