The privacy fix Wall Street has been waiting for

Banks do not publish their risk positions, and asset managers do not hand over customer cards. Yet both want a programmable settlement and a verifiable execution without exposing what they are settling for or for whom.

This tension has kept institutional capital on the sidelines of public chains, waiting for privacy technology to rise to compliance requirements.

If banks can’t enter the public blockchain markets without confidentiality, the entire $3.4T crypto market remains effectively off limits.

Chainlink is betting that it can close that gap first with “Confidential Compute,” a privacy layer in its new Chainlink Runtime Environment that processes sensitive data off-chain, returns attested results on-chain, and never reveals input or logic to the public ledger.

The service was launched as part of CRE on the 4th of Novemberwith early access planned for 2026 and a wider launch later that year.

Initial workflows run in cloud-hosted trusted execution environments, which are isolated hardware environments that run code without exposing data to the host system.

A published roadmap supports zero-knowledge proofs, multiparty computation, and fully homomorphic cryptography as these technologies mature.

Chainlink also disclosed two subsystems built for the institutional use case: a distributed key generation system for session secrets and a “Vault DON” for decentralized storage of long-term confidential data.

They appear that tokenized assets, cross-chain delivery versus payment, and compliance checks occur without leaking positions, counterparties, or API credentials to the public mempool.

Bank quality data meets verifiable execution

The short-term value is simple. Institutions can use proprietary data or external feeds on the chain without publishing the information first.

Examples of Chainlink span real-world private tokens, distribution of confidential data to paying subscribers, delivery versus payment on public and permissioned chains, and KYC or eligibility checks that return a binary yes-or-no attribute on the chain, maintaining an audit trail for regulators.

Each workflow in the CRE issues a cryptographic attestation of the logic that ran and when, but not the underlying data or business rules. This structure is important for two reasons.

First, it separates the verification layer from the data layer, so auditors or counterparties can confirm the integrity of the execution without seeing sensitive inputs.

Second, it works across public chains, permissioned networks, and Web2 APIs from a single orchestration point.

For a treasury desk that manages collateral flows or a tokenization platform that distributes compliance assets, this means integration instead of custom bridges for each environment.

TEE and cryptographic privacy

Today, privacy technology is divided into three design philosophies, each with distinct tradeoffs in terms of performance, trust assumptions, and maturity.

Privacy rollups, such as Aztec, use zero-knowledge proofs to maintain the privacy of transactions and state at the cryptographic level.

Everything remains encrypted, but the proof costs are high, and the composability of the chains requires the use of bridges. Confidential EVM layers, such as Fhenix, Inco, and Zama’s fhEVM, which use fully homomorphic cryptography, allow users to compute directly on encrypted data.

However, FHE remains the most expensive option, and the tool is still in the maturation process.

Confidential TEE-based EVMs, such as Oasis Sapphire, provide native execution speed by isolating code in hardware enclaves. However, they inherit the underlying chip threat model, as side-channel attacks and physical interpose exploits periodically compromise enclave guarantees.

Chainlink’s Confidential Compute starts in the TEE field because institutions need performance today.

Microsoft defines TEE as hardware that executes code and data in isolation, providing strong confidentiality and near-native speed without cryptographic overhead.

The adaptation of the product market is a treasury system that cannot wait minutes for a test to generate when it needs to transform the guarantee in seconds.

However, Chain link is aware that the TEE trust model concerns some users, which is why CRE wraps executive in decentralized attestation and secret sharing in its oracle network, and why the roadmap explicitly includes the ZK, MPC and FHE backends.

The game is that the TEEs are enough for the first institutional workflows if the verification layers and multi-cloud diversity are added. This cryptographic privacy can be built in later as computational costs decrease.

This bet has technical substance. Recent research has shown new attacks on Intel SGX enclaves, including physical interposing techniques that Intel itself notes fall outside the original SGX threat model.

These vulnerabilities do not invalidate TEEs for all use cases, but they do mean that single-enclave designs carry residual risk.

CRE’s oracle network’s decentralized attestation and distributed key management are designed to contain that risk: no TEE holds complete secrecy, and cryptographic logs create an audit trail that survives enclave compromise.

Whether it is sufficient for regulated finance depends on whether institutions trust the verification layer more than they distrust the enclave.

Where privacy meets liquidity

The architectural choice of privacy as an off-chain service, rather than a separate chain, creates a distinct composability profile compared to privacy rollups.

If private RWA tokens​​​​​​ and confidential data feeds are routed through CRE, they always settle publicly ethereumBase, or permissioned chains, where liquidity already exists.

This means that privacy workflows can leverage the same collateral pools and DeFi primitives as open applications, only with sensitive fields protected.

Privacy rollups offer stronger cryptographic guarantees, but they silo liquidity in their own execution environment and require bridges to interact with the wider ecosystem.

For an institution weighing whether to tokenize on a privacy layer-2 (L2) or on Ethereum with Compute Confidential, the question becomes: do users value cryptographic privacy over interoperability, or speed and connectivity over provable cryptography?

Chainlink also bundles Confidential Compute with its Automated Compliance Engine, which enforces KYC, jurisdictional checks and position limits in the same workflow.

This is the institutional package: private execution, verifiable compliance, and cross-chain settlement from a service level.

If the first pilots rely on that bundle, the treasury sweeps with the application of the integrated policy, the credit tokenized with the identity of the hidden participants, it signals that Chainlink wins in the integration of the work flow rather than only the privacy technology.

Clock and the competition

Timeline matters. Confidential Compute is expected to ship to the first users in 2026, not today. Aztec’s privacy rollup hit the public test network in May, while Aleo launched with private apps by default already live.

FHE-based L2s are racing toward usability with active SDKs and testnet implementations. If institutions decide they need cryptographic privacy guarantees and can tolerate slower performance or isolated liquidity, these alternatives will be ready for production when CRE early access begins.

If institutions prioritize speed, auditability and the ability to integrate with existing Web2 and multi-chain infrastructure, Chainlink’s TEE-first approach can capture deals on the cheap as ZK and FHE mature.

The deeper question is whether privacy concerns consolidate around a single technical approach or fragment by use case.

Corporate treasury workflows that require sub-second execution and auditor-friendly attestations can opt for TEE-based systems.

DeFi applications that prioritize censorship resistance and cryptographic guarantees over speed can migrate to privacy rollups. High-value, low-frequency transactions, such as syndicated loans and private equity settlements, could justify the computational cost of FHE for end-to-end encryption.

If this fragmentation takes place, Chainlink’s “multiple backends” path becomes critical: CRE wins by being the orchestration layer that works with any privacy technology, not locking users into just one.

Confidential Compute is not a fad, since privacy is the missing piece for institutional activity on the chain, and every major chain or middleware provider builds a version of it.

However, “the last mile” implies that this is the final unlocking, and this is only true if institutions accept TEE trust models with added layers of verification, or if the migration of Chainlink’s cryptographic backend occurs before competitors deliver faster and cheaper ZK or FHE.

The answer depends on who moves first: banks that need privacy to transact, or cryptographers that want to eliminate hardware trust. Chainlink is betting that it can serve the former while the latter takes over.