BIS Report Compliance Watch: The Real Risks of Stablecoins Are Not Just 'De-pegging'

链捕手Publicado a 2026-07-03Actualizado a 2026-07-03

Resumen

BIS Report Compliance Observations: The real risks of stablecoins go beyond "depegging" The BIS report "Anchoring trust in money: innovation beyond stablecoins" argues that while stablecoins and tokenization offer efficiency gains, their primary risk lies in fitting into an identifiable, monitorable, accountable, and regulatable financial system. Money's trust stems not just from technology but from institutional arrangements: a common unit of account, guaranteed redemption at par, liquidity support, regulatory frameworks, and financial integrity requirements. Stablecoins, operating on permissionless blockchains with pseudo-anonymity and non-custodial wallets, create systemic compliance gaps: unclear customer identity, incomplete fund origins, unexplained transaction purposes, fragmented cross-chain paths, and ambiguous liability. On-chain transparency does not equal compliance transparency. Public addresses don't reveal identity or intent. While blockchain analytics aid law enforcement, they cannot replace routine, large-scale AML/CFT controls. Effective compliance requires a closed-loop process encompassing customer onboarding, transaction monitoring, investigation, reporting, and audit. Stablecoin risks are not confined to the blockchain; they re-enter the traditional financial system via on/off-ramps, exchanges, and payment institutions. This forces banks to monitor client accounts for activity linked to virtual assets. The future direction is not to prohibit innovat...

Author: compliance newbie

Recently, the Bank for International Settlements (BIS) released Chapter 3 of its Annual Economic Report:

Anchoring trust in money: innovation beyond stablecoins

This can be understood as:Anchoring Trust in Money: Innovation Paths Beyond Stablecoins. The report was published on June 23, 2026.

From a macro-financial perspective, this report discusses the future monetary system, tokenization, and stablecoins.

However, from a compliance perspective, what it truly reminds us of is:

The issue with stablecoins is not just whether their price will de-peg, but whether they can be integrated into a financial system that is identifiable, monitorable, accountable, and regulatable.

I. BIS is not opposing technology; it is asking: Where does trust come from?

BIS acknowledges that stablecoins and tokenization do bring some efficiency improvements, such as faster payments, programmable payments, atomic settlement, and reduced reconciliation friction. The report also points out that DLT and tokenization can place assets and funds on programmable ledgers, supporting automation and 24/7 operations.

However, BIS's core argument is:

Money is not a purely technological product.

The reason money can be money is not just because it can be transferred, but because there is an institutional framework behind it:

A common unit of account,

Certainty of redemption at par value,

Liquidity support,

A regulatory and legal framework,

And financial integrity requirements.

This is crucial for compliance professionals.

Because any new payment instrument, once it enters large-scale usage scenarios, will ultimately face the same question:

Who identifies the customer? Who monitors the transaction? Who handles exceptions? Who bears the responsibility?

II. The Compliance Risks of Stablecoins: Not Just Anonymity On-chain

When many people talk about stablecoin risks, their first reaction is "on-chain anonymity" or "wallet untraceability."

But the BIS report articulates it more systematically.

In the traditional financial system, banks and regulated institutions undertake responsibilities such as customer identification, transaction monitoring, suspicious activity reporting, and, where necessary, stopping or recalling payments. In contrast, stablecoins primarily circulate on public, permissionless blockchains. Pseudonymity, non-custodial wallets, cross-chain bridges, and mixing tools can all weaken KYC and AML/CFT controls.

This means stablecoins pose not a single-point risk, but a combination of risks:

Who the customer is may not be clear;

The origin of funds may not be fully known;

The purpose of the transaction may not be explainable;

After cross-chain transfers, the path may become fragmented;

When problems arise, the liable entity may also be unclear.

Therefore, for compliance departments, they should not just ask:

"Is this address risky?"

They should ask more importantly:

Why does this customer want to use stablecoins?

How do funds move between stablecoins and fiat accounts?

Who are the counterparties?

What is the relationship between wallets, trading platforms, and payment institutions?

Is the fund flow consistent with the customer's background and business model?

III. On-chain Transparency Does Not Equal Compliance Transparency

Stablecoin proponents often say: on-chain transactions are public, so they are more transparent.

This statement is only half true.

On-chain data is indeed visible, but "address visibility" does not equal "identity visibility."

"Transaction path visibility" also does not equal "clear transaction purpose."

BIS also mentions that blockchain analytics companies are already supporting law enforcement, and some stablecoin issuers have frozen specific on-chain addresses, indicating that on-chain technology can indeed aid risk identification.

But BIS also emphasizes that these measures cannot replace daily, large-scale AML/CFT controls.

True compliance is not about buying a tool; it's about establishing a closed loop:

Can virtual asset exposure be identified before customer onboarding?

Can on-chain and off-chain fund flows be monitored when transactions occur?

After a risk hit, can a manual review and explanation be conducted?

After forming a suspicious lead, can it be documented, escalated, and reported?

After adjusting models and rules, can they be audited and reviewed?

Technology is just one link in the compliance chain, not compliance itself.

IV. Stablecoins Bring "On-chain Risk" Back to Traditional Finance

The BIS report mentions that as of the end of May 2026, the stablecoin market capitalization was approximately $3.2 trillion; estimated annual transaction volume in 2025 was around $28 trillion. However, after excluding transfers between wallets of the same entity, the actual economic significance would be much lower.

These numbers indicate one thing:

Stablecoins are already large enough that they cannot be ignored by compliance departments;

But they are not yet mature enough to completely replace the existing financial system.

More importantly, stablecoin risk does not remain on-chain.

It re-enters traditional financial institutions through on/off-ramps, trading platforms, payment institutions, trade scenarios, cross-border settlements, and customer accounts.

For example:

Customers frequently use bank accounts to fund virtual asset platforms;

Corporate clients claim to engage in cross-border trade, but funds ultimately flow through stablecoin channels;

Personal customer accounts receive large sums from strangers and then purchase virtual assets in bulk;

Customers explain the activity as "investment," "settlement," or "currency exchange," but the transaction behavior does not match the source of income.

These scenarios are not simply "virtual asset issues"; they are fundamentally customer due diligence and transaction monitoring problems that traditional financial institutions must confront.

V. Future Regulatory Direction: Not Prohibiting Innovation, but "Embedding the Rules"

BIS proposes an important direction:

Future tokenized finance should not detach from the existing trust framework. Instead, tokenization technology should be introduced into the two-tier monetary system based on central bank money and regulated institutions. From a compliance perspective, this essentially boils down to four words: rules first. A more viable future digital financial infrastructure should embed in the transaction flow: customer identity verification,

Transaction pre-screening,

Risk rule assessment,

Auditable data trails,

Privacy and data sovereignty protection, and cross-institution, cross-jurisdiction collaboration mechanisms. BIS also explicitly states that platforms with permissioned mechanisms, if they can embed AML/CFT pre-screening, list screening, and auditable data trails into the transaction flow, are more likely to maintain financial integrity in large-scale scenarios. This is also where compliance technology will truly add value in the future: not remediating after the fact, but embedding risk controls into the process before payment and settlement occur.

Compliance Newbie Observation

The inspiration this BIS report offers to compliance professionals is not "whether stablecoins are good or bad," but rather:

In the future, all new financial instruments, if they wish to become mainstream payment and settlement tools, must answer compliance questions.

Who will identify the customer?

Who will monitor the transaction?

Who will handle exceptions?

Who will bear the responsibility?

Who will ensure cross-border rule consistency?

If there are no answers to these questions, even the most advanced technology merely shifts risk to places harder to regulate.

Therefore, from a compliance standpoint, stablecoins are not a purely "crypto industry topic."

They affect bank account monitoring, payment institution risk control, cross-border fund flows, virtual asset access, customer risk rating, and financial crime prevention.

The truly valuable direction for the future is not using technology to bypass compliance,

But embedding compliance capabilities into the technological infrastructure.

Compliance is not the opposite of innovation.

Compliance is the infrastructure that determines how far financial innovation can go.

Criptos en tendencia

Preguntas relacionadas

QAccording to the BIS report's analysis, what is the core problem with stablecoins beyond the risk of 'de-pegging'?

AThe core problem is whether stablecoins can be integrated into a financial system that is identifiable, monitorable, accountable, and regulatable. It's about the absence of the institutional framework—including common unit of account, certainty of value, liquidity support, regulation, legal backing, and financial integrity requirements—that underpins trust in traditional money.

QWhat specific set of combined risks does the BIS report highlight regarding stablecoins and compliance?

AThe report highlights a combination of risks: the client's identity may be unclear; the origin of funds may be incomplete; the purpose of transactions may be unexplainable; transaction paths can be fragmented across bridges; and the liable entity in case of problems may be ambiguous.

QWhy does the article argue that 'on-chain transparency' does not equal 'compliance transparency'?

ABecause while on-chain transaction data is publicly visible, an 'address being visible' does not equate to 'identity being visible', and a 'transaction path being visible' does not mean the 'purpose of the transaction is clear'. True compliance requires a closed-loop process involving customer identification, transaction monitoring, manual review, reporting, and auditability, not just raw data availability.

QHow can risks associated with stablecoins impact the traditional financial system, as discussed in the article?

AStablecoin risks can re-enter the traditional financial system through on/off-ramps (fiat conversions), exchanges, payment institutions, trade settlements, cross-border payments, and customer bank accounts. This forces traditional institutions to deal with due diligence and transaction monitoring issues related to clients involved in virtual asset activities.

QWhat future regulatory direction does the BIS report suggest, according to the article's interpretation?

AThe suggested direction is not to prohibit innovation but to 'embed rules' into the infrastructure. Future tokenized finance should integrate with the existing trust framework (central bank money and regulated institutions) and embed compliance measures—like customer identification, pre-transaction screening, risk rule application, auditable data trails, and cross-jurisdictional mechanisms—directly into the transaction process from the start.

Lecturas Relacionadas

BIS Report Compliance Observations: The True Risks of Stablecoins Go Beyond 'De-pegging'

The BIS report, "Anchoring trust in money: innovation beyond stablecoins," highlights that the primary risks of stablecoins extend beyond potential de-pegging. It argues that the core challenge is whether stablecoins can be integrated into a financial system that is identifiable, monitorable, accountable, and regulatable. While acknowledging efficiency gains like faster payments and programmability, BIS emphasizes that money requires an institutional framework—including legal certainty, liquidity support, and financial integrity controls—which many stablecoins currently lack. The report details compliance risks, noting that while blockchain transactions are transparent, address visibility does not equate to identity or purpose clarity. This creates a systemic risk as pseudonymity, non-custodial wallets, and cross-chain bridges can undermine AML/CFT controls. Furthermore, these risks can spill over into the traditional financial system through on- and off-ramps. The future direction, per BIS, is not to prohibit innovation but to embed regulatory rules—such as identity verification and transaction screening—directly into the technological infrastructure of tokenized finance. The key takeaway for compliance is that any new financial instrument must clearly address questions of customer identification, transaction monitoring, accountability, and cross-border rule consistency to be viable as a mainstream payment tool.

marsbitHace 51 min(s)

BIS Report Compliance Observations: The True Risks of Stablecoins Go Beyond 'De-pegging'

marsbitHace 51 min(s)

When US Giants Collectively "Defect" to Chinese AI Models

When Silicon Valley Giants Turn to Chinese AI Models to Cut Costs A surprising trend is emerging: major U.S. tech companies are significantly reducing AI costs by switching to Chinese models. Coinbase, the largest U.S. cryptocurrency exchange, reportedly halved its AI spending after migrating to China's GLM-5.2 and Kimi 2.7 models, despite increasing usage. They achieved this through a sophisticated three-part strategy: implementing an automatic routing system to select the most cost-effective model per task, boosting cache hit rates from 5% to 60% to reuse computations, and employing "context engineering" to provide AI with more precise, less cluttered information. They are not alone. AI startup Lindy switched from Claude to DeepSeek, saving millions, while Snowflake's tests found GLM-5.2 solved 66% of coding tasks compared to Claude Opus's 67%—but at a fraction of the cost (output pricing is 5-7 times lower). While the top Western models may offer slightly better stability, the massive price differential is leading many businesses to reconsider their value proposition. This shift signals a deeper change in the AI industry, moving beyond pure performance benchmarks to a fierce cost competition. As pressure mounts, even OpenAI and Anthropic have begun slashing prices. For users, this means more choices, lower costs, and a crucial lesson: using multiple models based on task complexity, optimizing with caching, and keeping contexts lean are now key to leveraging AI efficiently and affordably.

marsbitHace 58 min(s)

When US Giants Collectively "Defect" to Chinese AI Models

marsbitHace 58 min(s)

When American Giants 'Defect' to Chinese AI Models

Summary: The trend of major U.S. technology firms adopting more cost-effective Chinese AI models is gaining momentum. A prime example is Coinbase, the largest U.S. cryptocurrency exchange, which reportedly halved its AI expenditure by switching to Chinese models GLM-5.2 and Kimi 2.7, while its usage volume increased. This was achieved through a sophisticated cost-saving system featuring intelligent model routing (selecting the most suitable model per task), dramatically improving cache hit rates from 5% to 60%, and implementing "Context Engineering" to streamline prompts. This shift is not isolated. Other companies like the AI startup Lindy and data cloud firm Snowflake are making similar moves, drawn by the significant price disparity. For instance, GLM-5.2 costs $1.40/$4.40 per million tokens (input/output), compared to $5/$25 for Claude Opus 4.7. While top Western models may offer slightly higher stability or speed in complex tasks, the performance gap is narrowing, making the price difference harder to justify for many enterprise use cases. The implications are significant for both businesses and individual users. It highlights the importance of a multi-model strategy based on task requirements, the value of caching and reusing outputs, and the effectiveness of providing concise context. Ultimately, this migration signals a potential reshaping of the AI industry's pricing model, moving competition from pure performance benchmarks to practical cost-effectiveness, with increased choice and downward price pressure benefiting end-users.

链捕手Hace 1 hora(s)

When American Giants 'Defect' to Chinese AI Models

链捕手Hace 1 hora(s)

Trading

Spot

Artículos destacados

Qué es $BANK

Banco AI: Un Paso Revolucionario en el Futuro de la Banca Introducción En una era marcada por avances rápidos en tecnología, Banco AI se sitúa en la intersección de la inteligencia artificial (IA) y los servicios bancarios. Este proyecto innovador busca redefinir el panorama financiero, mejorando la eficiencia operativa, las medidas de seguridad y las experiencias del cliente a través del poder de la IA. Al embarcarnos en esta exploración de Banco AI, profundizaremos en lo que implica el proyecto, sus dinámicas operativas, su contexto histórico y hitos significativos. ¿Qué es Banco AI? En su esencia, Banco AI representa una iniciativa transformadora destinada a integrar la inteligencia artificial en varias operaciones bancarias. Este proyecto aprovecha las capacidades de la IA para automatizar procesos, mejorar los protocolos de gestión de riesgos y mejorar la interacción con los clientes a través de servicios personalizados. Los objetivos principales de Banco AI incluyen: Automatización de Funciones Bancarias: Al aprovechar las tecnologías de IA, Banco AI tiene como objetivo automatizar tareas rutinarias, reduciendo la carga sobre los recursos humanos y mejorando la eficiencia. Mejora en la Gestión de Riesgos: El proyecto utiliza algoritmos de IA para predecir e identificar riesgos, fortaleciendo así las medidas de seguridad contra fraudes y otras amenazas. Personalización de Servicios Bancarios: Banco AI se centra en ofrecer productos y servicios financieros a medida al analizar datos y comportamientos de los clientes. Mejoramiento de la Experiencia del Cliente: La implementación de soluciones impulsadas por IA, como chatbots y asistentes virtuales, tiene como objetivo proporcionar a los usuarios interacciones más humanas, revolucionando la forma en que los clientes se relacionan con los bancos. Con estos objetivos, Banco AI se posiciona como un jugador crucial para hacer que la banca sea más eficiente, segura y centrada en el usuario. ¿Quién es el Creador de Banco AI? Los detalles sobre el creador de Banco AI siguen siendo desconocidos. Como tal, no se ha identificado a ninguna persona u organización específica en la información disponible. El anonimato que rodea el inicio del proyecto plantea preguntas, pero no resta valor a su ambiciosa visión y objetivos. ¿Quiénes Son los Inversores de Banco AI? Al igual que con el creador del proyecto, no se ha divulgado información específica sobre los inversores u organizaciones que apoyan a Banco AI. Sin esta información, es un desafío delinear el respaldo financiero y el apoyo institucional que podrían estar impulsando el proyecto hacia adelante. No obstante, la importancia de contar con una sólida base de inversión es fundamental para sostener el desarrollo en un campo tan innovador. ¿Cómo Funciona Banco AI? Banco AI opera en múltiples frentes innovadores, centrándose en factores únicos que lo diferencian de los marcos bancarios tradicionales. A continuación, se presentan las características operativas clave: Automatización: Al aplicar algoritmos de aprendizaje automático, Banco AI automatiza varios procesos manuales dentro de los bancos. Esto resulta en la reducción de costos operativos y permite que los trabajadores humanos redirijan sus esfuerzos hacia actividades más estratégicas. Gestión Avanzada de Riesgos: La integración de la IA en las prácticas de gestión de riesgos equipa a los bancos con herramientas para predecir con precisión amenazas potenciales como el fraude, garantizando que la información y los activos de los clientes permanezcan seguros. Recomendaciones Financieras Personalizadas: A través del aprendizaje continuo a partir de las interacciones con los clientes, los sistemas de IA desarrollan una comprensión matizada de las necesidades del usuario, lo que les permite ofrecer consejos adaptados sobre decisiones financieras. Interacciones Mejoradas con los Clientes: Al utilizar chatbots y asistentes virtuales impulsados por IA, Banco AI permite una experiencia más atractiva para el cliente, permitiendo a los usuarios resolver sus consultas rápidamente, reduciendo así los tiempos de espera y mejorando los niveles de satisfacción. En conjunto, estas características operativas posicionan a Banco AI como un pionero en el sector bancario, estableciendo nuevos parámetros para la entrega de servicios y la excelencia operativa. Línea de Tiempo de Banco AI Entender la trayectoria de Banco AI requiere mirar su contexto histórico. A continuación, se presenta una línea de tiempo que destaca hitos y desarrollos importantes: Inicios de 2010: La conceptualización de la integración de la IA en los servicios bancarios comenzó a ganar atención a medida que las instituciones bancarias reconocieron los posibles beneficios. 2018: Se produjo un aumento notable en la implementación de tecnologías de IA cuando los bancos comenzaron a utilizar herramientas de IA como chatbots para el servicio al cliente básico y sistemas de gestión de riesgos para mejorar la seguridad. 2023: La sofisticación de la IA continuó avanzando, con la introducción de IA generativa para tareas más complejas como el procesamiento de documentos y análisis de inversiones en tiempo real. Este año marcó un salto significativo en las capacidades que la tecnología de IA otorgó a los bancos. 2024-Estatus Actual: A partir de este año, Banco AI se encuentra en una trayectoria ascendente, con investigaciones y desarrollos en curso que pronto mejorarán las capacidades en las operaciones bancarias. La continua exploración de las aplicaciones de IA sugiere emocionantes desarrollos aún por venir. Puntos Clave Sobre Banco AI Integración de la IA en la Banca: Banco AI se centra en adoptar inteligencia artificial para optimizar los procesos bancarios y mejorar la experiencia del usuario. Enfoque en Automatización y Gestión de Riesgos: El proyecto enfatiza fuertemente estas áreas, con el objetivo de desplazar la carga de tareas rutinarias mientras mejora los marcos de seguridad a través de análisis predictivos. Soluciones Bancarias Personalizadas: Al aprovechar los datos de los clientes, Banco AI permite servicios bancarios adaptados a las necesidades individuales de los usuarios. Compromiso con el Desarrollo: Banco AI se mantiene comprometido con esfuerzos de investigación y desarrollo continuos, asegurando su adaptabilidad y relevancia continua a medida que la tecnología sigue evolucionando. Conclusión En resumen, Banco AI ejemplifica un paso crucial hacia adelante en la industria bancaria, aprovechando la inteligencia artificial para redefinir los paradigmas operativos, mejorar la seguridad y promover la satisfacción del cliente. A pesar de las lagunas en la información sobre el creador y los inversores, los objetivos claros y los mecanismos funcionales de Banco AI proporcionan una sólida base para su evolución continua. A medida que la tecnología de IA sigue avanzando y fusionándose con el sector bancario, Banco AI está bien posicionado para impactar significativamente el futuro de los servicios financieros, mejorando la forma en que entendemos e interactuamos con la banca.

168 Vistas totalesPublicado en 2024.04.06Actualizado en 2024.12.03

Qué es $BANK

Cómo comprar BANK

¡Bienvenido a HTX.com! Hemos hecho que comprar Lorenzo Protocol (BANK) sea simple y conveniente. Sigue nuestra guía paso a paso para iniciar tu viaje de criptos.Paso 1: crea tu cuenta HTXUtiliza tu correo electrónico o número de teléfono para registrarte y obtener una cuenta gratuita en HTX. Experimenta un proceso de registro sin complicaciones y desbloquea todas las funciones.Obtener mi cuentaPaso 2: ve a Comprar cripto y elige tu método de pagoTarjeta de crédito/débito: usa tu Visa o Mastercard para comprar Lorenzo Protocol (BANK) al instante.Saldo: utiliza fondos del saldo de tu cuenta HTX para tradear sin problemas.Terceros: hemos agregado métodos de pago populares como Google Pay y Apple Pay para mejorar la comodidad.P2P: tradear directamente con otros usuarios en HTX.Over-the-Counter (OTC): ofrecemos servicios personalizados y tipos de cambio competitivos para los traders.Paso 3: guarda tu Lorenzo Protocol (BANK)Después de comprar tu Lorenzo Protocol (BANK), guárdalo en tu cuenta HTX. Alternativamente, puedes enviarlo a otro lugar mediante transferencia blockchain o utilizarlo para tradear otras criptomonedas.Paso 4: tradear Lorenzo Protocol (BANK)Tradear fácilmente con Lorenzo Protocol (BANK) en HTX's mercado spot. Simplemente accede a tu cuenta, selecciona tu par de trading, ejecuta tus trades y monitorea en tiempo real. Ofrecemos una experiencia fácil de usar tanto para principiantes como para traders experimentados.

799 Vistas totalesPublicado en 2025.05.09Actualizado en 2026.06.02

Cómo comprar BANK

Discusiones

Bienvenido a la comunidad de HTX. Aquí puedes mantenerte informado sobre los últimos desarrollos de la plataforma y acceder a análisis profesionales del mercado. A continuación se presentan las opiniones de los usuarios sobre el precio de BANK (BANK).

活动图片