The Institutional Dilemma of Privacy Coins: From KYC Risk Assessment to the Shift Toward Compliant Infrastructure

When financial institutions face privacy coins, their most immediate concern is not “lack of technical understanding,” but “inability to perform KYC risk assessments.” This is not merely a regulatory compliance issue; it strikes at the fundamental logic of institutional risk control systems: the inability to verify counterparties, trace fund sources, or assess anti-money laundering risks. This systemic disconnection is profoundly reshaping the future of the privacy sector. From the ideal of complete anonymity, through pragmatic compromises of selective privacy, to infrastructure upgrades enabled by privacy-preserving computation, privacy is undergoing a fundamental shift from adversarial features to controllable, collaborative tools.

1. The Technical Advantages of Complete Anonymity and the Incompatibility with KYC Risk Assessment

Monero exemplifies the most “pure” technical approach among privacy coins—completely rejecting any form of observability. Using ring signatures, stealth addresses, and confidential transactions, Monero encrypts sender, receiver, and transaction amount simultaneously. For individual users, this means near-cash-level absolute anonymity. Transactions occur, but on-chain no one can determine who transacted with whom, or how much.

This design is highly effective against on-chain analysis. The greatest risk of transparent blockchains is “combinatorial monitoring”—public information from single transactions being pieced together over time. Through address clustering, behavioral pattern recognition, and off-chain data cross-validation, these can be linked to real identities, forming a “financial profile” that can be priced and exploited. Monero raises the cost of such monitoring, making large-scale, low-cost attribution analysis unreliable. In other words, Monero not only serves personal privacy but also responds to a deeper reality: in the digital age, privacy itself is a crucial component of security.

However, the fatal weakness of fully anonymous design is its permanent, structural non-audibility. For financial institutions, compliance with KYC/AML, counterparty risk assessment, source of funds verification, fraud prevention, and tax/accounting audits are not just regulatory requirements—they are fundamental risk management actions. Institutions need to be able to prove the legality and source of funds to regulators, auditors, and counterparties when necessary.

Monero’s architecture makes such proof impossible at the protocol level forever. Even if institutions are willing to comply voluntarily, they are technically incapable of doing so. When regulators demand source-of-funds explanations, they cannot obtain them; when KYC risk assessments are needed, counterparty information remains a black box. This is not “regulators not understanding technology,” but a fundamental conflict between two systems—modern finance’s bottom line is “auditability when necessary,” while the bottom line of complete anonymity is “never auditable at any time.”

This conflict manifests externally as systemic exclusion from financial infrastructure: mainstream exchanges delist Monero, payment and custody providers do not support it, and institutional funds cannot enter compliantly. While it may appear as “market rejection,” it is actually an inevitable result of institutional and channel structures. When compliant channels are closed, demand does not disappear—it shifts to high-friction gray intermediaries. Instant exchange services handle large volumes, with users paying higher spreads for accessibility, risking fund freezes, and facing opaque information. More critically, the business models of such intermediaries introduce ongoing structural pressure—when service providers quickly convert fees into stablecoins for cash-out, the market experiences passive sell-offs unrelated to genuine buy-side demand, long-term suppressing price discovery.

This creates a paradox: the more compliance channels exclude privacy coins, the more demand concentrates in high-friction intermediaries; the stronger these intermediaries become, the more distorted prices are; and the more distorted prices are, the harder it becomes for mainstream funds to evaluate and enter. This is not a matter of “market not accepting privacy,” but a systemic and channel-driven dilemma.

2. The Rise of Selective Privacy: From Binary Choices to Differentiated Authorization

Against the backdrop of complete anonymity hitting institutional and regulatory ceilings, new technological approaches are emerging. Selective privacy becomes a new compromise between privacy and compliance. Its core conceptual shift is fundamental: privacy is no longer viewed solely as a tool to oppose regulation but is redefined as a foundational infrastructure capability that can be absorbed by the system.

Zcash is a pioneering example of this shift. Its design features both transparent and shielded addresses, allowing users to choose freely between openness and privacy. When using shielded addresses, transaction information is encrypted and stored on-chain; when compliance or audit needs arise, users can disclose full transaction details to specific third parties via “view keys.” This represents a milestone in philosophy: privacy does not have to come at the expense of verifiability; KYC risk assessment and privacy protection can coexist within an authorization framework.

From an institutional evolution perspective, Zcash’s value lies in its “concept validation”—demonstrating that privacy can be optional, and cryptographic tools can provide interfaces for compliant disclosures. Major jurisdictions worldwide have not rejected privacy per se but have rejected “unverifiable anonymity.” Zcash’s architecture directly addresses this core concern.

However, when selective privacy upgrades from a “personal tool” to an “institutional transaction infrastructure,” structural limitations of Zcash become apparent. Its privacy model remains fundamentally a binary choice at the transaction level—either fully transparent or entirely hidden. For real-world finance, such coarse control is insufficient.

Institutional transactions involve multiple layers of participants: counterparties need to confirm performance conditions; clearing and settlement entities require knowledge of amounts and timing; auditors need complete records; regulators may only care about source and compliance attributes. These entities have asymmetric and non-overlapping information needs. Zcash cannot componentize transaction information or support differentiated authorization; institutions are forced to either fully disclose, risking business secrets, or fail to meet basic compliance. Its privacy capabilities thus struggle to embed into real institutional workflows.

In contrast, Canton Network exemplifies a different paradigm. It does not start from “anonymous assets” but from the process and regulatory constraints of financial institutions. Its core idea is not “hiding transactions” but “managing information access rights.” Using Daml smart contracts, Canton splits transactions into multiple logical components, with each participant only able to see data relevant to their permissions; other information is isolated at the protocol layer.

This change is fundamental. Privacy is no longer an after-the-fact attribute but embedded into contract structures and permission systems, becoming part of compliance workflows. Each participant can perform necessary KYC risk assessments, but the information they receive is entirely different—protecting commercial secrets while satisfying regulatory requirements.

The divergence between Zcash and Canton reveals the bifurcation in the privacy sector. The former remains rooted in cryptography-native approaches, attempting to balance personal privacy and compliance; the latter actively embraces the realities of traditional finance, engineering privacy into workflows and institutionalized processes. As institutional capital’s share in crypto markets continues to grow, the main battleground for privacy shifts accordingly. The future competition will not be about who hides most thoroughly, but who can be compliant, auditable, and scalable without unnecessary information exposure. Under this standard, selective privacy becomes an essential pathway to mainstream finance.

3. Privacy 2.0 and Privacy Computing: From Transaction Obfuscation to Infrastructure Upgrades

Once privacy is redefined as an essential condition for institutional on-chain activity, the technological boundaries of the privacy sector expand. Privacy is no longer just about “whether transactions are visible,” but evolves toward the deeper question: Can systems perform computation, collaboration, and decision-making without exposing data itself?

This marks the transition from “Privacy Asset/Transfer” 1.0 to Privacy Computing 2.0. The 1.0 era focused on “what to hide” and “how to hide”—transaction paths, amounts, identity links; the 2.0 era asks: What can be done in a hidden state?

This distinction is crucial. Institutions need not only privacy-preserving transfers but also the ability to perform transaction matching, risk calculations, clearing, settlement, strategy execution, and data analysis under privacy constraints. If privacy only covers payment layers, leaving business logic exposed, its value to institutions is limited.

Aztec Network exemplifies this shift. It does not treat privacy as a tool to oppose transparency but embeds it as a programmable property within smart contract execution environments. Using zero-knowledge proof-based rollups, Aztec allows developers to define which states are private and which are public at the contract level, enabling “partial privacy, partial transparency” logic. Privacy is no longer limited to simple transfers but can encompass lending, trading, vault management, DAO governance, and other complex structures.

But Privacy 2.0 does not stop at native blockchain solutions. As AI, data-intensive finance, and cross-institutional collaboration emerge, pure on-chain zero-knowledge proofs become insufficient for all scenarios. The privacy sector begins evolving toward broader “privacy compute networks.”

Projects like Nillion and Arcium are born in this context. Their common feature is not to replace blockchains but to serve as privacy collaboration layers between blockchain and real-world applications. Using 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 process. Participants do not need access to raw data but can jointly perform model inference, risk assessment, or strategy execution.

Privacy upgrades from “asset attribute” to “computational and collaborative infrastructure” expand the potential market to AI inference, dark pools, RWA data disclosure, and enterprise data sharing. In these scenarios, privacy computing is not optional but essential—without it, the system cannot operate. This gives the privacy sector its first real “bottom-up moat”: once data and workflows are embedded in a privacy compute network, migration costs become significantly higher than ordinary DeFi protocols.

Another key feature of Privacy 2.0 is the invisibility of privacy. Privacy no longer exists as an explicit “privacy coin” or “privacy protocol” but is decomposed into reusable modules embedded into wallets, account abstractions, Layer2 solutions, cross-chain bridges, and enterprise systems. End users may not even realize they are “using privacy,” but their asset balances, transaction strategies, and identity links are protected by default. This “invisible privacy” aligns better with large-scale adoption.

Regulatory focus shifts accordingly. The core issue in 1.0 was “does it have anonymity”; in 2.0, it becomes “can it verify compliance without exposing raw data.” Zero-knowledge proofs, verifiable computation, and rule-based compliance thus become key interfaces for privacy computing projects and regulatory environments. Privacy is no longer seen as a risk source but as a technical means to achieve compliance.

4. The New Era of Privacy and Compliance: Verifiable, Auditable, Scalable

The core dividing line in the privacy sector is no longer “is there privacy,” but “how to use privacy within compliance constraints.”

Complete anonymity models have irreplaceable security value at the personal level, but their systemic non-audibility makes them unsuitable for institutional finance. Monero demonstrated the feasibility of strong anonymity at the engineering level but also clearly proved that—once finance enters an era of compliance—the focus shifts from “can I hide everything” to “can I prove everything when needed.”

Selective privacy, with its design of disclosure and authorization, provides a feasible technical interface between privacy and regulation. Institutions no longer need to choose passively between “full transparency” and “full concealment” but can finely control who sees what information based on specific scenarios. This capability fundamentally improves KYC risk assessment—different compliance entities can evaluate risks across different dimensions, protecting trade secrets while satisfying regulatory requirements.

The rise of Privacy 2.0 further elevates privacy from an asset attribute to a foundational infrastructure for computation and collaboration. Privacy computing enables institutions to jointly analyze data, infer models, and make decisions without ever exposing raw data. This is revolutionary for anti-fraud, risk assessment, investment strategies, and other financial operations—institutions can gain sufficient insights for proper KYC and risk management while completely avoiding direct contact with counterparties’ or partners’ raw data.

In the future, privacy will no longer be an explicit feature but embedded as a default assumption across financial and data workflows. Truly valuable privacy projects are not necessarily the most “secret,” but the most “usable, verifiable, and compliant.” This marks a key milestone in the evolution of the privacy sector—from experimental edge cases to an essential infrastructure of the modern financial system.