Quantum computing is often framed as a distant storm on the horizon, and not yet relevant to today’s cryptographic systems. In 2026, that framing is dangerously misguided. The Ethereum Foundation’s recent decision to launch a dedicated Post-Quantum (PQ) cryptography team, backed by $2 million in funding, is a watershed moment for the industry. The world’s most influential smart contract ecosystem is no longer treating quantum risk as theoretical; it is acting on the correct assumption that cryptographic disruption could arrive far sooner than expected. 

The quantum threat is already a present market risk, not a future technical problem, and crypto’s failure to treat it as such will define the next systemic crisis. Some readers may find this view overly alarmist or argue that highlighting quantum risk could undermine confidence in digital assets. Others may object that this perspective challenges long-held assumptions about Bitcoin’s resilience and the pace of technological change. However, these contentions radically underestimate how close we are to a cryptographic collapse.

From theory to strategic priority

It’s important to note that quantum computing is no longer confined to academic research. Nation-states, defense agencies, and major technology companies are racing to build machines capable of solving problems classical computers can’t. The risk is not merely computational speed but the potential collapse of cryptographic trust itself.

This urgency is now reflected in some landmark policy developments. The European Commission and EU Member States recently released a coordinated roadmap to transition the bloc’s digital infrastructure to post-quantum cryptography. It stipulates that by 2026, all Member States must begin national PQC strategies; by 2030, critical infrastructure must adopt quantum-resistant encryption; and by 2035, the transition should be completed across all feasible systems. 

The Ethereum Foundation’s decision to allocate funding and talent toward post-quantum research mirrors this new reality.

The dangerous comfort of long timelines

Despite these developments, some industry voices continue to downplay the risk. Bitcoin (BTC) pioneer Adam Back has argued that Bitcoin faces no meaningful quantum threat for 20 to 40 years. This position rests on the assumption that danger only begins when a quantum computer can break cryptographic keys in real time.

The threat does not start when quantum machines arrive at full strength; it starts when attackers can harvest public keys today and wait. Deloitte recently reported that roughly four million Bitcoin, around 25% of all usable supply, sit in addresses that expose public keys vulnerable to quantum attacks. Once a sufficiently advanced quantum computer exists, those wallets could be drained almost instantly using Shor’s algorithm. 

The damage would not unfold gradually. It would be sudden, asymmetric, and irreversible.

Why upgrading is not a simple fix

Supporters of the long-horizon view argue that Bitcoin and other blockchains can simply adopt the National Institute of Standards and Technology’s post-quantum cryptography standards when the time comes. But cryptographic migration is a protocol-level transformation, not a routine patch.

Researchers estimate that upgrading Bitcoin to a quantum-resistant cryptosystem could require up to 75 days of downtime, or over 300 days if the network must operate at reduced capacity to limit attack vectors during migration. For a trillion-dollar asset class, such a disruption would ripple through exchanges, derivatives markets, ETFs, institutional custody systems, and payment rails. This is a risk the market is not currently pricing in.

Blockchains are not alone in this exposure, as the global banking and payments infrastructure relies on the same cryptographic standards now considered vulnerable. A quantum breach would compromise not just assets, but identity systems, digital signatures, interbank settlements, and automated clearing mechanisms.

In practical terms, this could mean frozen payment rails, invalidated digital contracts, and emergency shutdowns of financial networks. The shock would move beyond crypto into equity markets, foreign exchange, and sovereign debt, creating a systemic crisis rooted in broken trust.

When AI and quantum outpace governance

This risk is amplified by the ongoing proliferation of AI, which is accelerating discovery, automation, and exploitation. When paired with quantum computing, it creates a scenario in which machine-scale attacks outpace human governance and regulatory response. Laws move in years. Algorithms move in milliseconds, and the gap is widening continuously. Decentralized systems were designed to remove single points of failure, yet cryptographic fragility threatens to reintroduce them at the foundation layer.

If cryptographic assumptions change, valuations will follow, and capital will increasingly favor quantum-resilient infrastructure. Risk premiums on legacy chains will widen, and regulators will increasingly demand transparency around cryptographic readiness, and institutional investors will expect quantum-risk disclosures. The Ethereum Foundation’s decision is an early signal that the markets will not ignore for long.

Building a swap DApp is relatively straightforward. Running it under real market conditions — with bots, arbitrageurs, and volatile liquidity — is not. BeInCrypto sat down with Andrey Fedorov, CMO & CBDO at STON.fi Dev at Consensus Hong Kong to hear what that process actually looked like.

STON.fi launched as an AMM (automated market maker) on TON Blockchain — a swap interface with liquidity pools. Omniston, its liquidity aggregation protocol, came later as a response to fragmentation: multiple DEXs on TON meant users had to manually compare prices across protocols. Omniston was supposed to fix that by aggregating liquidity into a single access point.

Aggregation worked. But scale exposed new constraints.

Three Lessons From Production

Fedorov is candid about what went wrong early on. “First there was just one token, and it was very easy to provide the technology. Activity levels were minimal, and the user base was still small. But over time it exploded.”

The first lesson was scaling. Both the front end and back end buckled under unexpected demand. The second was subtler: multi-hop swaps — routing trades through intermediate tokens — worked in testing but revealed edge cases under live conditions. “In theory, both hops execute seamlessly,” Fedorov explains. “In practice, you have simultaneous transactions, liquidity shifting across pools, and multiple DEXs updating state at once. The first hop can succeed while the second fails.”

The third lesson was about complexity itself. The initial model assumed a simple set of actors: users swap, liquidity providers provide. Reality added arbitrageurs, bots, and more complex interaction patterns that hadn’t yet been fully anticipated. “I don’t think it is actually possible to work out all these things in the beginning. You need to launch it, see how it goes, then fix something if it breaks.”

STON.fi now accounts for 80 to 90 percent of DEX activity on TON, underscoring its dominant share of swap volume on the chain. But cross-chain swaps, next on the roadmap, will reset that counter. “The fundamentals will be the same, but I’m sure we will see new challenges.”

Why Aggregation Wasn’t Enough

Omniston’s original proposition was to connect all TON DEX pools and find the best route. But aggregating public liquidity has a ceiling. If nobody has added liquidity to a particular pair, no amount of smart routing helps.

“Sometimes people just don’t want to provide liquidity in a specific pool,” Fedorov says. “When a user wants to swap a token in this pool, they can’t get a good price because there is no liquidity.”

The answer was escrow swaps — a parallel execution path that taps into private liquidity from professional market makers, or “resolvers.” Instead of relying solely on AMM pools, Omniston now evaluates both public and private sources and routes each swap through whichever delivers the better outcome.

“It’s not a silver bullet, because we need to have both. The combination provides the best experience.”

Tokenized Equities as a Stress Test

The escrow model proved its value when STON.fi integrated xStocks — tokenized representations of US equities issued by Backed Finance. These are technically TON jettons, but they behave differently from crypto-native tokens in ways that matter for execution.

The harder challenge was liquidity: unlike established crypto pairs, xStocks don’t yet have deep AMM pools across pairs. Technically, AMM support is there. But we also introduced an additional execution path — escrow swaps — so users can access deeper liquidity. Today, most xStocks volume executes through escrow.

From the user’s perspective, Fedorov insists the experience should feel identical to any other swap. “We want our users to forget about technical complexity. Under the hood it is different, but users don’t see it.”

The Self-Custody Trade-off

Fedorov is direct about the constraints of remaining fully non-custodial. 

“Sometimes we see solutions with strong traction — big user bases, high volume. From a business standpoint, integrating them would boost our growth immediately. But many of them are centralized. When I bring those options to our technical team, the answer is simple: it doesn’t work like that.” STON.fi is non-custodial. Users keep their assets in their wallets. Swaps are executed by smart contracts.

Centralized integrations are faster and simpler — often just an API connection. DeFi integrations require trustless, contract-level logic where assets never leave the user’s wallet. “We could grow faster if we compromised on custody. But then we wouldn’t be building DeFi infrastructure — we’d be building another fintech layer.”

The trade-off isn’t only technical. It’s educational. Sometimes this creates a marketing and communication challenge. Self-custody shifts responsibility to the user — something many newcomers underestimate. “If someone loses their seed phrase, we can’t restore access. We don’t have it. We’ve never had it. But quite often users still come to us expecting support, like they would from a bank or centralized exchange.”

In centralized systems, there’s a safety net — password reset, account recovery, customer service with override power. In DeFi, security comes from not having that backdoor. The same mechanism that protects users also removes our ability to intervene.

For STON.fi, that means investing more in onboarding, education, and clearer UX — without diluting the core principle of self-custody.

“It’s a long-term bet. In the short term, education is harder. But in the long term, users understand the value of ownership. Especially in Web3, that’s the point.”

Distribution First, Then Depth

Fedorov frames TON not only as a blockchain choice but also as a distribution strategy because of its integration with Telegram. STON.fi and Omniston integrate with wallets, apps, games, and bots across the Telegram ecosystem — each one a potential swap surface. “They want to use the protocol because they want to enable swaps in their applications. But it is also our distribution network. It’s a win-win.”

The next phase is cross-chain aggregation — starting with Tron, then expanding to EVM chains — to unify liquidity across ecosystems rather than just across DEXs on a single chain.

“Make things easier for those who don’t want to think about technical stuff. Get wider distribution by integrating into all the apps. And aggregate liquidity from multiple blockchains, not just one,” Fedorov says. “That’s the roadmap. Now it’s about scaling it.”

Crypto fear drops below zero on Matrixport index, hinting selling pressure may be exhausted and a reversal could be near.

Bitcoin sentiment has dropped to its most pessimistic levels in years, with Matrixport’s proprietary Greed and Fear Index signaling that selling pressure may be nearing exhaustion.

The financial services firm suggested in its most recent analysis that the market could be approaching a turning point, even as prices face continued short-term uncertainty.

Sentiment Plummets to Multi-Year Lows

In a chart published on February 17, Matrixport revealed that its Greed and Fear Index has fallen below zero on its 21-day average, a zone that in past cycles appeared close to price floors.

The model tracks changes in positioning and volatility, and earlier instances of similar readings often occurred shortly before markets stabilized. The note added that prices could still drop further before any recovery, though historically such pessimistic sentiment often coincided with what it called “attractive” entry periods.

“Given the cyclical relationship between sentiment and Bitcoin price action, the latest reading suggests the market may be approaching another inflection point,” the company stated.

Matrixport also pointed out that traders needed to be careful, with the current environment demanding they “sharpen” their focus in preparation for “conditions that typically precede a meaningful rebound.”

And their call isn’t without merit if observable signals like institutional flows are anything to go by. According to Lookonchain, Bitcoin investment products recorded another week of outflows, with $380 million exiting in the last seven days. In that time, BlackRock’s IBIT hemorrhaged 3,538 BTC, closely followed by Fidelity, which saw over 2,000 BTC worth upwards of $143 million withdrawn.

Additionally, while BTC was trading around the $68,000 level at the time of writing, barely slipping in the last 24 hours, the king cryptocurrency is down nearly 3% on the week, with steeper drops on longer timeframes, including a 28% collapse over 30 days and a more than 40% decline across the past six months, per data from CoinGlass.

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Derivatives Contraction Signals

Matrixport’s analysts aren’t the only ones who’ve noticed the mood of trepidation in the market. Earlier in the month, Alternative.me’s widely followed Fear and Greed Index told a similar story, dropping to its lowest level since 2019, after Bitcoin shaved about $30,000 from its price in less than ten days.

Interestingly, data shared earlier today by analyst Darkfost pointed to another pressure point. According to them, open interest across exchanges has been shrinking steadily since the October 2025 market top, with positions on Binance down about 39% and declines of approximately 33% on Bybit and 24% on BitMEX.

“This environment indicates that investors are actively reducing exposure, cutting risk, or being forced out through liquidations driven by ongoing volatility,” Darkfost explained. “Under these conditions, it is difficult to envision Bitcoin stabilizing sustainably and reigniting a bullish trend in the short term.”

In 2026, documents are no longer passive records. They are high-value operational assets. Invoices dictate cash velocity. Contracts determine legal exposure. KYC forms influence compliance posture. Insurance claims impact profitability. Regulatory filings define reputational stability. Yet most enterprises still rely on rule-based OCR tools that fail to understand context, interpret intent, or scale with unstructured data growth.

According to industry research from Mordor Intelligence: The global Intelligent Document Processing market is growing rapidly due to AI adoption, automation demand, and regulatory pressures. Similarly, Fortune Business Insights projects significant expansion of IDP across BFSI, healthcare, and logistics: This transformation is not incremental. It is structural. Partnering with a Top Intelligent Document Processing Company is no longer an operational decision; it is a strategic one.

Modern Intelligent Document Processing Solutions combine:

• Artificial Intelligence (AI)
• Machine Learning (ML)
• Natural Language Processing (NLP)
• Large Language Models (LLMs)
• Computer Vision
• Robotic Process Automation (RPA)
• Workflow orchestration

The result? A self-optimizing document lifecycle engine that extracts, validates, interprets, and routes information autonomously.

What is Intelligent Document Processing (IDP)?

Enterprise Intelligent Document Processing is an AI-driven automation framework that transforms document-heavy workflows into structured, validated, and decision-ready intelligence streams.

Unlike traditional OCR which captures text without understanding, AI-Based Intelligent Document Processing Solutions interpret relationships, intent, risk signals, and contextual meaning within documents. According to Gartner, IDP combines:

• Artificial Intelligence (AI)
• Machine Learning (ML)
• Optical Character Recognition (OCR)
• Natural Language Processing (NLP)
• Analytics

To convert structured and unstructured documents into reliable business data, thus reducing manual effort while accelerating enterprise decision cycles.

How a Leading Intelligent Document Processing Company Delivers Value

Capture Seamlessly

Documents are ingested across omnichannel inputs email, APIs, mobile uploads, cloud repositories, scanners, and enterprise applications. Advanced pre-processing enhances image quality, ensuring the accuracy of downstream extraction.

Extract Intelligently

Using computer vision and domain-trained models, the platform extracts:

• Structured fields
• Multi-level tables
• Handwritten inputs
• Clause-level intelligence

Models continuously self-improve through feedback loops, reducing template dependency and manual retraining.

Interpret Context

LLMs and NLP engines evaluate semantic meaning, detect anomalies, identify contractual risk, and distinguish between similar data elements while maintaining explainability and traceability. 

Validate Dynamically

Data is cross-validated against ERP, CRM, compliance rules, and external databases. Confidence thresholds and rule engines ensure only high-integrity data proceeds downstream. 

Orchestrate Autonomously

Integrated with RPA and workflow engines, the system routes documents, triggers actions, and escalates exceptions using intelligent human-in-the-loop (HITL) controls.

Generate Decision Intelligence

Modern Intelligent Document Processing Solutions go beyond extraction; they deliver:

• Automated contract summaries
• Fraud pattern detection
• Cross-document analysis
• Conversational document querying

Why Enterprise Intelligent Document Processing is Dominating 2026

1. The Explosion of Unstructured Data

Industry reports consistently highlight that most enterprise data remains unstructured. Emails, PDFs, contracts, ESG disclosures, and scanned forms contain high-value insights but lack structured formatting.

Persistence Market Research forecasts continued enterprise adoption of IDP technologies for unstructured data management. A leading Intelligent Document Processing Company transforms unstructured chaos into structured intelligence in real time.

2. Regulatory Complexity & Compliance Automation

Regulatory frameworks such as financial compliance mandates, healthcare documentation rules, and data protection standards are increasing globally. Organizations are adopting Enterprise Intelligent Document Processing to ensure:

• Complete audit trails
• Automated validation
• Reduced human error
• Secure data handling

AIIM’s industry survey shows enterprises accelerating IDP adoption beyond basic automation into compliance and governance applications. Compliance is no longer reactive. It is algorithmically enforced.

3. Generative AI Is Transforming Document Intelligence

The integration of LLMs into document workflows is redefining how enterprises interact with data. Gartner research on Generative AI’s impact on document processing highlights how AI models are enhancing contextual understanding and reasoning. Modern AI-Based Intelligent Document Processing Solutions now enable:

• Automated contract summarization
• Risk clause identification
• Conversational document querying
• Compliance gap analysis
• Executive-ready reporting

Documents are becoming interactive intelligence systems.

4. Operational Efficiency & Cost Optimization

Expert Market Research projects continued market growth driven by cost-reduction initiatives and automation acceleration. Organizations implementing Enterprise Intelligent Document Processing commonly report:

• Reduced processing time
• Lower operational costs
• Improved SLA adherence
• Faster decision cycles
• Reduced fraud exposure

This is operational leverage at scale.

Our Intelligent Document Processing Solutions

As a leading Intelligent Document Processing Company, we engineer enterprise-grade platforms built for scale, security, and performance.

AI-Powered Document Classification

Our Enterprise Intelligent Document Processing platform auto-classifies:

• Invoices vs. Purchase Orders
• KYC vs. onboarding forms
• Claims vs. policies
• Contracts vs. amendments

Models continuously learn and adapt to new document formats.

Advanced Contextual Data Extraction

Unlike static OCR templates, our AI-Based Intelligent Document Processing Solutions extract:

• Multi-level tables
• Financial figures
• Embedded metadata
• Signatures and stamps
• Clause-level intelligence

This capability aligns with multimodal AI advancements described in emerging IDP research.

Generative AI Document Reasoning

We integrate LLM-driven reasoning to deliver:

• Contract summaries in seconds
• Comparative clause analysis
• Risk detection
• Cross-document anomaly identification
• Conversational search interfaces

Enterprise Intelligent Document Processing is evolving into autonomous reasoning engines.

Human-in-the-Loop Governance

Enterprise accuracy demands oversight.

Our Intelligent Document Processing Solutions include:

• Confidence scoring
• Smart exception handling
• Validation workflows
• Continuous retraining

This hybrid AI-human model ensures compliance-grade precision.

Enterprise Integrations & Infrastructure

A top-tier Intelligent Document Processing Company must integrate seamlessly with:

• ERP systems
• CRM platforms
• RPA environments
• Cloud storage
• Hybrid infrastructure

Gartner’s Magic Quadrant resource for IDP vendors demonstrates the increasing enterprise integration maturity of the sector:

Security & Compliance by Design

Security is foundational in our AI-Based Intelligent Document Processing Solutions:

• End-to-end encryption
• Role-based access controls
• Immutable audit logs
• Zero-trust architecture

Enterprise security cannot be an afterthought.

Industry-Specific Impact of Enterprise Intelligent Document Processing

Enterprise Intelligent Document Processing (IDP) is no longer a horizontal efficiency tool; it has evolved into a verticalized transformation engine tailored to the regulatory, operational, and risk dynamics of specific industries. By combining AI-driven extraction, contextual intelligence, validation engines, and workflow orchestration, IDP delivers measurable impact across high-document-volume sectors.

Banking & Financial Services

• Automated KYC verification
• Loan document structuring
• Fraud anomaly detection
• Regulatory audit readiness

Insurance

• Claims data extraction
• Underwriting risk validation
• Policy clause digitization

Healthcare

• Patient onboarding automation
• Medical record digitization
• Insurance eligibility validation

Legal

• Contract lifecycle automation
• Clause-level risk detection
• Due diligence acceleration

Logistics & Supply Chain

• Bill of lading automation
• Three-way invoice matching
• Trade compliance validation

Key Benefits of Choosing a Top Intelligent Document Processing Company

Choosing a leading Intelligent Document Processing Company is not just a technology upgrade; it’s a strategic enterprise transformation decision. High-performing Enterprise Intelligent Document Processing Solutions drive measurable gains in efficiency, financial performance, compliance strength, and scalable growth.

1. Structural Cost Reduction

Automation reduces manual review dependency and operational overhead.

2. Accelerated Processing Cycles

Straight-through processing eliminates bottlenecks and improves customer responsiveness.

3. Higher Data Accuracy

Continuous model training reduces correction rates and increases confidence scores.

4. Embedded Compliance Governance

Validation engines and audit logs reduce regulatory exposure.

5. Enterprise-Grade Scalability

Cloud-native, API-driven architecture scales across geographies and departments.

6. Real-Time Decision Intelligence

Structured document data feeds dashboards, analytics, and AI models instantly.

2026 Trends Shaping the Future of IDP

Intelligent Document Processing is rapidly evolving from a tactical automation tool into a strategic enterprise intelligence layer powered by AI, generative reasoning, and autonomous workflows. Multiple industry sources and market analyses show that IDP is transitioning from static extraction toward adaptive, context-aware, and integrated intelligence systems.

1. Multimodal AI Unlocks Next-Gen Document Understanding

Modern IDP platforms combine computer vision, NLP, and deep learning to interpret text, layout, images, tables, and handwritten inputs simultaneously. This enables systems to understand both structure and meaning across complex, multi-format documents. The result is higher automation accuracy and contextual intelligence beyond traditional OCR limitations.

2. Intelligent, Agentic Reasoning Engines

IDP is evolving into an AI-driven reasoning layer that not only extracts data but also evaluates context, detects risk, and recommends actions. By embedding large language models and validation logic, platforms can autonomously interpret intent and support decision-making. Documents are no longer processed; they are analyzed and reasoned over.

3. Zero-Touch & Autonomous Workflow Orchestration

Organizations are adopting zero-touch workflows where high-confidence documents move through validation and system updates without human intervention. Confidence scoring, real-time rule checks, and intelligent exception routing minimize manual review. This dramatically reduces cycle times while preserving governance and auditability.

4. Regulatory & ESG Reporting Automation

With the expansion of global compliance mandates, IDP is increasingly used to extract, validate, and structure regulatory and ESG disclosures. Automated audit trails and rule-based verification improve transparency and reporting accuracy. This capability is becoming essential for risk management and corporate accountability.

5. Cloud-First & Integrated Enterprise Architectures

Cloud-native IDP deployments offer elastic scalability, global accessibility, and seamless integration with ERP, CRM, and automation platforms. API-driven connectivity enables real-time data exchange across enterprise ecosystems. IDP is shifting from a standalone tool to a foundational layer within intelligent automation stacks.

Why Choose Us as Your Intelligent Document Processing Company?

Our Intelligent Document Processing Solutions are built on:

AI-First Architecture

Built from the ground up with artificial intelligence at its core, enabling adaptive learning, contextual understanding, and long-term scalability. This ensures smarter automation that evolves with your business.

Domain-Trained Enterprise Models

Industry-specific AI models designed to understand complex documents in regulated sectors. They deliver higher accuracy, reduced risk, and minimal manual intervention.

Generative AI Reasoning

Advanced AI that not only extracts data but also interprets intent, summarizes content, and identifies risks. It transforms documents into actionable intelligence.

Secure, Scalable Infrastructure

Enterprise-grade architecture with robust security, compliance controls, and cloud scalability. Designed to handle high volumes while maintaining resilience and governance.

Dedicated AI Architects

Expert AI strategists who align automation with your business objectives and continuously optimize performance. We act as long-term transformation partners, not just vendors.

Continuous Optimization

Ongoing monitoring, model refinement, and workflow enhancement to maximize ROI. Your automation improves over time as business needs evolve.

The Autonomous Enterprise Starts Here

The document-heavy enterprise of the past cannot thrive in an AI-driven economy where speed, intelligence, and adaptability define market leaders. A Top Intelligent Document Processing Company transforms static documents into actionable intelligence, operational friction into measurable velocity, and compliance complexity into strategic strength.

Modern Enterprise Intelligent Document Processing now serves as the core digital infrastructure powering automation, real-time insight, governance control, and data-driven decision-making at scale. Organizations that embed IDP deeply within their workflows accelerate performance, reduce risk exposure, and unlock sustainable growth.

The question is no longer whether to adopt IDP but how fast you can deploy it. Partner with Antier to build a secure, future-ready foundation for an autonomous enterprise.

Authorities in Russia’s Republic of Dagestan have opened a criminal investigation against a local man suspected of financing terrorism, the state news agency TASS reported.

Russian arrested as scrutiny grows over crypto and terror financing

The case was initiated by investigators in Makhachkala, the region’s capital, where a man is accused of providing funds or material support that could have been used to assist extremist activities. The move reflects ongoing efforts by Russian law enforcement to clamp down on suspected financial networks linked to terrorism.

According to the TASS report, specific details about the actions that triggered the probe have not been disclosed publicly, but the initiation of a formal criminal case indicates that authorities believe there are sufficient grounds to pursue charges.

The suspect is currently under investigation while law enforcement continues to gather evidence.

Russia has been actively investigating and prosecuting individuals and groups accused of involvement in terrorism-related activity, particularly in the North Caucasus region where separatist and extremist networks have historically been a concern for federal authorities. Previous high-profile terrorism cases have drawn significant media attention and have often involved complex financial structures alleged to support violent acts.

The investigation comes amid heightened global attention on the role cryptocurrencies can play in illicit finance. Law enforcement agencies in Europe and elsewhere have increasingly warned that digital assets, particularly when routed through opaque or loosely regulated services, can create opportunities for money laundering, sanction evasion, and covert transfers.

This dynamic has placed crypto transactions under close watch by both national security and financial regulators.

Meanwhile, the European Union is preparing a sweeping ban on cryptocurrency transactions involving Russian entities as part of its latest sanctions package, aiming to close loopholes that allowed sanctioned actors to shift value via digital asset service providers.

The crypto market continued to exhibit weakness on Tuesday morning, broadly following a tech selloff across U.S. equities and a correction in the price of precious metals.

Bitcoin trades at $68,000, down 1.25% since midnight UTC, while Nasdaq futures and gold lost 0.55% and 2.4% respectively over the same period.

Altcoins also lost ground as popular memecoins PEPE, DOGE and TRUMP led the drawdown, losing between 3.5% and 4.5%.

The tech selloff has been driven by fears around artificial intelligence and how it might disrupt several industries. Bitcoin has been closely tied to Nasdaq since Feb. 3, with the correlation coefficient indicator rising from negative 0.68 to positive 0.72 over the past two weeks.

Gold, meanwhile, is currently trading at $4,928 after failing to establish a level of support above $5,000. The precious metal hit a record high of $5,600 on Jan. 28 before a historic 21.5% correction over the subsequent four days.

Derivatives positioning

• Crypto futures continue to see capital outflows. The cumulative industry wide notional open interest has declined by 1.5% to $93 billion in 24 hours, reaching fresh multi-month lows.
• Leveraged bets worth $229 billion have been liquidated by exchanges over 24 hours, with longs (bullish plays) accounting for most of the tally.
• Open interest in DOGE futures has declined by 4%, leading the trend in most majors. PEPE, LINK and AVAX have seen 3% to 5% declines in open interest.
• Open interest in futures tied to HYPE, the recent outperformer, has cooled to 44.45 million HYPE, the lowest since early December. This likely reflects profit-taking after the token outpeformed bitcoin and other majors during the recent crash.
• The market panic has ebbed, as evidenced from the sharp pullback in bitcoin and ether’s implied volatility indices from monthly highs.
• On Deribit, bitcoin and ether puts continue to trade pricier than calls, indicating lingering downside fears, however, the positioning is now longer as defensive as it was two weeks ago.

Token talk

• Altcoins continue to track bitcoin on as the “bitcoin dominance” metric has now ranged between 57.4% and 60.1% since September.
• Over the past seven days AI token MORPHO has posted a 23.5% gain, while privacy coin zcash ZEC$284.32 is up by 19% over the same period.
• Conversely, layer 1 blockchain token layer zero (ZRO) has lost 16% over the past week as it continues to lose momentum after announcing a deal to collaborate with Citadel Securities and DTCC.
• The relative weakness of several altcoins continues to persist on lower time frames, with HYPE, SUI and ASTER all losing between 3% and 4.8% since midnight UTC as the crypto market awaits a bullish catalyst.

Congress races to finalize US crypto market rules as Trump-backed bill nears passage, splitting SEC–CFTC powers and setting deadlines on exchanges and stablecoins.

CFTC launches CEO Innovation Council for crypto oversightUnder the proposed framework, the CFTC would assume primary regulatory authority over digital commodities including Bitcoin and Ethereum. The legislation provides brokers and exchanges a 180-day registration window to obtain provisional status following enactment.

CFTC Chairman Michael Selig has indicated the bill could reach the President’s desk within months, according to public statements. The framework would require joint SEC and CFTC rulemaking within 18 months to address complex areas including mixed transactions and margin structures.

The Senate Banking Committee must reconcile its version with the Agriculture Committee’s draft before the February 28 White House deadline for stablecoin frameworks, according to congressional schedules.

Congressional leaders continue to call for investigations into Trump-linked cryptocurrency ventures, including WLFI, according to statements from members of Congress.

As the GBP/JPY chart shows, the pound has dropped below the 12 February low against the Japanese yen, marking its weakest level since the beginning of 2026. The pair last traded beneath the 207.500 mark in mid-December 2025.

→ The yen’s strength is supported by expectations that economic stimulus measures introduced by Prime Minister Sanae Takaichi, in coordination with the Bank of Japan, will underpin the national currency. Barclays forecasts further appreciation of the yen.

→ Sterling weakened today following reports that UK unemployment reached a five-year high in December, while wage growth slowed. This may reinforce arguments in favour of additional interest rate cuts by the Bank of England.

Technical Analysis of GBP/JPY

Long-term moving averages are turning lower, signalling potential structural shifts and possible capital reallocation after five years of an overall uptrend in GBP/JPY.

Price action is forming a well-defined descending channel. In this context:
→ the median line has switched from acting as support to serving as resistance (as highlighted by the thicker lines);
→ today, GBP/JPY is trading in the lower quarter of the channel, indicating continued bearish dominance.

It is worth noting that yesterday’s breakout above local resistance (marked by an arrow) proved to be false, triggering renewed downward momentum.

On the other hand, after dipping below the 12 February low near 207.560, the pair has started to rebound, raising the possibility of a mirrored move and a false bearish breakout.

Nevertheless, the outlook for bulls remains challenging. Even if they manage to push prices slightly higher, they may encounter resistance around 208.315 — a level where sellers previously demonstrated strength when breaking local support (shown in purple).

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