The crossroads of privacy coins: from "Unconditional Privacy" to the paradigm shift of "Verifiable Privacy"

Privacy is becoming a necessary condition for blockchain to connect with mainstream finance—but this form of privacy is undergoing a fundamental transformation. From complete anonymity to selective disclosure, and now to the emergence of privacy computing infrastructure, the privacy track has reached a crossroads of differentiation.

Monero’s “Deadlock”: Why Fully Private Privacy Doesn’t Work in Finance

Monero represents the purest technical ideal of privacy coins. Through mechanisms like ring signatures, stealth addresses, and confidential transactions, it hides the sender, receiver, and transfer amount at the protocol level, making it impossible for external observers to trace fund flows. For individual users, this offers a perfect privacy experience—default protection without the need for choice.

But it is precisely this “perfection” that has become a deadlock for adoption by financial institutions.

The bottom line of modern financial systems is “auditability when necessary.” Banks need to retain transaction records to meet risk management, anti-money laundering, and tax requirements. Regulators need to trace the source of funds to prevent illegal capital inflows. Fully anonymous systems “permanently lock” this information at the protocol level—even if institutions are willing to comply voluntarily, the structure makes compliance impossible.

This is not simply a technical versus regulatory conflict but a fundamental opposition of system goals. KYC risk assessments cannot be performed on fully anonymous chains—institutions cannot verify the identity of counterparties or the compliance attributes of fund sources, making necessary AML verification impossible.

What is the result? Exchanges delist, payment providers refuse access, and mainstream capital cannot enter. The demand has not disappeared but has migrated to high-friction intermediaries like instant exchange services, where users pay higher spreads and fees, while bearing risks of fund freezing and counterparty risk. Intermediaries quickly sell off collected Monero fees, creating persistent structural selling pressure that long-term distorts price discovery.

Viewed this way, fully anonymous privacy is not a technical failure but is locked into non-institutionalized use cases. As finance enters an era of compliance, the focus is no longer on “whether everything can be hidden” but on “whether everything can be proven when needed.”

Zcash’s Trial and Error: Why “Optional Privacy” Is Still Not Enough

Zcash improved upon Monero’s model by introducing a coexistence design of transparent addresses and shielded addresses. Users can choose privacy or transparency, and can also disclose transaction details to specific parties via viewing keys. Conceptually, this is a milestone shift: privacy and compliance are no longer mutually exclusive.

From a proof-of-concept perspective, Zcash demonstrates that cryptographic tools can reserve technical interfaces for regulatory disclosure. Regulators care not about “full transparency” but about “non-auditable anonymity.” Zcash’s design directly responds to this core concern.

However, when Zcash moves from a personal transfer tool to an institutional transaction infrastructure, bottlenecks emerge.

Institutional transactions involve multiple layers of participants: counterparties need to confirm performance conditions, clearinghouses need to know amounts and timing, auditors need to verify complete records, and regulators are concerned with fund sources and KYC risk assessments. These entities have asymmetric and partially overlapping information needs.

Zcash’s binary structure cannot finely meet these differentiated needs. A transaction is either fully public or entirely hidden; institutions cannot selectively disclose “necessary information.” This means that in complex financial workflows, Zcash either exposes too much sensitive business information or cannot achieve basic compliance. Privacy capabilities thus struggle to embed into real institutional workflows.

Canton and Integration with Real-World Finance: Engineering and Process-Oriented Privacy

Contrasting with Zcash’s conceptual approach, Canton Network starts from the business processes and institutional constraints of financial entities. Its core is not “hiding transactions” but “fine-grained management of information access rights.”

Using the smart contract language Daml, Canton breaks down a transaction into multiple logical components. Different participants can only see data relevant to their permissions, with other information isolated at the protocol level. Privacy is not an after-the-fact attribute but embedded into the contract structure and permission system, becoming part of the compliant process.

This design is fundamentally transformative. Canton actively embraces the real financial system, engineering privacy and institutionalizing it—not as an adversary to transparency but as a controllable, verifiable infrastructure within the financial framework. KYC risk assessments are no longer opposed to privacy but can be performed without exposing raw identity data.

Privacy 2.0: From “What to Hide” to “What Can Be Done in a Hidden State”

As privacy is redefined as a necessary condition for institutional on-chain activity, the privacy track itself evolves.

Privacy 1.0 focused on “what to hide and how”—obscuring transaction paths, amounts, and identity links. But institutions need more than private transfers—they require privacy-preserving transaction matching, risk calculation, clearing and settlement, strategy execution, and data analysis. If privacy only covers payment layers and cannot extend to business logic layers, its value to institutions is limited.

This is the core shift of Privacy 2.0—focusing on “what can still be done in a hidden state.”

Aztec Network exemplifies this shift. It embeds privacy as a programmable attribute within smart contract execution environments. Using zero-knowledge proof-based Rollup architecture, developers can finely define which states are private and which are public, enabling “partial privacy, partial transparency” hybrid logic. Privacy is no longer limited to simple transfers but can cover lending, trading, vault management, DAO governance, and other complex financial structures.

Deeper evolution in Privacy 2.0 points toward “privacy computing networks.” Projects like Nillion, Arcium are building off-chain privacy collaboration layers. Through multi-party secure computation (MPC), fully homomorphic encryption (FHE), and zero-knowledge proofs (ZKP), data can be stored, invoked, and computed in encrypted form throughout the entire process. Participants do not need access to raw data but can jointly perform model inference, risk assessment, or strategy execution.

This elevates privacy from a “transaction layer attribute” to a “computing layer capability.” The market potential extends to AI inference, dark pools for institutions, RWA data disclosure, and enterprise data collaboration.

Unlike traditional privacy coins, these projects derive value not from “privacy premiums” but from the irreplaceability of their functions. When certain computations are impossible in open environments or pose severe business risks in plaintext, privacy computing becomes a matter of “it cannot run without it,” rather than “whether it is needed.”

Another feature of Privacy 2.0 is “invisible privacy.” Privacy no longer exists as an explicit form but is decomposed into reusable modules embedded in wallets, account abstractions, Layer2, cross-chain bridges, and enterprise systems. End users may not realize they are “using privacy,” but their asset balances, transaction strategies, and identity links are protected by default.

Meanwhile, regulatory focus shifts as well. In Privacy 1.0, the concern was “whether there is anonymity”; in Privacy 2.0, it becomes “whether compliance can be verified without exposing raw data.” Zero-knowledge proofs and rule-based compliance thus become key interfaces for privacy computing projects and regulatory frameworks. Privacy is no longer seen as a risk source but as a technical means to achieve compliance.

The True Turning Point in the Privacy Track

The core dividing line in the privacy track is no longer “whether privacy exists” but “how to use privacy under compliance.”

Fully anonymous models have irreplaceable security value at the personal level, but their non-auditable nature makes them unsuitable for institutional-level financial activities. Selective privacy, with its design of disclosability and authorization, provides a technical interface between privacy and regulation. Privacy 2.0 further upgrades privacy from an asset attribute to an infrastructure capability for computation and collaboration.

In the future, privacy will no longer exist as an explicit function but will be embedded as a default assumption in various financial and data workflows. Truly valuable long-term privacy projects may not be the most “secret,” but they will be the most “usable, verifiable, and compliant.”

This marks a key milestone in the transition of the privacy track from experimental to mature stage.