Stablecoin usage in Venezuela likely to keep expanding amid economic instability

cointelegraph2025-12-14 tarihinde yayınlandı2025-12-14 tarihinde güncellendi

Özet

Venezuela's economic instability and hyperinflation are driving increased reliance on stablecoins, particularly USDT, as essential tools for daily transactions and as a store of value. According to TRM Labs, nearly a decade of economic crisis, sanctions, and failing traditional infrastructure has made crypto adoption a necessity. Peer-to-peer platforms and crypto-to-fiat conversions are critical in a low-banking environment, with over 38% of Venezuelan crypto site visits going to a major P2P service. Despite regulatory uncertainty, stablecoins are primarily used for payroll, remittances, and commerce rather than speculation. Venezuela ranks 9th globally in crypto adoption when adjusted for population size.

Venezuelans are already heavily reliant on blockchain technology for banking after suffering through a decade of economic pressures; however, usage is likely to keep growing if conditions worsen in the South American country, blockchain intelligence firm TRM Labs says.

As regional and geopolitical tensions continue to rise, driven in part by US-Venezuela tensions, the TRM Labs team predicted in a report on Thursday that macroeconomic instability and the bolívar’s continued devaluation will likely sustain demand for stablecoins as both a store of value and a medium of exchange.

At the same time, regulatory ambiguity and continued uncertainty surrounding the country’s crypto regulator, SUNACRIP’s, authority and enforcement capacity, and eroding trust in traditional banking infrastructure could prolong the population’s dependence and drive more usage.

“Absent a material shift in Venezuela’s macroeconomic conditions or the emergence of cohesive regulatory oversight, the role of digital assets — particularly stablecoins — is poised to expand.”
Source: TRM Labs

Venezuela is 18th globally for crypto adoption, the Chainalysis 2025 Crypto Adoption Index report found, but its rank increased to 9th when adjusted for population size.

Peer-to-peer transactions a key service for Venezuelans

Peer-to-peer (P2P), transfers made from one person to another through an intermediary, along with USDT (USDT) to-fiat conversions, have emerged as key services Venezuelans are using in the absence of reliable domestic banking channels, according to TRM Labs.

The blockchain intelligence firm tracked Venezuelan IP addresses and found that more than 38% of site visits were to a lone global platform that offers P2P trading functionality, which underscores its “role in facilitating crypto access in Venezuela’s low-banking environment.”

“A significant share of crypto-to-fiat activity is facilitated through platforms supporting informal settlement rails — even amid reports of intermittent service disruptions.”

Related: Venezuela blocks Binance, X amid presidential election dispute

“Local platforms also play a key role, particularly those offering mobile wallets and bank integrations suited to domestic users,” the team added.

Venezuela’s crypto industry created out of desperate necessity

Venezuela’s crypto ecosystem is ultimately the product of nearly a decade of economic collapse, international sanctions pressure, and state experimentation with digital financial alternatives, the TRM Labs team said.

Stablecoins, especially USDT, play a central role in household and commercial transactions in Venezuela, and despite compliance and sanction evasion concerns, stablecoins remain “overwhelmingly driven by necessity rather than speculation or criminal intent.”

“For most Venezuelans, stablecoins now operate as a substitute for retail banking — facilitating payroll, family remittances, vendor payments, and cross-border purchases in the absence of consistent domestic financial services.”

Magazine: Quantum attacking Bitcoin would be a waste of time: Kevin O’Leary

İlgili Okumalar

From South Korea to the United States: Blue-Collar Jobs Are Becoming Increasingly Popular, Thanks to AI

AI is reshaping the labor market's value proposition. The traditional four-year college degree is losing its appeal as a guaranteed career path, while skilled blue-collar trades like electricians, welders, and plumbers are experiencing historic demand and wage premiums. This shift is driven by dual pressures: AI's displacement of certain white-collar roles and a booming need for physical infrastructure and data center construction. Data confirms the trend. In the U.S., vocational school revenue surged, and a significant portion of recent layoffs are AI-related. Surveys show a majority of Gen Z adults plan to pursue blue-collar work, citing better job security against AI automation. Vocational education interest has exploded recently. Experts cite a psychological shift as younger generations seek tangible, AI-resistant careers and avoid high student debt. In many cases, salaries for skilled trades now match or exceed those requiring a bachelor's degree. In South Korea, semiconductor vocational high schools boast near-total employment, with graduates securing high-paying roles at companies like Samsung. The shortage is structural, exacerbated by a retiring baby boomer workforce and massive infrastructure projects. Companies like JPMorgan Chase, Meta, and Lowe's are investing heavily in training programs. However, overcoming historical stigma and a "perception gap" around trade careers remains a key challenge to closing the talent gap.

marsbit1 saat önce

From South Korea to the United States: Blue-Collar Jobs Are Becoming Increasingly Popular, Thanks to AI

marsbit1 saat önce

Qualcomm: AI Hype Subsides, When Will Smartphones Emerge from the Gloom?

Qualcomm reported its Q3 FY2026 results (ending June 2026), with revenue of $9.95B, down 4% YoY but above expectations. Gross margin declined to 53.1%, pressured by rising costs across manufacturing and memory. Key business segments showed mixed performance: Handset revenue fell 19.6% YoY to $5.09B, dragged by an 11% decline in non-Apple Android shipments and weaker high-end mix. Conversely, Automotive revenue surged 61% to $1.59B, and IoT grew 9% to $1.83B. Core operating profit dropped 41% YoY due to margin compression and higher expenses. Management's Q4 FY2026 guidance projects revenue of $9.7B-$10.5B, in line with consensus, but Non-GAAP EPS guidance of $2.05-$2.25 fell short of expectations. Amidst persistent weakness in its core handset market, Qualcomm is pursuing growth in AI, focusing on Edge AI (smartphones, PCs, automotive) and Data Center AI. Its data center strategy includes four pillars: AI accelerators (e.g., AI200), commercial CPUs (Dragonfly C1000), custom silicon, and connectivity solutions. While these initiatives initially boosted its stock, concerns over AI capital expenditure sustainability have since erased those gains. The company targets $5B in data center revenue for FY2027 and $15B for FY2029. The report concludes that with the traditional handset business still under pressure, the data center opportunity is currently viewed as a longer-term option, and a more conservative valuation based on core operations may be warranted until AI contributions materialize.

marsbit1 saat önce

Qualcomm: AI Hype Subsides, When Will Smartphones Emerge from the Gloom?

marsbit1 saat önce

From TPU to Self-Evolving Agents: How Jeff Dean Predicts the Next Step in AI

At the 2026 YC Startup School, Jeff Dean outlined his vision for AI's next phase, shifting focus from simply scaling models to building intelligent, autonomous systems. He believes AI's progress is no longer just about creating smarter models, but about integrating them into systems capable of long-term, iterative work, automated experimentation, and continuous learning. This evolution moves the competition from "who has the bigger model" to "who can best organize intelligence." Dean suggests AI capabilities are now comparable to a junior engineer, enabling the automation of complex workflows. However, the true challenge and opportunity lie in managing these AI "workers" at scale. He emphasizes the importance of **context engineering**—structuring tools, memory, and feedback loops—over raw model power. For startups, this means building deep expertise in niche domains where general models currently fail (near 0-1% success rates), leveraging proprietary data, specialized tools, and domain-specific evaluators. A recurring theme is re-examining fundamental constraints. Dean's past work, like moving Google's search index to memory or creating the TPU, stemmed from questioning outdated assumptions about hardware and cost. He sees similar inflection points today, particularly in **specialized inference hardware** to drastically reduce latency and energy consumption for real-time Agent operation. Notably, he points out that in modern AI systems, the dominant cost is often not computation but **data movement**. Reliable, long-running Agents require robust system design, borrowing concepts from distributed computing like checkpointing, state management, and parallel exploration to handle failures and maintain progress over days or weeks. As AI automates execution, the scarcest human skills will shift to **defining clear specifications**, **judging what problems are worth solving** (taste), and designing effective feedback loops. Ultimately, Dean's framework prioritizes understanding the problem deeply, identifying the true bottlenecks, and systematically building closed-loop systems where AI can not only perform tasks but also improve AI itself.

marsbit1 saat önce

From TPU to Self-Evolving Agents: How Jeff Dean Predicts the Next Step in AI

marsbit1 saat önce

İşlemler

Spot
活动图片