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The Role of AI Chatbots in Modern HR Process Automation

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Human Resources has evolved from an administrative function into a strategic driver of organizational performance. Yet, despite this shift, many HR teams remain burdened by manual processes, fragmented systems, and reactive workflows that do not scale with modern workforce demands. As organizations grow across geographies, compliance frameworks, and talent models, the complexity of HR operations increases exponentially. Traditional HR automation tools, built on rigid workflows and static portals, fail to deliver the responsiveness and intelligence required today.

This is where AI chatbots in HR are redefining how organizations automate, scale, and modernize HR operations. By partnering with an experienced AI Chatbot Development Company, enterprises can implement conversational interfaces powered by artificial intelligence to unlock a new era of HR process automation – one that is proactive, context-aware, and deeply integrated into core business systems.

The Limitations of Traditional HR Automation Systems

Before understanding the impact of AI chatbots, it is critical to examine why legacy HR automation approaches fall short.

Key Challenges in Traditional HR Operations

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  • HR systems operate in silos (HRMS, ATS, payroll, compliance tools)
  • Employees struggle to navigate complex portals for simple queries
  • Most HR workflows rely on email-based approvals
  • Policy interpretation remains manual and inconsistent
  • HR teams spend the majority of their time on repetitive support tasks

Despite digitization, HR remains process-heavy but intelligence-light. Automation exists, but decision-making and interpretation still require human intervention. This operational gap has created the need for HR automation using AI, where systems can understand, decide, and act without constant manual oversight.

How AI Chatbots Enable HR Workflow Automation at Enterprise Scale

Unlike traditional rule-based systems that rely on fixed keywords, modern AI chatbots are built to understand how employees naturally communicate. Powered by advanced language intelligence and enterprise integrations, they play an active role in automating HR operations rather than simply responding to queries.

Key Differentiators of AI Chatbots in HR
  • Intent-based understanding, not keyword matching
    AI chatbots use Natural Language Processing to accurately interpret employee intent even when questions are informal, incomplete, or phrased differently.
  • Context-aware conversations
    By retaining conversation history and employee context such as role, location, and policy eligibility, chatbots deliver consistent and personalized responses without repetition.
  • Direct integration with HR systems
    AI chatbots connect seamlessly with HRMS, payroll, ATS, and compliance platforms to retrieve real-time data and perform actions securely.
  • Built-in workflow execution
    Beyond answering questions, chatbots can initiate and complete HR workflows, including leave applications, approvals, and record updates.
  • Active participation in HR operations
    These capabilities allow AI chatbots to move beyond static FAQs and function as intelligent, action-driven components of end-to-end HR process automation.

Together, these capabilities form the intelligence layer that differentiates AI-powered HR solutions from traditional, rule-based HR software.

AI Chatbots for Employee Self-Service: Redefining HR Accessibility

One of the most impactful and widely adopted use cases of AI chatbots in HR is employee self-service automation. As organizations scale, HR teams are increasingly overwhelmed by repetitive, high-volume queries that do not require human intervention but still consume significant time and resources.

The Employee Experience Challenge

Employees regularly reach out to HR for routine requests such as:

  • Leave balances and approval status
  • HR policy explanations and clarifications
  • Payroll and salary-related questions
  • Benefits eligibility and coverage details
  • Tax documents and compliance information

While these queries are essential, they are largely repetitive and manual, leading to slower response times, employee frustration, and reduced HR productivity.

How AI Chatbots Enable Self-Service at Scale

When integrated with core HRMS and payroll systems, AI chatbots for employee self-service can:

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  • Securely authenticate employees
  • Retrieve real-time, role-specific HR data
  • Interpret policies contextually based on eligibility
  • Deliver instant, conversational responses

This approach significantly reduces dependency on HR support tickets while ensuring employees receive accurate, consistent, and timely information—anytime they need it.

HR Workflow Automation Using AI Chatbots

The true power of AI chatbots lies in their ability to execute HR workflows, not just provide information.

Examples of Automated HR Workflows

  • Leave requests and approvals
  • Attendance regularization
  • Shift and roster management
  • Policy acknowledgment tracking
  • Employee exit and clearance processes

How Workflow Automation Works

Instead of navigating forms or sending emails, employees interact naturally:

Employee: “Apply for three days of leave starting Monday.”

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AI Chatbot:

  • Validates leave balance
  • Checks policy rules
  • Routes approval to the manager
  • Updates HRMS automatically

This is HR workflow automation driven by conversation, fast, accurate, and scalable.

AI Chatbots for Recruitment: Automating Talent Acquisition at Scale

Recruitment is one of the most resource-intensive HR functions, making it an ideal candidate for automation.

AI Chatbots for Recruitment and Candidate Engagement

AI chatbots assist recruitment teams by:

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  • Engaging candidates 24/7
  • Answering role-specific queries
  • Screening candidates based on predefined criteria
  • Scheduling interviews automatically
  • Sending follow-ups and reminders

This improves both recruiter efficiency and candidate experience.

Intelligent Candidate Screening

Chatbots can evaluate:

  • Skill relevance
  • Experience thresholds
  • Availability and location preferences
  • Role alignment

By automating early-stage screening, recruiters focus on high-quality candidates instead of manual filtering.

AI Chatbots for Onboarding: Accelerating Time-to-Productivity

Once a candidate is hired, onboarding becomes the next critical HR challenge.

How AI Chatbots Improve Onboarding

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AI chatbots guide new employees through:

  • Document submission and verification
  • Policy walkthroughs
  • IT and access requests
  • Training module assignments
  • First-week task coordination

This structured, guided onboarding experience improves retention, engagement, and early productivity.

Payroll and HR Compliance Automation with AI Chatbots

Payroll and compliance processes involve high risk, strict regulations, and minimal tolerance for errors.

1. Payroll Automation Use Cases

AI chatbots can:

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  • Explain salary structures
  • Break down tax deductions
  • Track reimbursements
  • Answer bonus and incentive queries

2. HR Compliance Automation

Chatbots assist with:

  • Labor law interpretation
  • Location-specific compliance rules
  • Policy enforcement consistency
  • Audit-ready interaction logs

This enables payroll and HR compliance automation with reduced manual dependency and lower risk exposure.

AI Chatbots for Internal HR Support and Knowledge Management

HR knowledge often exists in scattered formats, such as PDFs, intranets, shared drives, and emails.

Centralized HR Knowledge Access

AI chatbots for internal HR support act as a unified interface that:

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  • Retrieves policy documents instantly
  • Interprets complex policy queries
  • Escalates sensitive issues appropriately
  • Provides role-specific guidance to managers and employees

This transforms HR from a reactive support function into a structured, intelligent service layer.

Enterprise Architecture for AI-Powered HR Solutions

Enterprise-grade HR chatbots require a robust technical foundation.

Key Components:

  • Conversational AI and LLMs
  • Secure HR data retrieval (RAG pipelines)
  • HRMS, ATS, and payroll integrations
  • Workflow orchestration engines
  • Role-based access control (RBAC)
  • Compliance logging and audit trails

Because of this complexity, most enterprises partner with an experienced AI Chatbot Development Company to design, build, and maintain these systems.

Data Privacy, Security, and Compliance Considerations

HR data includes sensitive personal and financial information. Any AI-driven HR system must prioritize security.

Best Practices

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  • End-to-end data encryption
  • On-premises or private cloud deployment
  • Zero data retention for AI models
  • Access control by role and hierarchy
  • Compliance with GDPR and regional labor laws

Without these safeguards, HR automation introduces operational risk.

The New Standard for HR Operations

As workforce structures grow more complex and distributed, organizations must move beyond basic digitization and embrace intelligent, AI-driven automation. AI chatbots are no longer optional add-ons; they are becoming the backbone of modern HR operations and a core component of enterprise HR workflow automation solutions. By enabling employee self-service, automating recruitment and onboarding, streamlining payroll and compliance, and strengthening internal HR support, AI chatbots deliver faster execution, consistent governance, and significantly improved employee experiences. The future of HR belongs to organizations that invest early in scalable, secure, and AI-powered HR solutions, setting new benchmarks for efficiency, agility, and workforce engagement.

Antier empowers enterprises to build next-gen AI-driven HR ecosystems as a trusted AI Chatbot Development Company, delivering secure, enterprise-grade chatbot solutions tailored for complex HR environments. With deep expertise in AI, automation, and system integration, Antier helps organizations transform HR into a strategic, future-ready function.

Frequently Asked Questions

01. How have HR operations evolved in recent years?

HR operations have shifted from being purely administrative to becoming a strategic driver of organizational performance, although many teams still face challenges with manual processes and fragmented systems.

02. What are the limitations of traditional HR automation systems?

Traditional HR automation systems often operate in silos, require manual intervention for decision-making, and rely on outdated workflows, making them less responsive to modern workforce demands.

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03. How do AI chatbots improve HR workflow automation?

AI chatbots enhance HR workflow automation by using Natural Language Processing to understand employee intent, enabling proactive and context-aware interactions that streamline HR operations.

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South Korea launches probe Into Bithumb after $43B “fat-finger” Bitcoin blunder

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South Korea launches probe Into Bithumb after $43B “fat-finger” Bitcoin blunder

South Korea’s Financial Supervisory Service (FSS) has escalated scrutiny of major cryptocurrency exchange Bithumb following an unprecedented operational mistake in which the firm accidentally credited customers with tens of billions of dollars’ worth of Bitcoin.

Summary

  • South Korea’s Financial Supervisory Service (FSS) has launched a full-scale investigation into Bithumb following a massive $43 billion Bitcoin “fat-finger” error.
  • The incident stemmed from an internal operational mistake that temporarily credited users with Bitcoin far exceeding the exchange’s actual holdings.
  • Regulators are examining Bithumb’s internal controls and IT systems, with potential penalties possible if violations are confirmed.

The investigation follows a striking error on February 6, 2026, when Bithumb, during a routine promotional event, inadvertently distributed 620,000 Bitcoin, worth roughly $40 billion to $44 billion at market prices, to users instead of the intended small cash rewards.

The mishap stemmed from an employee inputting payouts in Bitcoin (BTC) units rather than Korean won, leading to an explosion of overissued Bitcoin credits before the mistake was detected.

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What happened in the Bithumb mistake

In a “Random Box” promotion designed to reward users with modest cash amounts, Bithumb’s payout system mistakenly issued Bitcoin due to a unit entry error, resulting in the colossal overshoot.

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Within minutes, hundreds of users found massive sums of Bitcoin in their accounts, equivalent to 13–14 times Bithumb’s actual BTC holdings based on industry estimates.

The exchange acted swiftly to freeze affected accounts and block trading and withdrawals within about 35 minutes, recovering the vast majority of the missent tokens. Still, a small portion, representing millions in value, was sold or withdrawn before the controls took effect.

FSS investigation and regulatory response

Initially launching an emergency review, the FSS escalated its examination to a full-scale formal investigation. Bithumb was notified of the probe signalling a deep dive into what went wrong and whether internal controls violated the Virtual Asset User Protection Act or other regulatory standards.

FSS Governor Lee Chan-jin has emphasized that the episode revealed systemic weaknesses in internal control and electronic ledger systems at the exchange. Regulators are examining how an exchange with far fewer actual reserves was able to record and disburse phantom Bitcoin balances so rapidly.

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Depending on what investigators find, the probe could lead to sanctions against Bithumb, including fines or even suspension of operations if negligence or legal violations are confirmed. The FSS has also noted that users who sold erroneously credited Bitcoin may be legally obligated to return it as unjust enrichment under current interpretations of Korean law.

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This Crypto Bear Market Is Different as RWAs Grow

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Crypto Breaking News

Chainlink (CRYPTO: LINK) co-founder Sergey Nazarov argues that the current crypto downturn is not a replay of previous bear markets. Speaking on X on Tuesday, Nazarov noted that there have been no FTX-style collapses this time and pointed to a persistent wave of tokenized real-world assets that continues to grow despite price declines. Crypto market capitalization has fallen about 44% from its October all-time high of $4.4 trillion, with roughly $2 trillion leaving the space in just four months. He frames the cycle as a test of the industry’s progress: cycles reveal how far the ecosystem has advanced, and this downturn is exposing both resilience and a real-world asset narrative that could outlast speculative pricing.

Key takeaways

  • The downturn lacks a single systemic event comparable to FTX-era collapses, suggesting improved risk management across institutions.
  • Tokenized real-world assets (RWAs) are expanding on-chain, signaling a use case beyond mere price speculation.
  • On-chain perpetuals and asset tokenization offer 24/7 markets, on-chain collateral, and real-time data that could drive institutional adoption.
  • Chainlink’s credibility as a backbone for on-chain RWAs remains intact even as the broader market experiences weakness.
  • Analysts and industry observers see a bifurcation between crypto prices and the growth trajectory of on-chain RWAs, potentially reshaping the industry’s value proposition.

Tickers mentioned: $BTC, $ETH, $LINK

Sentiment: Neutral

Price impact: Negative. A broad sell-off and outflows have pressured prices and market capitalization, even as on-chain RWA activity trends higher.

Market context: The current cycle unfolds amid a shifting risk environment, macro uncertainty, and ongoing debates about liquidity and regulation that influence both crypto assets and tokenized RWAs.

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Why it matters

The argument that the bear market is not a monolithic crash but a spectrum of dynamics matters because it reframes what investors should watch. Nazarov emphasizes that the absence of large, systemic failures this cycle points to improved risk controls and more mature market infrastructure. In practical terms, this could translate into steadier liquidity provision, fewer cascading liquidations, and greater confidence in deploying capital through on-chain channels rather than off-ramp exits.

Central to this narrative is the acceleration of RWA tokenization. According to RWA.xyz, tokenized RWAs on-chain have surged by about 300% over the past 12 months, underscoring a use case that can prosper irrespective of crypto price cycles. The implication is clear: real-world assets—ranging from securitized notes to commodity-linked contracts—are becoming meaningful, on-chain stores of value and collateral concepts, not merely speculative bets. This trend could feed into broader institutional demand, as on-chain mechanisms offer transparency, auditability, and cross-border settlement capabilities that traditional markets take days or weeks to deliver.

Yet the market’s performance remains tethered to macro and sector-specific catalysts. LINK, the token associated with pricing data and oracle services, has faced sustained weakness, trading in bear-market territory after peaking earlier in the cycle. The dynamic illustrates a decoupling: while RWAs push forward in practical utility, the crypto market, including major assets like Bitcoin and Ethereum, can diverge for periods where macro sentiment dominates. In this context, on-chain RWAs could gradually displace some narrative weight away from pure price action toward real-world utility and risk-adjusted capital formation.

Institutional involvement is widely anticipated to hinge on the utility of these on-chain structures. Nazarov argues that the combination of perpetual markets, tokenized assets, and robust on-chain collateral is creating a more resilient foundation for institutions to experiment with crypto-enabled finance. The broader ecosystem benefits from infrastructure upgrades that enable risk management, settlement, and governance in a transparent, programmable environment. The takeaway is not that crypto prices must explode to prove value, but that the underlying systems—the oracles, the data streams, and the contractual primitives—are becoming indispensable to professional finance.

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As markets digest these developments, some observers emphasize that the current sell-off is driven by factors outside the crypto sector. Analysts have framed the move as a wider market concern about AI equities, liquidity expectations under a potentially tighter policy regime, and shifts in liquidity leadership. While these external pressures complicate the price narrative, the on-chain RWA ecosystem appears to be advancing on its own trajectory, aligned with broader fintech adoption and cross-chain interoperability goals.

“If these trends continue, I believe what I have been saying for years will happen; on-chain RWAs will surpass cryptocurrency in the total value in our industry, and what our industry is about will fundamentally change.”

Not all bear markets are equal

Industry observers have framed this downturn as potentially less damaging to the core ecosystem than prior cycles. Bernstein analyst Gautam Chhugani described the Bitcoin bear case as historically weak, suggesting that the price action reflects a crisis of confidence rather than a structural breakdown. “The current Bitcoin price action is a mere crisis of confidence. Nothing broke, no skeletons will show up,” the note said. The takeaway is that the macro environment, not just isolated crypto incidents, is weighing on sentiment.

Other voices emphasize a more nuanced picture. For instance, market participants note that macro catalysts—ranging from interest-rate expectations to tech-sector dynamics—have a disproportionate influence on crypto pricing versus on-chain activity. The sell-off has been described as being driven more by non-crypto catalysts than by internal systemic failures within the crypto space, a distinction that could support a faster reacceleration should risk appetite improve and liquidity return.

Market context

Against the backdrop of a 44% drawdown in crypto market cap from the October peak and substantial outflows, the story of RWAs on-chain remains a central pillar of longer-term value propositions in crypto. The dynamic underscores a broader trend toward tokenization and on-chain finance as mainstream infrastructure projects mature. If on-chain RWAs continue to gain traction, the sector could reorient investor attention toward scalable, real-world use cases, rather than relying solely on volatility-driven appetite for purely digital assets.

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Why it matters

For builders, the message is clear: investing in robust on-chain infrastructure for RWAs—oracle reliability, settlement speed, and secure collateral mechanisms—could yield enduring demand. For investors, RWAs offer a potential hedge against crypto-price cycles by anchoring value in tangible, off-chain assets. For the market, the continued growth of RWAs may redefine what constitutes “crypto value,” expanding the spectrum of investable instruments and potentially attracting traditional finance players to participate in a more regulated, verifiable on-chain ecosystem.

What to watch next

  • Updates from RWA.xyz on on-chain RWAs growth metrics and new asset classes tokenized on-chain.
  • Institutional pilots adopting on-chain perpetuals and RWA-backed collateral frameworks.
  • Regulatory developments affecting tokenized real-world assets and oracle data provisioning.
  • Cross-chain integrations that improve liquidity, settling quickly, and governance for RWAs.

Sources & verification

  • Sergey Nazarov’s X post discussing bear-market dynamics and RWAs growth.
  • RWA.xyz data showing on-chain RWA value growth (about 300% YoY).
  • LINK price/index coverage referenced in market commentary.
  • Bernstein note on Bitcoin bear-case context.
  • Wemade KRW stablecoin alliance with Chainlink coverage.

RWA momentum and a reshaping crypto market

Chainlink’s foundational role in powering on-chain RWAs remains a consistent thread as the sector charts its next phase. The on-chain RWA narrative is supported by observable growth metrics and a steady flow of products that enable real-world assets to exist, trade, and collateralize on-chain. While price action can swing with global liquidity and risk sentiment, the underlying technology stack—secure oracles, robust data feeds, and programmable contracts—continues to attract the interest of developers, institutions, and asset issuers alike. The broader question is whether on-chain RWAs will eventually carry a larger share of industry value than speculative crypto assets, a shift Nazarov has been vocal about predicting for years.

Risk & affiliate notice: Crypto assets are volatile and capital is at risk. This article may contain affiliate links. Read full disclosure

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Ethereum Enters Capitulation Zone as MVRV Turns Negative: Bottom Near?

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Latest Bitcoin & Ethereum News, Crypto Prices & Indexes

Ethereum (CRYPTO: ETH) has slipped into a zone that market watchers associate with capitulation, as on-chain signals flash bearish, yet opt for caution on whether a definitive bottom is in place. The focal point is the MVRV Z-Score, a gauge that compares current market value to the realized value, effectively measuring how much investors are paying relative to the price at which Ether last moved. A reading around -0.42 indicates Ether is trading below its realized value, a sign historically linked to stress but not a sole predictor of a lasting bottom. While some analysts argue this signals a clear capitulation phase, others warn that the current slide may not reach the extremes observed in past bear markets.

The MVRV Z-Score was designed to flag phases of euphoria or capitulation by showing when market value diverges markedly from realized value. In practice, a notably negative score has preceded bottoming behavior in prior cycles, albeit without a guaranteed timetable. Joao Wedson, a crypto Quant analyst and founder of Alphractal, described the current reading as “showing that Ethereum is indeed going through a clear capitulation process.” Yet, he cautioned that today’s data do not match the intensity of the 2018 and 2022 bear-market lows. The record low for the metric sits at -0.76, observed in December 2018, underscoring the scale of the slide that would be needed for a historical parallel.

Ether MVRV Z-Score tanks below zero in capitulation. Source: Alphractal 

The near-term horizon, however, remains contested. Wedson noted that further downside is possible before any sustained recovery takes hold, citing continued market stress and the possibility of liquidity constraints during tax season. “The market is already under stress, but historically, there is still room for further downside before a definitive structural bottom is formed,” he said. Ether’s price action has been volatile, with a sharp decline followed by a tentative rebound, complicating the call on whether the capitulation phase is nearing its end.

The recent price action has been punishing: Ether has fallen about 30% over the past two weeks, sinking to a bear-market low near $1,825 on a Friday before a modest rebound to roughly $2,100 on the following Monday. The moves come amid broader macro fragility and shifting risk sentiment within crypto markets, prompting both caution and opportunism among analysts. Some traders and researchers see this as a rare “buy fear” window, while others warn that risk remains elevated until on-chain dynamics confirm a bottom.

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HashKey Group senior researcher Tim Sun told Cointelegraph that historical performance has reinforced the view that Ethereum’s MVRV Z-Score can be a reliable indicator for identifying bottoming zones, particularly when combined with evolving on-chain activity and long-term ecosystem development. “Judging by on-chain activity, protocol evolution, and long-term ecosystem structure, Ethereum’s fundamentals have not seen any substantive deterioration. On the contrary, they continue to improve across several key dimensions,” he said. Still, Sun stressed that current trajectories could change if the primary drivers of decline persist, suggesting that a definitive bottom remains contingent on future liquidity and demand signals.

Meanwhile, other observers offered a more optimistic read. Michaël van de Poppe, founder of MN Fund, argued that the drawdown presents a rare opportunity to consider ETH as an investable bet, noting a substantial gap between the current price and the “fair price” implied by the MVRV ratio. “I think that this is a tremendous opportunity to be looking at ETH,” he tweeted, positing that negative deviations historically precede substantial recoveries when macro and on-chain conditions align. The narrative held that Ether’s network metrics and the broader ecosystem strength underpin a case for accumulation once the weak hands have been flushed out.

Other voices joined the chorus of potential catalysts for a rebound. Andri Fauzan Adziima, Bitrue’s research lead, suggested that persistent negative MVRV zones have historically preceded strong recoveries in subsequent cycles. He contended that ETH’s network fundamentals remained robust and that a long-term accumulation stance could emerge once price risk subsides. “Brutal capitulation now, but historically one of the best ‘buy fear’ windows for ETH,” Adziima said, underscoring the tension between near-term price action and longer-term structural factors.

ETH prices have tanked back to long-term cycle lows. Source: TradingView

Market participants acknowledged that the current pullback may be overshadowed by longer-term catalysts such as network upgrades and continued ecosystem maturation, even as price action remains sensitive to near-term liquidity and macro dynamics. The narrative that “buying fear” can yield outsized returns if followed by demand recovery continues to gain traction among several traders, though it remains balanced by caution regarding April liquidity and potential tax-related squeezes.

One of the best “buy fear” windows for Ether

Despite the caution, several observers argued that the current environment could present one of the more compelling entry points for ETH in recent memory. Van de Poppe’s commentary echoed a view shared by others that a sharp deviation below fair value can precede a robust rebound when demand returns and on-chain indicators resume strengthening. The notion is that ETH’s price could be primed for a longer-term recovery even if the immediate path remains choppy.

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As the debate continues, sentiment remains nuanced. Some participants emphasize that negative MVRV conditions have historically aligned with durable recoveries once the weak hands capitulate, while others warn that liquidity constraints around the April tax season could delay any sustained recovery. The balance between on-chain fundamentals and macro stressors will likely shape Ether’s trajectory over the coming weeks and into the next quarter.

For investors watching the tape, the key takeaway is that volatility may persist even as underlying fundamentals show resilience. The combination of a negative MVRV reading and persistent price pressure suggests that any bottoming process will require a convergence of favorable liquidity and sustained demand, rather than a simple technical bounce.

Why it matters

The ongoing discussion around Ether’s valuation and bottoming prospects matters for multiple stakeholders. For traders, MVRV-based indicators provide a framework to interpret on-chain signals amid price volatility, while investors may view the current setup as an opportunity to accumulate at a discount relative to realized value. For developers and ecosystem participants, the narrative about Ethereum’s fundamentals—network activity, upgrade timelines, and long-term growth—matters for capital allocation, governance engagement, and potential product developments that could draw renewed user interest.

From a market-wide perspective, Ethereum’s fate remains a bellwether for risk appetite in crypto markets. A clear bottom in ETH could bolster sentiment across altcoins and contribute to a broader risk-on environment, while a protracted drawdown could reinforce caution and delay recovery for other assets. In either case, the episode underscores the importance of on-chain metrics as a corroborating lens for price action, beyond headlines and short-term moves.

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What to watch next

  • Monitor liquidity conditions around the April tax season for potential downside or relief catalysts.
  • Track on-chain indicators related to MVRV Z-Score and general network activity to assess whether a structural bottom forms.
  • Watch for sustained price stabilization above recent lows and any acceleration in demand signals that could precede a rebound.
  • Observe broader macro factors and crypto market flows that could influence risk sentiment and capital allocation.

Sources & verification

  • On-chain MVRV Z-Score interpretation and commentary by Joao Wedson of Alphractal (tweet/status referenced in the article).
  • Cointelegraph reports on Ether’s 30% decline over a two-week period and the subsequent move to around $2,100.
  • HashKey Group insights from Tim Sun regarding MVRV Z-Score reliability and Ethereum fundamentals.
  • Industry commentary from Michaël van de Poppe and Bitrue’s Andri Fauzan Adziima on negative MVRV zones and potential buy opportunities.

Risk & affiliate notice: Crypto assets are volatile and capital is at risk. This article may contain affiliate links. Read full disclosure

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U.S. BTC ETFs register back-to-back inflows for first time in a month

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U.S. BTC ETFs register back-to-back inflows for first time in a month

For the first time in nearly a month, U.S. bitcoin exchange-traded funds (ETFs) have recorded back-to-back net inflows, snapping a redemption streak that stretched back to mid-January.

According to SoSo value data, the consecutive inflows shift began on Friday with $471.1 million in fresh capital, followed by a $144.9 million on Monday. This comes as bitcoin bounced back from Thursday’s $60,000 low to around $70,000.

In mid-January, bitcoin peaked near $98,000 after a two week rally that started at $87,000. The subsequent sell-off to $60,000 saw investors yank millions of these spot ETFs.

Broadly speaking, investors still appear confidence about the cryptocurrency’s long-term prospects, as evident from the spot ETFs’ resilient asset under management (AUM).

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According to Checkonchain, the cumulative AUM of the 11 funds has only decreased by about 7% since early October, sliding from 1.37 million BTC to 1.29 million BTC. Bitcoin, meanwhile, is down over 40% since hitting record highs above 126,000 in October.

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Bitcoin, Ethereum, Crypto News & Price Indexes

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Bitcoin, Ethereum, Crypto News & Price Indexes

Ethereum has hit a zone typically associated with mass selling, with an MVRV Z-Score returning a score of -0.42 — though analysts are split on whether the price of Ether is close to bottoming out. 

The MVRV Z-Score is a metric used to assess whether a crypto asset is overvalued or undervalued by comparing its market value to its realized value, which reflects the total value of Ether based on the price at which it was last transacted. 

The metric was created to identify periods of market euphoria or capitulation when market value was considerably higher or lower than realized value.

CryptoQuant analyst and Alphractal founder and CEO, Joao Wedson, said the score “shows that Ethereum is indeed going through a clear capitulation process.”

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However, the analyst said the data “does not compare to the intensity” seen at the major bottoms of the 2018 and 2022 bear markets. 

The lowest value in history was -0.76, recorded in December 2018, said Wedson.

Ether MVRV Z-Score tanks below zero in capitulation. Source: Alphractal 

Further downsides for ETH prices possible

The analyst cautioned that further downsides could be possible before any meaningful recovery. 

“The market is already under stress, but historically, there is still room for further downside before a definitive structural bottom is formed,” he said. 

The price of Ether has fallen 30% over the past fortnight, reaching a bear market low of $1,825 on Friday before a minor recovery to $2,100 on Monday. 

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Related: Tom Lee tips lack of leverage and gold ‘vortex’ for Ether’s 21% slump

HashKey Group senior researcher Tim Sun told Cointelegraph that historically, Ethereum’s MVRV Z-Score “has proven to be a highly reliable indicator for tracking subsequent market shifts, particularly in identifying bottoming zones across multiple cycles.”

“Judging by on-chain activity, protocol evolution, and long-term ecosystem structure, Ethereum’s fundamentals have not seen any substantive deterioration. On the contrary, they continue to improve across several key dimensions,” he said.

However, it is premature to conclude that Ether has finished its bottoming process as long as the primary drivers of the current decline persist, he added.  

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“Given the potential liquidity constraints associated with the upcoming April tax season, the probability of further price downside remains a significant factor.”

One of the best “buy fear” windows for Ether

Other market commentators, such as MN Fund founder Michaël van de Poppe, were a little more optimistic, stating, “I think that this is a tremendous opportunity to be looking at ETH.”

“The core reason for this is that there’s a massive gap to the ‘fair price,’” he said, referring to the MVRV ratio.

Ether is currently as undervalued as it was during the April 2025 crash, the June 2022 bottom after the Terra/Luna collapse, the March 2020 Covid crash, and the December 2018 bear market bottom.

“In all of those cases, this provided a tremendous buying opportunity for this particular asset.”

Andri Fauzan Adziima, research lead at crypto trading platform Bitrue, told Cointelegraph that negative MVRV zones “have repeatedly preceded explosive recoveries in past cycles.”

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“With ETH’s network metrics holding strong, it feels like a prime long-term accumulation setup once the weak hands are fully flushed,” he said. 

“Brutal capitulation now, but historically one of the best ‘buy fear’ windows for ETH.” 

ETH prices have tanked back to long-term cycle lows. Source: TradingView

Magazine: Bitcoin difficulty plunges, Buterin sells off Ethereum: Hodler’s Digest