Stablecoins See Largest Conversion Spreads In Africa, Research Shows

bitcoinistОпубликовано 2026-02-12Обновлено 2026-02-12

Введение

Research from Borderless.xyz reveals that Africa has the highest median conversion spreads for stablecoin-to-fiat transactions globally, reaching nearly 300 basis points (3%) in January. This is significantly higher than Latin America's 1.3% and Asia's 0.07%. Within Africa, costs vary widely; South Africa has a low rate of 1.5% due to competition, while Botswana and Congo saw spreads exceeding 19% and 13%, respectively. The high costs are attributed to local market structure and lack of liquidity rather than blockchain technology. While stablecoins offer potential for cheaper remittances, the final conversion cost depends heavily on local competition and infrastructure, limiting savings in many African corridors.

Africa’s promise of cheaper remittances via stablecoins is clashing with reality in many places. According to data from Borderless.xyz, January’s median spread for stablecoin-to-fiat conversions across Africa reached nearly 300 basis points — about 3% — far higher than Latin America’s roughly 1.3% and Asia’s tiny 0.07%. That gap matters. It hits wallets where people send money home.

Conversion Costs Vary By Market

Reports note huge differences inside the continent. South Africa showed one of the lowest conversion costs at about 1.5%, where several providers compete and markets have deeper liquidity.

At the other extreme, Botswana’s median spread climbed to almost 19.4% in January, although pricing eased later that month. Congo also saw conversion levels above 13%. The dataset covered 66 currency corridors and nearly 94,000 rate observations, so these are not isolated blips.

Average regional spreads for stablecoin transactions. Source: Borderless.xyz

Competition And Liquidity Shape Rates

The numbers point to a simple takeaway: who sits between the stablecoin and the local cash matters. Where multiple payment providers operate, conversion costs generally sit between about 1.5% and 4%.

Where a single outfit dominates, spreads can top 13%. The “spread” here is the gap between what a provider will buy and sell a stablecoin for — like a bid-ask gap in traditional markets — and it is the execution cost a sender ultimately pays.

Based on reports, it appears these frictions come from local market structure and liquidity more than from the underlying blockchain tech.

Table shows mid-market stablecoin rates, local Tradfi rates, and the resulting BPS premium per currency. Source: Borderless.xyz

Stablecoins Compared With Traditional FX

Borderless.xyz also measured how stablecoin mid-rates stack up against interbank FX mid-market rates, a metric the company calls the TradFi premium.

Across 33 currencies globally, the median difference was about five basis points, or 0.05%, meaning stablecoins and traditional mid-market rates were largely aligned in many places.

In Africa, however, the median gap widened to close to 120 basis points, or about 1.2%. That larger premium helps explain why stablecoins do not automatically translate into big savings for every corridor.

BTCUSD trading at $67,018 on the 24-hour chart: TradingView

What This Means For Senders And Markets

Economists say stablecoins are cutting remittance costs in Africa, noting that legacy services often charge around $6 for every $100 sent.

The recent data adds nuance: faster settlement and lower fees are possible, but only when local on-ramps and off-ramps work well. For consumers, that means potential savings in some corridors and frustratingly high costs in others.

For regulators and market entrants, the signal is clear — boosting competition and liquidity at the local level is as important as improving cross-border rails.

Stablecoins have opened a route that can be cheaper and quicker. Yet in practice, the last mile — turning crypto into local money — still depends on local players, pricing models, and market depth.

Featured image from andBeyond, chart from TradingView

Связанные с этим вопросы

QWhich continent has the highest median spread for stablecoin-to-fiat conversions according to the research?

AAfrica has the highest median spread for stablecoin-to-fiat conversions at nearly 300 basis points (about 3%), which is far higher than Latin America's 1.3% and Asia's 0.07%.

QWhat factors are identified as the primary drivers of high conversion costs for stablecoins in certain African countries?

AThe primary drivers are local market structure and liquidity. High conversion costs occur where a single payment provider dominates, leading to spreads that can top 13%, whereas areas with multiple competing providers see lower costs between 1.5% and 4%.

QHow does the median TradFi premium for stablecoins in Africa compare to the global median?

AThe median TradFi premium in Africa is about 120 basis points (1.2%), which is significantly wider than the global median of approximately 5 basis points (0.05%).

QWhat was the median spread for stablecoin conversions in Botswana in January, according to the report?

ABotswana's median spread for stablecoin conversions climbed to almost 19.4% in January, although the pricing eased later that month.

QWhy don't stablecoins automatically translate into big savings for every remittance corridor despite their potential?

AStablecoins do not automatically translate into big savings because the final cost depends on the efficiency of local on-ramps and off-ramps. High spreads charged by local providers, due to lack of competition and liquidity, can erase the potential benefits of faster settlement and lower base fees.

Похожее

Near Returns to the AI Stage: Transformation into a Public Chain Due to 'Payroll Difficulties,' Agent and Privacy Emerge as New Growth Narratives

NEAR Returns to AI Origins: From Payroll Struggles to Blockchain, Now Focusing on AI Agents and Privacy NEAR Protocol's journey began not with grand blockchain ambitions, but from a practical hurdle: its AI startup founders, including Transformer paper co-author Illia Polosukhin, couldn't efficiently pay international developers in 2017. This led them to pivot and build a high-performance, scalable blockchain. After years navigating various crypto narratives like sharding and cross-chain interoperability, NEAR is now leveraging its AI roots to re-enter the AI arena. A key driver is its "NEAR Intents" layer, which abstracts complex cross-chain transactions. Users simply state their goal (e.g., swap BTC for ETH), and a solver network finds the optimal route. This system has processed over $20B in cross-chain volume, generating significant fee revenue. A major growth area is private transactions via "Confidential Intents/Swaps," which hide trade details until settlement to protect against MEV and front-running. Remarkably, private swaps recently accounted for over 40% of NEAR's transaction volume, highlighting strong demand but also potential regulatory scrutiny. With its AI-founder pedigree, NEAR is positioning itself at the intersection of blockchain, AI agents, and privacy, aiming to become infrastructure for the emerging agent economy while navigating the challenges of its rapid adoption.

marsbit2 ч. назад

Near Returns to the AI Stage: Transformation into a Public Chain Due to 'Payroll Difficulties,' Agent and Privacy Emerge as New Growth Narratives

marsbit2 ч. назад

From Ethereum to AI's 'CROPS': What Exactly is This Set of 'Slow Variables' That Vitalik Repeatedly Emphasizes?

In recent discussions, Vitalik Buterin has frequently emphasized the concept of "CROPS," a framework defining core values for Ethereum's development. CROPS stands for Censorship Resistance, Capture Resistance, Open Source, Privacy, and Security. Initially outlined in the Ethereum Foundation's "EF Mandate," it represents a commitment to user sovereignty, ensuring that the network resists external control, remains open, protects privacy, and prioritizes security. The relevance of CROPS extends beyond Ethereum's foundational principles, becoming crucial in the context of AI integration. As AI agents begin handling wallet operations and automated transactions, the risk increases that users may cede control over their digital assets, privacy, and intentions to centralized AI service providers. A "CROPS AI" would therefore emphasize local execution where possible, privacy-preserving remote model calls (e.g., using zero-knowledge proofs), and transparent, verifiable processes to maintain user agency. Vitalik highlights a significant convergence between "CROPS Ethereum access layer" and "CROPS AI." Both address the same fundamental challenge: how users can access powerful services—be it blockchain data via RPCs or AI models—without exposing sensitive information or relinquishing ultimate control. This intersection points toward a future digital entry point that is more private, secure, and user-controlled. Ultimately, CROPS is not merely an abstract ideal but a practical guidepost. It steers development—from protocol resilience and wallet design to AI agent safety—towards a future where users retain self-sovereignty even as digital systems grow more complex and powerful. In an era of accelerating AI adoption, these "slow variables" of censorship resistance, openness, privacy, and security may define Ethereum's enduring value.

marsbit2 ч. назад

From Ethereum to AI's 'CROPS': What Exactly is This Set of 'Slow Variables' That Vitalik Repeatedly Emphasizes?

marsbit2 ч. назад

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

Silicon Valley investor and "Godfather of Startups" Steve Hoffman warns that combining Web3 with AI is likely a trap, not a promising venture. In an interview, Hoffman argues that while AI is a foundational technology touching all industries, Web3 adds complexity, friction, and regulatory risk without solving mainstream consumer or business needs. He advises founders to focus on deep, specialized applications where startups can out-iterate giants, rather than on generic features easily replicated by large tech companies. Hoffman observes that Silicon Valley will lead foundational AI research, while China excels at rapid, large-scale application and commercialization, particularly in robotics. He stresses that AI-driven autonomous agents capable of collaborative, multi-step tasks are 2-4 years away, which will cause significant job displacement. The solution is not to slow AI but to redesign business models around human-AI collaboration and reform social systems like education and retraining. For startups, Hoffman recommends focusing on vertical, expertise-heavy domains to build defensibility. He sees major opportunities in AI fraud detection and cybersecurity. Key founder mindsets include systemic thinking over feature-focus, relentless customer centricity, building adaptive teams, and deeply understanding AI's capabilities and limits. Hoffman is also leading a non-profit initiative to establish university centers aimed at training future leaders in responsible, human-value-aligned AI innovation.

marsbit4 ч. назад

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

marsbit4 ч. назад

Token Inefficient, Economy Tokenless

The article "Tokens Aren't Economical, Economics Aren't Tokenized" analyzes a pivotal shift in the AI industry from a technology-driven narrative to one dominated by capital efficiency. It highlights two concurrent trends: a severe capital shortage due to the exorbitant and recurring costs of compute (e.g., OpenAI's high burn rate) and a wave of corporate spin-offs where major tech companies are separating their AI units (like Kuaishou's Kling and Baidu's Kunlunxin). The core argument is that AI's "anti-internet" business model, where user growth increases costs rather than profits, has created a disconnect between high valuations and actual cash flow. Spin-offs address this by allowing AI assets to be valued independently. Within a parent company, they are seen as cost centers, but as standalone entities, they are priced based on their growth potential and scarcity in the primary market, leading to massive valuation premiums (e.g., Kling's estimated value tripling post-spin-off). The industry is at an inflection point, moving from "model worship" to "value realization." The competition is evolving from a pure compute (GPU) race to a broader focus on systemic efficiency and full-stack engineering (involving CPUs and orchestration) to achieve viable commercialization. The year 2026 is framed as a critical moment where the industry must definitively answer how to economically translate AI capability into tangible business value, reshaping the sector's future power structure.

marsbit4 ч. назад

Token Inefficient, Economy Tokenless

marsbit4 ч. назад

Торговля

Спот
Фьючерсы
活动图片