How to Bring Private Credit Onchain

Private credit is showing clear signs of stress.

Blackstone’s $82B flagship private credit fund, BCRED, faced $3.7B in redemption requests in Q1 2026 (roughly 8 percent of the fund's net asset value), forcing Blackstone to inject $400M of its own capital to stabilize it. BlackRock’s HLEND recently gated redemptions because it could not honor investor withdrawal requests. Blue Owl Capital Corporation II similarly halted redemptions in February following a surge in withdrawals. Meanwhile, many Business Development Companies are trading at roughly 20 percent discounts to NAV (while offering yields of 10 to 11 percent), and default rates across parts of the private credit market have risen as high as 9 percent.

This is not a crisis yet. Private credit is a $1.8 to $2 trillion market, which is small relative to the $130 trillion global bond market or the roughly $180 trillion banking system. The industry could likely absorb a single fund default (or a handful) without risking major contagion. But the confidence dynamics are ugly, and the underlying structural problems are real: traditional private lending is bloated by intermediaries, misaligned incentives, and inefficient cost structures.

A growing chorus of voices in the crypto and DeFi community has proposed a solution: bring private credit onchain and automate it with smart contracts. The appeal of this model is obvious.

Encoding credit agreements such as redemption windows, withdrawal limits, collateral ratios, and distribution policies in immutable contracts makes those rules unalterable. Fund managers cannot arbitrarily change the terms of a credit agreement after capital has been committed, like BCRED and HLEND did when they tightened redemptions in response to withdrawal pressure.

Automating key parts of private lending, including debt issuance, repayment, redemptions, loan health monitoring, and liquidations, enables those processes to execute deterministically according to business logic programmed into smart contracts. Intermediaries with questionable incentives and unaccountable actors can be eliminated from the critical path, promising a system that is more transparent, less discretionary, and less reliant on trust.

These advantages are real and reflect the ability of smart contracts to deterministically enforce clearly defined rules without relying on trusted intermediaries. But while smart contract enforcement can solve the rules problem, it cannot immediately solve the truth problem. Onchain private credit is hard to implement in reality precisely because determining the truth about financial instruments is both notoriously difficult and absolutely essential.

A refresher on private credit markets

To understand the truth problem, it helps to revisit traditional private credit markets and see how they work in practice. We'll consider a mid-market company that carries first-lien senior secured debt from a direct lender as an example.

The borrower-lender relationship is governed by the credit agreement, which includes financial covenants requiring the borrower to maintain specific financial thresholds. One common financial covenant is the interest coverage ratio, which requires that EBITDA be at least twice the borrowing company’s interest expense. If the ratio falls below that threshold, lenders have the right to declare a default and enforce their security interest, which may include liquidating pledged collateral or negotiating a restructuring.

At first glance, this covenant seems straightforward to encode in a smart contract. A contract's logic could simply state that “if the interest coverage ratio falls below 2.0x, trigger a default.” The difficulty arises when we ask a simple question: how does the smart contract determine a borrower’s interest coverage ratio?

In traditional private credit markets, that determination is made through a covenant testing process that relies heavily on borrower reporting and third-party evaluation. Borrowers submit monthly financial reports to the servicer. The servicer calculates the interest coverage ratio using EBITDA from income statements and interest expense from debt schedules and compares it against the covenant threshold. If the interest coverage ratio falls below the threshold, the servicer is supposed to notify lenders and trigger a default determination.

But anyone familiar with private credit knows it does not always work that way in reality due to misaligned incentives. The servicer often maintains an ongoing relationship with the borrower, and that relationship can be affected if the servicer notifies lenders of a borrower's default, triggering a costly workout or, in the worst case, liquidation. This creates a conflict of interest in which the party responsible for determining whether covenants have been breached has an incentive to avoid declaring a breach.

Tactics employed by servicers skirting default declarations are well documented: generous interpretations of covenant definitions, deliberate miscalculations of EBITDA, delayed reporting of borrower performance, or undisclosed renegotiations of covenant thresholds between reporting periods. If we analyzed every credit crisis from the last few decades, it is more than likely that one or more of these tactics were employed by an unscrupulous servicer to disastrous consequences.

This is the truth problem laid out. The rules may be clear, but enforcement of those rules is guided by information provided by the servicer. If the servicer provides inaccurate, false, or incomplete information, lenders and other participants in the capital stack cannot determine the truth and may be unable to make correct decisions concerning when and how to enforce covenants defined in the credit agreement.

The verification gap in onchain private credit

The truth problem leads to what we call the “verification gap” in onchain private credit. Smart contracts can perfectly enforce the rules of a credit agreement without a human in the loop, but they still rely on external inputs to determine the truth about the credit instrument before deciding how and when the rules should be enforced. If those inputs cannot be independently verified, smart contract enforcement may be unreliable and fail to guarantee correct outcomes.

In existing crypto lending models, a borrower pledges digital assets as collateral and receives an overcollateralized loan in return. This model works because the borrower's financial data is publicly available, and both collateral and loaned assets are issued and held onchain. It is trivial to assess the health of open loan positions and trigger liquidation if a loan is insufficiently collateralized or the borrower reneges on the agreed repayment timeline, and the system works well without a centralized operator.

Private credit markets are different. The borrower's financial data exists offchain, stored in bank accounts, ERP systems, Stripe dashboards, and the borrower's own internal records. Collateral assets and underlying credit instruments exist offchain as well. Those things may be tokenized and tracked onchain, but the representation is not perfectly aligned with the underlying financial reality. The data used to build and update tokenized representations is also unverifiable from the blockchain’s perspective.

Tokenizing a private loan is straightforward. Verifying the underlying financial reality behind that tokenized representation is far more difficult. The gap between “we tokenized a private credit facility” and “you can verify it” is where the verification gap emerges.

Traditional private credit markets are flawed, in part, because covenant testing and default determination rely on human intermediaries who are subject to misaligned incentives and conflicts of interest. However, deploying private credit markets onchain and automating covenant testing with smart contracts will not make them flawless.

A smart contract can eliminate reliance on a designated intermediary for covenant testing, but it still needs to verify the underlying credit instrument to determine whether a borrower is in breach of loan covenants. That determination requires access to borrower data. Since borrower data is not stored on the blockchain, someone needs to retrieve it and feed it to the smart contract onchain. This is where the problem with naive implementations of onchain private credit becomes obvious.

If the party providing this data is honest and sends accurate borrower data, the smart contract will accurately assess covenant compliance and reliably determine whether a borrower is complying with financial covenants. If the party is dishonest and provides incorrect borrower data, the smart contract cannot reliably determine the borrower's compliance with covenant thresholds and may fail to identify defaults.

Moreover, if the party that provides the data used by the smart contract to enforce rules related to default determination also has an incentive to prevent or delay a determination of default, we have merely recreated the same conflict of interest found in traditional private credit markets, but with a blockchain wrapper. They may selectively disclose information, delay reporting, or even refuse to provide the necessary data at all. Enforcing the rules is easy, but determining the truth is hard.

Building infrastructure for onchain private credit

Some financial instruments are relatively straightforward to bring onchain. Treasury bills provide a good example. The underlying instruments have transparent pricing, standardized structures, and no covenant complexity. Tokenized Treasury bills are largely a solved problem.

Private credit is fundamentally different. The underlying instrument is a bespoke loan tied to a specific borrower, with covenants, collateral, and performance metrics that shift with every payment cycle. Verifying the financial reality behind tokenized representations of private credit is far more difficult.

Closing that verification gap and solving the truth problem requires infrastructure capable of ingesting real-world data, evaluating it independently, and producing verifiable results about bespoke financial instruments. The following limitations must be addressed if we are to build infrastructure capable of supporting onchain private credit markets.

1. Native access to real-world data

The covenant tests introduced earlier failed because a human intermediary controlled what data got reported and when. The fix is to remove the intermediary from the data pipeline entirely, not simply move to trusting a new intermediary. 

Smart contracts need the ability to pull borrower data directly from source systems such as ERP platforms, bank APIs, and accounting software, rather than waiting for a party with conflicting incentives to push that data onchain. The push model is exactly where the conflict of interest lives; native ingestion from verified sources fundamentally changes the trust model.

2. Confidential and verifiable computation

Even if borrower data arrives through a trusted pipeline, the covenant evaluation itself has to occur somewhere that no single party controls. The servicer cannot run it. The fund manager cannot run it. The borrower certainly cannot run it.

But the evaluation also cannot be fully public. A mid-market company’s EBITDA and debt schedule are not the kind of information it can broadcast to every participant in the capital market. At the same time, the computation must be verifiable so that participants across the capital stack, including junior and senior lenders and equity investors, can confirm that it ran correctly.

This means covenant evaluations must occur within an environment that preserves confidentiality while still allowing independent verification. Lenders should be able to verify the correctness of an evaluation and have confidence in the result, and borrowers should be able to preserve their privacy while responding to data requests during covenant evaluations. 

3. Bespoke covenant encoding

Covenant definitions must be encoded with sufficient precision to reflect the complexity of real credit agreements. Private credit contracts include numerous carve-outs, baskets, and cross-referenced definitions that cannot be captured by simplistic templates. Template-based approaches often break down in real-world scenarios. Any infrastructure serious about onchain private credit must be able to encode this complexity faithfully rather than merely approximating it.

Taken together, these requirements reveal a missing layer in the infrastructure stack for onchain credit markets: the determination layer.

Crypto needs a determination layer 

The determination layer sits between the raw data produced by real-world systems and the smart contracts that enforce lending rules. It is where messy real-world borrower data is transformed into verifiable truth about specific financial instruments, expressed in a form that smart contracts can reliably act on. Without a determination layer, onchain private credit will remain a tokenized wrapper around the same opaque system that we know today.

Crypto does not need more tokenization platforms for onchain private credit to work. It needs a determination layer. A functional determination layer must address key infrastructure challenges, particularly native data access and confidential computation, and support expressive logic to enable complex covenants. It must also close the verification gap and ensure smart contract enforcement produces valid outcomes rather than deterministically enforcing the wrong result due to unverified inputs.

Rialo's infrastructure is optimized for exactly these goals. It enables something that did not exist before: verifiable determinations that a smart contract can act on, that any counterparty can verify, and that do not require trusting any single party to produce them accurately. This is possible due to the combination of Rialo’s confidential computing environment (REX)¹ and its ability to connect smart contracts to real-world APIs².

Building this infrastructure is difficult, but solving it is essential if private credit is ever going to move onchain in a meaningful way. Smart contract enforcement is valuable, but it is only the second piece of the puzzle: the first and more fundamental requirement is the ability to determine the truth about bespoke financial instruments with strong guarantees of reliability and confidentiality.

At Rialo, we believe blockchains can make credit markets more efficient, composable, secure, transparent, and accessible. We will continue building toward that goal and share the lessons we learn along the way.