Tax Evasion Goes Digital: Criminals Shift To Novel Crypto Instruments – Analysts

bitcoinistPubblicato 2026-05-22Pubblicato ultima volta 2026-05-22

Introduzione

Italian police uncovered a tax fraud case worth over $1 million where the suspect used novel Bitcoin-based tools, the Ordinals protocol and BRC-20 token standard, to conceal undeclared capital gains. The individual allegedly created and sold tokens, funneling profits back into a primary Bitcoin wallet in a repeated cycle to avoid tax records. Analysts from Chainalysis note that while tax evasion using cryptocurrency is not new, methods are becoming more creative, with bad actors increasingly turning to NFTs, DeFi, and new token standards. However, a fundamental weakness exists: the blockchain provides a permanent, unchangeable record of all transactions. Blockchain intelligence tools can trace these transactions and link them to individuals, especially when combined with data from exchanges. This case demonstrates that technical novelty does not guarantee anonymity. The tax gap remains a significant issue globally, with studies showing low reporting rates among crypto owners. As new digital assets generate wealth, the discrepancy between on-chain activity and declared income is drawing increased scrutiny from investigators worldwide.

An Italian police unit cracked a tax fraud case worth over a million dollars — and at the center of it was not a secret bank account or a shell company, but Bitcoin inscriptions.

A New Way To Hide Old Money

Italy’s Economic and Financial Police Unit in Foggia uncovered a scheme in which a suspect allegedly used the Bitcoin Ordinals protocol and the BRC-20 token standard to generate and conceal roughly 1 million euros, or about $1.1 million, in undeclared capital gains.

According to blockchain analytics firm Chainalysis, the suspect created tokens using those tools, listed them on marketplaces, sold them for far more than they originally cost, and funneled the profits back into a primary Bitcoin wallet.

The cycle repeated — earnings went straight into new inscriptions, keeping the money moving and off tax records.

Introduced in 2023, the Ordinals protocol works by assigning a serial number to a satoshi, the smallest unit of Bitcoin, and embedding data such as images or text into a Bitcoin transaction. The BRC-20 standard builds on that by letting users deploy, mint, and transfer tokens directly on the Bitcoin blockchain.

Tax Authorities Playing Catch-Up

Tax evasion through crypto is not new. What is changing is how creative the methods are getting. Chainalysis said bad actors are increasingly turning to NFTs, decentralized finance protocols, and emerging token standards in hopes of keeping wealth hidden from authorities. The firm published its findings Wednesday.

BTCUSD now trading at $77,065. Chart: TradingView

Compliance data suggests the problem runs deep. A study released in March found that only 32% to 56% of US crypto owners report their gains to tax authorities. In Norway, that figure dropped to just 12%, based on research published in August 2024.

Meanwhile, the US Internal Revenue Service puts the country’s gross tax gap — the total taxes legally owed but not collected — at around $606 billion.

A Trail That Never Disappears

Despite the technical creativity behind schemes like the one in Italy, Chainalysis said there is a built-in weakness in using crypto to hide money. The blockchain keeps a permanent record of every transaction, and that record cannot be changed or deleted.

The Fatal Flaw Of Crypto Fraud

Blockchain intelligence tools are capable of rebuilding a complete financial network and comparing it with information crypto exchanges are required to disclose, making it possible to trace transactions back to suspected tax cheats. Officials said the Italian case shows that technical novelty does not equal anonymity.

As new types of digital assets continue to appear and generate income, analysts say the gap between actual on-chain wealth and what people declare on their taxes will draw more attention from investigators around the world.

Featured image from Tax Central, chart from TradingView

Domande pertinenti

QWhat novel digital tools were allegedly used by a suspect in Italy to conceal undeclared capital gains?

AThe suspect allegedly used the Bitcoin Ordinals protocol and the BRC-20 token standard to generate and conceal the undeclared capital gains.

QAccording to Chainalysis, what are some of the crypto-based methods increasingly being used by bad actors to hide wealth from tax authorities?

AAccording to Chainalysis, bad actors are increasingly turning to NFTs, decentralized finance protocols, and emerging token standards to hide wealth.

QWhat is the inherent weakness of using crypto to hide money, as highlighted by the article?

AThe inherent weakness is that the blockchain maintains a permanent, unchangeable record of every transaction, creating a traceable trail.

QWhat is the estimated gross tax gap in the United States, as mentioned in the article?

AThe US Internal Revenue Service estimates the country's gross tax gap to be around $606 billion.

QBased on the article's example, what does the Italian tax fraud case demonstrate about technical novelty in crypto?

AThe Italian case demonstrates that technical novelty in crypto does not equal anonymity, and transactions can be traced back to suspects using blockchain intelligence tools.

Letture associate

Seeking Alpha's Hot Article: Why Might the U.S. Stock Market Crash in June?

In a recent Seeking Alpha article, financial professor and analyst Damir Tokic argues that the US stock market may be poised for a significant crash in June 2026. The core thesis centers on a "mega-bubble" in equities, particularly within the technology sector, which has driven the S&P 500 to near-record valuations, with a Shiller P/E ratio exceeding 40—a level comparable to the 2000 dot-com bubble. Tokic identifies two primary catalysts for a potential collapse. First, he points to unsustainable market exuberance fueled by what he terms the "Trump Stimulus"—massive AI capital expenditure by tech giants, which he believes is politically driven and cannot last. Second, and more urgently, he highlights the escalating Iran war as a critical threat. The ongoing closure of the Strait of Hormuz has created a severe global energy supply crunch. Strategic petroleum reserves are projected to hit critically low operational levels by June, potentially causing oil prices to spike above $200 per barrel and triggering a severe, supply-driven inflationary shock. This scenario, Tokic warns, would force the Federal Reserve's hand. Despite currently maintaining a dovish bias, the Fed would likely be compelled to officially pivot to a hawkish stance at its June FOMC meeting to combat soaring inflation and bond yields. He contends that such a shift—or even a failure to act, which would destroy Fed credibility—could be the trigger that punctures the market bubble. The resulting downturn, he concludes, could rival the bear markets of 2000 and 2008, advising investors to prepare for a major correction.

marsbit14 min fa

Seeking Alpha's Hot Article: Why Might the U.S. Stock Market Crash in June?

marsbit14 min fa

AI PC Battle: Bet on the Toll Booth, Not the Camp

**Title:** The AI PC Battle: Don't Bet on Sides, Bet on the Tollbooth **Summary:** The AI PC competition is moving beyond simple "x86 vs. Arm" narratives. The core investment thesis should focus on identifying which players can sustain margins, cash flow, and pricing power throughout the upgrade cycle, rather than backing a particular architecture. The opportunity is analyzed in three layers: 1. **The Advanced Foundry Tollbooth:** TSMC is positioned to collect "tolls" regardless of which chip designer wins, due to its dominant ~70% share in advanced semiconductor manufacturing, which is essential for high-end AI PC chips. 2. **Compute & Platform Spillover:** AMD represents an offensive in the x86 CPU+GPU space, while NVIDIA leverages its GPU and CUDA software stack dominance. Both benefit from the demand for increased local AI compute. 3. **Architecture Diffusion & Turnaround Plays:** ARM and Intel offer potential for significant upside (elasticity), but investments here require stricter discipline due to higher execution risks and competitive challenges. The industry is transitioning from concept to shipment validation. While short-term forecasts for AI PC adoption have been revised down slightly due to tariffs and procurement delays, the long-term trend towards AI becoming a standard PC feature remains intact. The key driver for upgrade cycles will be whether compelling enterprise applications (e.g., privacy-sensitive computing, low-latency inference) emerge beyond consumer-focused features like meeting summarization. Investment strategy should prioritize companies with platform-level advantages and recurring revenue streams. TSMC offers high certainty as the foundational tollbooth. AMD presents a strong offensive play within the established ecosystem. ARM and Intel are higher-risk, higher-potential-reward turnaround bets. The report cautions against chasing short-term hype and emphasizes a disciplined, long-term approach focused on buying ecosystem strength and cash-flow certainty after market enthusiasm subsides. **Key Risks:** Underwhelming AI PC applications slowing upgrade cycles; slow improvement in Windows on Arm compatibility; macro/tariff impacts on PC demand; potential advanced node supply-demand mismatches affecting TSMC; high overall AI sector valuations making stocks vulnerable to a risk-off shift in markets.

marsbit29 min fa

AI PC Battle: Bet on the Toll Booth, Not the Camp

marsbit29 min fa

Ten-Thousand-Word Analysis: From $10 to $290, MRVL Wins the Entire AI Era by 'Not Making GPUs'

Marvell Technology's stock price surged from under $10 in 2016 to a record $290 in June 2026, fueled not by making GPUs, but by dominating AI infrastructure connectivity. This analysis argues the market misvalues MRVL as merely a smaller Broadcom in custom AI chips, overlooking its true, unique position. Marvell's core strength lies in enabling high-speed data flow for AI clusters through three interconnected businesses. First, it holds a commanding ~70% market share in high-speed optical DSPs (essential for data center light modules), a deep-moat business with accelerating growth. Second, its custom AI chip design business serves hyperscalers like AWS, Microsoft, and Google, with a significant revenue pipeline despite lower margins. Third, stable cash flows come from Ethernet switch chips and enterprise storage controllers. Together, they form a full-stack "AI data movement" platform. CEO Matt Murphy's transformative leadership since 2016, involving strategic divestments, key acquisitions (like Inphi for optical DSPs), and securing long-term agreements with major cloud providers, repositioned the company. A pivotal $2 billion strategic investment from NVIDIA in 2026 underscored Marvell's critical role in the AI ecosystem, particularly through collaborations like NVLink Fusion. While Marvell faces risks—including client concentration (losing the Amazon Trainium3 design), lower-margin business mix, competitive threats, insider selling, and complex supply chains—its fundamentals remain strong. The optical interconnect moat is widening with the acquisition of Celestial AI (photonics fabric), and financial metrics show accelerating revenue growth and operating leverage. With a PEG ratio suggesting undervaluation relative to its growth, the thesis is that the market undervalues Marvell's monopolistic position in AI "plumbing" while overemphasizing its competitive custom chip segment. The story transcends investing, symbolizing how in any complex system—from the internet to AI—the value of "connection" ultimately surpasses that of individual "nodes."

marsbit58 min fa

Ten-Thousand-Word Analysis: From $10 to $290, MRVL Wins the Entire AI Era by 'Not Making GPUs'

marsbit58 min fa

AI Relay Stations Spark Heated Debate on Zhihu: Behind Cheap Tokens, What Are Users Really Worried About?

A discussion on Zhihu about "AI relay stations" shifted the niche developer topic of "cheap tokens" into broader user awareness. Users moved beyond simply questioning the legitimacy of these services to focus on practical concerns: Where do cheap tokens truly come from? Is the model being accessed the real one? Can relay stations see prompts, code, and API keys? For occasional users, are the risks worth it? The core debate centered less on price and more on trust. A primary worry is model authenticity—the risk of "model swapping," where users paying for a premium model might be routed to a cheaper one, creating an information asymmetry. Others argued that cost comparisons matter; while cheaper than official pay-as-you-go APIs, relay stations may not be the lowest-cost option versus subscriptions, domestic models, or free tiers, making user needs assessment crucial. Speculation about token sources ranged from legitimate bulk discounts to gray-area methods like account sharing or exploiting regional pricing. This opacity makes risk assessment difficult for users. Data security emerged as a critical concern, especially for enterprise use. When processing sensitive information like code, contracts, or client data, the inability to verify a relay station's data handling, retention, or access policies poses significant compliance and confidentiality risks. The evolving consensus suggests relay stations can be used cautiously for low-sensitivity, disposable tasks (e.g., summarizing public info, simple translation). However, they should not be the default for sensitive, professional, or production workflows involving proprietary data, Agents, or automated systems. Recommendations include avoiding large prepayments, not relying on a single service, using test prompts to monitor quality, anonymizing data where possible, and keeping official channels as backups. Ultimately, the discussion framed tokens not just as a billing unit but as a measure of real cost encompassing price, model integrity, data security, and service stability. The popularity of relay stations highlights user demand for affordable access, but the debate underscores a key trade-off: the savings from cheap tokens may come at the price of trust, transparency, and control over one's data and AI experience.

marsbit1 h fa

AI Relay Stations Spark Heated Debate on Zhihu: Behind Cheap Tokens, What Are Users Really Worried About?

marsbit1 h fa

Trading

Spot
Futures
活动图片