Crypto World
Binance launches AI trading skills with unified agent interface
Binance debuts seven AI Agent Skills to automate trading, data, and risk workflows.
Summary
- Binance rolled out seven AI Agent Skills to connect spot, wallet, and trading via a unified interface, adding OCO, OPO, and OTOCO support and on-chain analytics tools.
- The skills include real-time market rankings, smart money signal tracking, and contract risk detection, signaling a push toward agent-based execution across Binance’s retail and institutional user base.
- Major AI-linked and exchange tokens saw modest intraday gains, with BTC and ETH trading slightly higher as markets priced in incremental automation demand and on-chain activity growth.
Binance has introduced its first batch of seven AI Agent Skills, creating a unified interface that lets AI agents access spot trading, wallet data, and execution tools in one environment. The rollout adds a programmable layer over Binance’s existing infrastructure, allowing automated systems to query real-time market data, execute complex order types, and analyze token and address information without manual intervention. Positioned at the intersection of exchange infrastructure and AI-driven trading, the update underscores how centralized venues are racing to become the execution backbone for agentic trading strategies.
The new skills package is built around several core capabilities designed to remove friction between data, decision-making, and order placement. First, agents can pull live market data, including order book information, price feeds, and ranking tables that surface top-performing or highly traded assets across the platform. Second, execution is no longer limited to simple market or limit orders, with the interface now supporting OCO (one-cancels-the-other), OPO (one-procures-the-other), and OTOCO (one-triggers-one-cancels-the-other) structures that let agents predefine conditional strategies and risk parameters. Third, the skills extend into on-chain style analytics by offering address and token information analysis, smart money signal tracking, and contract risk detection, effectively merging elements usually associated with specialized analytics platforms into the exchange stack.
From a user perspective, the combination of real-time queries and executable logic means agent developers can script entire trading or portfolio workflows without building their own exchange connectivity stack. A single AI agent can, for example, scan market rankings for volume spikes, cross-reference smart money flows into specific contracts, evaluate basic risk flags, and then place a staged OCO or OTOCO order structure to manage entries and exits. This architecture supports both high-frequency style reaction to fast-moving events and more measured swing-trading strategies based on aggregated analytics. It also lowers the barrier to deploying semi-autonomous bots for retail traders who rely on third-party tools, while institutional desks can integrate the interface into existing infrastructure for more systematic strategies.
The inclusion of smart money signal tracking and contract risk detection moves Binance further into territory historically occupied by standalone on-chain intelligence firms. By exposing these capabilities as skills accessible to AI agents, the exchange can keep users within its own ecosystem rather than sending them to external dashboards for early flow or risk signals. In practice, this might involve an agent continuously scanning for large or repeated flows from tagged sophisticated wallets into a new token, then testing the associated contract for typical red flags such as trading restrictions, mint functions, or ownership concentration before any capital is deployed. The same workflow could be used defensively, with agents watching for sudden outflows or changes in contract behavior that may warrant tightening stops or closing positions.
For risk management, the advanced order types paired with contract scanning provide a more granular toolkit than many retail users previously applied. OCO and OTOCO structures, in particular, let agents define both upside targets and downside protection in a single conditional chain, minimizing the chance that human users forget to place stops or exits in volatile markets. Combined with wallet data access, an agent can check free balances, open orders, and portfolio concentration before committing to a new position, effectively running a pre-trade risk check similar to what regulated brokers and prime services offer. This mirrors how larger trading desks aggregate risk views across instruments and venues, but compresses it into a single programmable endpoint for Binance-specific activity.
AI Agent Skills could prove particularly relevant for quant funds, market makers, and structured product issuers that already deploy systematic strategies across major venues. Rather than building and maintaining multiple bespoke integrations, these firms can use the unified interface to embed agent-driven logic on top of Binance liquidity, while still routing orders through their own risk frameworks. For smaller professional traders, the ability to script and test strategies around conditional orders and smart money flows offers a scaled-down version of institutional tooling without large engineering budgets. Over time, if volumes routed through AI agents grow, liquidity dynamics on pairs like BTC and ETH could increasingly reflect the behavior of automated strategies rather than discretionary traders.
On the retail side, the launch adds another layer to the ongoing trend of exchanges offering more out-of-the-box automation. Previously, many users relied on external bots or third-party platforms to implement grid trading, DCA strategies, or volatility breakout systems; now, those logic blocks can be coded into agents that sit directly on top of the exchange’s infrastructure. This reduces latency, simplifies custody questions, and potentially improves execution quality, but it also raises questions about over-reliance on automated tools among less experienced traders. Education around how conditional orders work and how risk flags are generated will be critical, especially during periods of elevated volatility in assets such as BTC and ETH.
The broader competitive landscape among exchanges is shifting toward AI and automation as differentiators, with multiple platforms experimenting with GPT-style assistants, strategy builders, and one-click bot marketplaces. Binance’s move to expose agent skills at the infrastructure layer rather than as a purely consumer-facing chatbot suggests it intends to anchor itself as a base layer for third-party AI trading tools. That approach mirrors how some exchanges integrated with payment networks like Visa to capture transactional flows, but here the target is the emerging wave of agentic capital allocation tools. If other major players such as Coinbase adopt similar unified interfaces, interoperability and standardization of agent APIs could become a new battleground alongside fees and listing quality.
Market reaction to the announcement has so far been measured rather than euphoric, reflecting a market that increasingly prices AI narratives with more scrutiny. Exchange-native tokens and AI-linked assets posted modest gains on the day, while major benchmarks like BTC and ETH traded within recent ranges, indicating that participants view the launch as an incremental infrastructure upgrade rather than a cycle-defining catalyst. Still, on-chain activity metrics, derivatives positioning, and spot volumes will be important to watch in the coming weeks to gauge whether agent-driven strategies begin to leave a detectable footprint in flows and volatility regimes. For ecosystems like SOL, where on-chain order books and DeFi venues already support sophisticated trading, the race will be to match or exceed the usability and reach of centralized AI tooling, or risk losing trader mindshare to exchange-centric agent hubs.
A Bitcoin Policy Institute study delves into how artificial intelligence models choose among money forms in a variety of hypothetical scenarios, revealing a strong inclination toward Bitcoin and digital money over fiat in most cases. The research tested 36 models across six providers and generated more than 9,000 responses across a spectrum of monetary tasks, from long-term value preservation to everyday payments. The findings show Bitcoin outpacing stablecoins in many contexts, while stablecoins regain sway in transactional use cases like micropayments and cross-border transfers. The study’s authors emphasize that the results reflect training data patterns and framing rather than widespread real-world adoption, but they nonetheless offer a unique lens on how AI interprets money in a digital era, with results released via MoneyForAI.org.
Key takeaways
- 36 AI models across six providers produced 9,072 responses to monetary scenarios; Bitcoin was selected in 48.3% of cases, the most-used instrument overall.
- When asked to preserve purchasing power over multi-year horizons, 79.1% of responses favored Bitcoin, the study’s most lopsided result.
- In payments, micropayments, and cross-border transfers, stablecoins were chosen 53.2% of the time versus 36% for Bitcoin, highlighting a transactional edge for stablecoins in certain contexts.
- Nearly 91% of responses preferred digitally native instruments (including Bitcoin or other digital assets) over fiat, with zero models rating fiat as their top choice.
- Model-provider differences emerged: Anthropic models averaged 68% BTC preference; OpenAI 26%; Google 43%; and xAI 39%, illustrating how training data shapes outputs rather than deterministic financial forecasting.
Tickers mentioned: $BTC
Market context: The study arrives amid ongoing experimentation with digital money in AI-assisted scenarios, underscoring how institutional and research communities are evaluating Bitcoin’s role as a borderless, programmable asset alongside stablecoins and other digital instruments.
What to watch next – The Bitcoin Policy Institute plans to broaden the model set and providers, test different prompt framings, and explore additional monetary scenarios to validate whether these preferences hold under varied conditions.
Why it matters
For users and investors, the findings offer a nuanced view of how AI systems—trained on vast data corpora—perceive money forms in a digital economy. The recurring tilt toward Bitcoin in long-horizon scenarios reinforces Bitcoin’s narrative as a non-sovereign store of value that can operate independently of any single country’s monetary policy. Yet the study also highlights practical reasons stablecoins remain appealing for transactions: near-instant settlement, compatibility with existing payment rails, and the ability to freeze or limit access in certain jurisdictions, which some participants see as a drawback for a universally accessible currency. The methodological caveats matter for interpretation: the results reflect synthetic prompts and model training data rather than current market adoption or consumer behavior.
From a development perspective, the research underscores how AI agents—when asked to optimize for efficiency or resilience in simulated economies—tend to converge on a small set of digital money forms. This convergence could inform the design of wallet interfaces, AI-driven financial planning tools, and cyber-physical systems that rely on digital value transfers. It also raises policy questions about the role of programmable money in cross-border ecosystems and how guardians of financial stability might respond to AI-generated preferences that favor digital currencies in abstract decision environments. In other words, the study is less about predicting the next price move and more about understanding how AI framing shapes perceptions of what “money” should look like in a digitized world.
The research also points to distinct differences across AI families. Anthropic models leaned most toward Bitcoin, while other providers displayed broader variance. These disparities remind readers that the results are contingent on the models’ training data and internal prompts rather than a universal forecast for asset demand. While some may interpret the Bitcoin bias as an endorsement of BTC in all contexts, the authors are careful to emphasize that the observed preferences do not translate directly into real-world adoption or policy outcomes. They describe the results as patterns emerging from the interplay between model design and the digital money landscape rather than a prescriptive verdict on fiat, stablecoins, or Bitcoin itself.
What to watch next
- Expanded model coverage: expect the BPI to include more AI models and more providers to test whether the BTC preference persists across the broader AI ecosystem.
- Framing sensitivity: researchers will experiment with alternative prompts to determine how wording and context influence outcomes.
- Broader scenarios: additional situations—such as storing earnings across multiple countries and complex settlement schemes—could further illuminate how AI perceives money in varied environments.
- Implications for tooling: developers building AI-assisted financial tools may use these insights to shape asset-selection features and risk disclosures in simulated environments.
Sources & verification
Bitcoin’s role in AI-driven monetary tests: what the study reveals
Bitcoin (CRYPTO: BTC) emerged as the leading instrument across the majority of prompts, appearing in 48.3% of the 9,072 responses generated by 36 models across six providers, according to the Bitcoin Policy Institute’s report released on MoneyForAI.org. The exercise probed a range of economic scenarios—from preserving purchasing power over years to everyday payments—testing how AI agents allocate value across money forms. The result is a strong tilt toward digital money, particularly Bitcoin, as the substrate for economic activity that can function across borders and regulatory regimes.
In long-horizon scenarios, the study found 79.1% of AI responses favored Bitcoin, marking the most pronounced bias in any tested category. This constellation of results suggests that, when asked to optimize for durability and sovereignty, AI agents consistently gravitate toward assets that retain value independently of any single country’s monetary policy. The digital-money axis appears to be the most favored frame for multi-year planning within the tested prompts, hinting at how future AI tools might simulate or advise on wealth preservation in a world where fiat policies are volatile or opaque.
Conversely, when the focus shifts to payments and transactions—whether micropayments or cross-border transfers—stablecoins win a higher share: 53.2% of responses favored stablecoins, while Bitcoin attracted 36%. The transactional efficiency and network familiarity of stablecoins explain their appeal in these contexts, where rapid settlement and compatibility with existing systems can matter as much as asset selection in a simulated environment. A prominent industry observer noted that stablecoins’ ability to be frozen is a double-edged sword: it provides control in certain regulatory settings but removes a layer of confidence for users seeking an uninterrupted transfer capability. Jeff Park, the chief investment officer at Bitwise, framed the context succinctly: the “most obvious explanation” for stablecoins’ relative performance in these scenarios is the ability to freeze, whereas Bitcoin cannot be frozen, offering a durable trust anchor in a digital suite of tools.
Across all responses, the AI agents favored digitally native instruments—Bitcoin, stablecoins, altcoins, tokenized real-world assets, or compute units—over fiat in roughly 91% of cases. The study’s authors emphasize that fiat relevance did not appear as a top overall choice in any of the 36 models tested. They caution readers that these results reflect patterns in training data and prompt design more than real-world adoption patterns. In other words, the study captures how AI systems interpret monetary constructs when asked to optimize for hypothetical outcomes, rather than a forecast of consumer behavior or regulatory impact.
The analysis also reveals notable differences among model families. Anthropic models averaged a Bitcoin preference of 68%, with OpenAI at 26%, Google at 43%, and xAI at 39%. These numbers illustrate how distinctive training corpora and prompt engineering shape outputs, reinforcing the study’s central caveat: responses are indicative of data patterns rather than prescriptive predictions about the future of money. The researchers acknowledge that the prompt framing used in several scenarios may have steered results toward certain instruments, and they plan to explore alternative framings in future work to measure sensitivity and robustness of the observed preferences. Aside from the methodological note, the study contributes to a growing discourse about how AI agents conceptualize money in a highly digitized financial landscape, where fiat, stablecoins, and digital assets coexist in a rapidly evolving ecosystem.
TLDR
- American Bitcoin purchased 11,298 ASIC miners to expand its bitcoin mining operations.
- The new equipment will increase the company’s total mining capacity by about 12%.
- The miners will add approximately 3.05 exahashes per second to the company’s hashrate.
- American Bitcoin will deploy the machines at its Drumheller site in Alberta in March 2026.
- The company’s total owned fleet will grow to 89,242 miners with 28.1 EH per second of capacity.
American Bitcoin confirmed the purchase of 11,298 ASIC miners to expand its bitcoin mining operations. The company said the new equipment will increase total capacity by about 12%. The machines will deploy at its Drumheller, Alberta, site in March 2026.
American Bitcoin Expands Fleet With 11,298 New Miners
American Bitcoin said the purchase will add about 3.05 exahashes per second of capacity. The miners will operate at an efficiency of 13.5 joules per terahash. As a result, the company’s total owned fleet will reach 89,242 units. The combined capacity will represent about 28.1 EH/s at an average efficiency of 16 J/TH.
The company stated that the equipment will arrive and be deployed in March 2026. Once installation finishes, the operational fleet will include 58,999 active miners. These machines will run at about 25 EH/s with an efficiency of 14.1 J/TH. Based on current network data, the added capacity equals about 0.3% of global hashrate. That share could produce about 42 bitcoin each month, or roughly 515 bitcoin each year.
Operational Strategy and Bitcoin Holdings
Eric Trump, co-founder and chief strategy officer, outlined the company’s focus. He said, “As bitcoin matures, the priority is clear: grow American-owned, professionally operated hashrate.” He added that this strategy will protect the network and support innovation in the United States.
Matt Prusak, president of American Bitcoin, described the firm’s mining approach. He said, “Every decision we make is oriented around maximizing Bitcoin accumulation.” The company reported that it mined bitcoin at a 53% discount to spot prices in the fourth quarter of 2025. During that period, bitcoin reached an all-time high above $126,000 in early October.
By year-end 2025, the firm reported revenue of $185.2 million. It posted a net loss of $153.2 million. The loss stemmed mainly from an unrealized $227.1 million loss on bitcoin holdings under fair value rules. The company closed the year with 5,401 bitcoin on its balance sheet.
American Bitcoin later reported holding 6,039 bitcoin valued at nearly $402 million. The company also posted a quarterly loss of $59.45 million. At recent prices near $68,000 per bitcoin, the projected annual output could generate about $35 million in gross revenue before costs.
Shares of American Bitcoin traded lower on Tuesday. The stock declined about 2.6% to $0.99 during trading. In later trading, the shares fell nearly 6% to below $0.96. Over the past month, the stock has dropped nearly 29%.
David Bailey, a former crypto advisor to the Trump administration, argues that the US government could be doing more to support Bitcoin adoption.
“At the end of the day, liking Bitcoin is not enough,” Bailey said during the Bitcoin Investor Week Conference in New York, which was published to YouTube on Tuesday.
“The Trump administration was a very important first step, but you know there is so much further for us to go and not just in talk but in actual delivery,” said Bailey, who now serves as CEO and Chairman of KindlyMD, a Bitcoin treasury company.
Bailey points to stalled Strategic Bitcoin Reserve plan
Trump repeatedly voiced his support for Bitcoin (BTC) and the broader crypto industry during his presidential campaign appearances.
While he signed an executive order for a Strategic Bitcoin Reserve in March 2025, it is understood that the US government has yet to begin accumulating Bitcoin outside of the funds seized through illicit activity.
“We’re sitting here a year later, the Strategic Bitcoin Reserve was signed into an executive order,” Bailey said.
“Last time I checked, we don’t even know how much Bitcoin we have exactly,” Bailey added. Data from Arkham Research shows it currently holds 378,372 Bitcoin, worth approximately $22.48 billion at the time of publication.
Just two months after Trump signed the executive order, White House AI and crypto czar David Sacks said the process of accumulating wouldn’t be so straightforward, explaining that the US could buy more Bitcoin if the government could fund the purchase in a “budget-neutral” way, without a tax or adding to the growing national debt.
Industry participants became more divided on the possibility as the year progressed. Some stayed optimistic. Galaxy Digital’s head of firmwide research, Alex Thorn, said in September that there was a “strong chance” it would still happen before the end of 2025.
Bailey said that while Trump has been the first politician to champion “our worldview,” an opinion alone isn’t enough to drive Bitcoin’s price to $1 million.
“Just because you like Bitcoin doesn’t mean that you’ve invested the political capital necessary for things to happen,” Bailey said.
“Unless you’re willing to bear the political capital necessary to mobilize the different gears necessary to move the ball forward, then at the end of the day, you can like Bitcoin, you cannot like Bitcoin, you’re going to get the same outcome achieved.”
Bitcoin will succeed either way, says Bailey
However, even without action from the US government, Bailey said Bitcoin will eventually succeed. “It’s not like we need the government to cater for us for Bitcoin to be successful,” Bailey said.
“Whether it’s four years from now, or 10 years from now, or 20 years from now, we will get to the point where we actually have a government that is conducive to the rules we need for Bitcoin to be successful,” he said.
Related: Bitcoin futures demand falls to 2024 lows: Are institutions exiting the market?
“I’m bullish on what we can accomplish in this administration. If we really want the progress to continue, we need more people to own Bitcoin every year,” Bailey said.
“We need more voters to own Bitcoin every year. And then it is just inevitable,” he added.
Bitcoin is currently trading at $68,220, approximately 45% below its October all-time high of $126,000, according to CoinMarketCap.
Outside the Strategic Bitcoin Reserve, Bitcoiners are eyeing the potential passage of the US CLARITY Act, which aims to provide the industry with more regulatory clarity. Trump said in a Truth Social post on Tuesday that “the U.S. needs to get Market Structure done, ASAP.”
Magazine: Would Bitcoin really be at $200K if not for Jane Street? Trade Secrets
Bettors have long been able to speculate on the chance of a nuclear weapon detonating on Polymarket, but the current conflict with Iran – and scrutiny about insiders trading on war – has apparently caused the platform to remove the contracts.
Polymarket has created a market that would monetize a nuclear attack amid increasing concerns that bets are happening among government insiders who can make military decisions. pic.twitter.com/r1CbWaLWcw
— David Sirota (@davidsirota) March 3, 2026
The markets, which asked users to assign probabilities to whether a nuclear weapon would detonate by specific dates, have circulated on Polymarket for years and historically have resolved to “No.”
But renewed attention to the contracts comes as prediction markets face criticism after a trader reportedly made more than $400,000 betting on Venezuelan leader Nicolás Maduro’s ouster shortly before the U.S. operation that led to his capture, raising questions about whether insiders could exploit the platforms to trade on the outbreak of war – such as the start of this current conflict with Iran – and other military actions.
Historical trading suggests the contracts occasionally priced meaningful risk.
A Polymarket contract in 2023 at one point implied roughly a 19% chance that a nuclear weapon would detonate before the end of the year, according to platform data.
A later market expiring in June 2025 traded near 12%.
The markets also attracted significant trading activity. The 2025 contract alone recorded more than $1.7 Million in volume, while the 2023 version drew nearly $700,000 in wagers.
All this comes as U.S. regulators consider how to oversee prediction markets.
The Commodity Futures Trading Commission proposed rules in 2024 that would bar exchanges it regulates from listing event contracts tied to war, terrorism, assassination, or other activities deemed contrary to the public interest.
Chairman Mike Selig said the Commission plans to issue clearer guidance on prediction markets in the near future.
Australia could unlock 24 billion Australian dollars ($17 billion) annually from advances in tokenized markets and digital assets, but only if lawmakers move forward with regulation. A new study by the Digital Finance Cooperative Research Centre (DFCRC) outlines regulatory uncertainty, coordination hurdles, and a limited pathway for pilots as the primary constraints. The research argues that a well-designed sandbox for testing tokenized financial market use cases could catalyze ongoing collaboration between regulators and industry players, help refine licensing frameworks, and accelerate real-world adoption of tokenized rails for markets, payments, and collateral management.
Key takeaways
- The DFCRC projects up to A$24 billion in annual economic gains from tokenized markets and digital finance if regulatory frameworks are clear and supportive.
- A dedicated sandbox for testing tokenized financial market use cases is recommended to foster regulator–industry collaboration and to mature licensing for institutional participants.
- Tokenized instruments, including government bonds and CBDCs, could underpin the growth of tokenized markets, enabling more efficient collateralized lending, settlement, and cross-border payments.
- Without a more predictable regulatory regime, the projected gains could shrink significantly; the study cautions that gains depend heavily on the pace and scope of policy reform.
- The report notes the project was launched in collaboration with the Digital Economy Council of Australia and financed by OKX, highlighting industry interest and the potential role of private partners in advancing a regulatory-ahead regime.
Tickers mentioned:
Sentiment: Bearish
Market context: The findings reflect a broader global push toward regulated tokenized finance, with sandbox approaches and pilot programs shaping how markets, settlements, and collateral management could evolve as liquidity and interoperability improve across digital assets.
Why it matters
The Australia study frames tokenization not merely as a technology upgrade but as a foundational shift in how capital markets, payments, and asset ownership operate. By linking regulatory clarity with technical experimentation, the DFCRC argues that tokenized markets could unlock liquidity that today remains constrained by legacy infrastructures and custodial frictions. In practical terms, tokenization could widen investor access to a broader set of instruments, improve market depth, and facilitate faster settlement cycles—benefits that, in turn, could widen the pool of available capital and deepen secondary markets.
More specifically, tokenized money—encompassing stablecoins and central bank digital currencies (CBDCs)—could streamline cross-border and domestic transactions by diminishing reliance on traditional correspondent banking rails, which can carry high fees. The DFCRC notes that tokenized rails promise greater transparency, traceability, and resiliency, with smart contracts automating processes such as collateral management, margining, and settlement. In this vision, assets become not only more liquid but more programmable, enabling new forms of automated lending, repo arrangements, and invoice financing that could reduce transaction costs and expand financing options for businesses and institutions alike.
Crucially, the report emphasizes the distribution of gains across three core areas—collateralized lending, repo, and invoice financing—where tokenized rails could yield the most measurable improvements. In such ecosystems, smart contracts handle collateral evaluation, threshold triggers, and settlement on a continuous basis, reducing counterparty risk and improving capital efficiency. If regulators provide a clear, interoperable framework, these gains could translate into tangible improvements for the broader economy, from faster settlement times to lower financing costs for infrastructure projects and small-to-medium enterprises.
The authors acknowledge that projected gains are contingent on regulatory unfoldings. The report highlights that, absent substantial regulatory reform, Australia could see far more modest economic benefits. If the current trajectory persists, DFCRC estimates that crypto-related economic gains may plateau at around A$1 billion by 2030, well short of the aspirational A$24 billion. Kate Cooper, chief executive of the crypto exchange OKX, underscored this view, stressing that robust regulation is a prerequisite for material gains, as uncertain rules can choke investor confidence and slow the deployment of tokenized services. The media release accompanying the study reiterates that the most significant upside emerges from well-defined licenses and infrastructure built to institutional standards. For readers seeking the full economic analysis, the DFCRC Economic Impact Report is available here: https://dfcrc.s3.ap-southeast-2.amazonaws.com/260303_DFCRC_Economic+Impact+Report_V7_Single.pdf.
The discussion sits within a broader international context where policymakers are balancing innovation with consumer protection, market integrity, and systemic risk concerns. While Australia contemplates a regulatory path, the underlying message is consistent with global trends: for tokenized markets to scale, regulators and industry participants must co-create frameworks that reduce friction without sacrificing safeguards. The DFCRC’s partnership with the Digital Economy Council of Australia and its funding from OKX signal both a public and private appetite for experimentation—paired with a clear-eyed recognition that policy design will ultimately determine the speed and scale of adoption. The study’s emphasis on three pillar areas also resonates with other research suggesting that tokenized collateral and automated settlement can transform capital markets by unlocking liquidity and reducing operational risk.
As the authors point out, the estimated gains could be higher or lower depending on regulatory outcomes, and the direction of policy evolution will shape both the pace and the geographic footprint of any rollout. The report’s cautions aside, the proposed sandbox model offers a concrete pathway to de-risk experimentation, offer a platform for pilots, and create license-ready infrastructure that could invite institutional participants to participate in tokenized markets at scale. In the near term, observers will watch how regulators respond to proposals for pilot projects, licensing regimes, and pilot-friendly capital-raising mechanisms that could accelerate the transition from theory to practice in tokenized finance. The collaboration behind the report reflects a broader industry push for practical regulatory reform that can foster innovation while preserving market integrity.
References to the DFCRC and its associated documents appear in links within this article, including the economic impact report and related materials that discuss tokenization and CBDCs in the Australian context. The broader ecosystem benefits described by the DFCRC align with ongoing discussions about how tokenized assets could reshape payments, lending, and collateral management, underscoring the importance of clear, institutionally aligned frameworks as Australia contemplates the next era of digital finance.
What to watch next
- Regulatory progress in Australia: any new guidelines or licensing reforms that enable sandbox participation by banks and non-bank financial institutions.
- Launch of tokenized-government-bond pilots or wholesale securities pilots within a sandbox framework.
- Deployment and testing of CBDCs in controlled environments to support settlement, collateralization, and cross-border flows.
- Announcements of further collaborations between regulators, industry groups, and crypto firms to evolve licensing standards for institutional players.
Sources & verification
- Digital Finance Cooperative Research Centre Economic Impact Report PDF: https://dfcrc.s3.ap-southeast-2.amazonaws.com/260303_DFCRC_Economic+Impact+Report_V7_Single.pdf
- OKX media release on the DFCRC economic impact collaboration: https://dfcrc.com.au/wp-content/uploads/2026/03/Economic-impact-report-media-release-digital.pdf
- Tokenization explained overview: https://cointelegraph.com/explained/tokenization-explained
- CBDCs overview for beginners: https://cointelegraph.com/learn/articles/what-are-cbdcs-a-beginners-guide-to-central-bank-digital-currencies
- Stablecoins market cap and growth data: https://cointelegraph.com/news/stablecoins-300-billion-market-cap-47-growth-ytd
- Additional reference: Australian crypto industry perspectives and related policy discussions: https://cointelegraph.com/news/australia-crypto-adoption-regulation-smsf-growth-2026
Unlocking Australia’s $24 Billion Digital Finance Opportunity
The DFCRC’s analysis positions tokenization as a potential lever for widening participation in capital markets and for improving the efficiency of financial plumbing through programmable assets. A well-structured sandbox could serve as a bridge between high-level policy goals and the day-to-day realities of banks, fintechs, and asset managers exploring tokenized markets. By enabling controlled experiments with tokenized government bonds, collateralized lending, and cross-border settlement, Australia could build a scalable blueprint for modernizing its financial infrastructure while maintaining robust investor protections. The study emphasizes that gains are not just about faster settlements or better liquidity; they hinge on a broader regulatory architecture that supports innovation without compromising financial stability. If policymakers can align on licensing standards, interoperability, and risk controls, the country could position itself as a measured, forward-looking hub for digital finance at the regional level and beyond.
Crypto World
Bitcoin Nears Historic Sixth Red Month as Gold and Silver Shed $2.4 Trillion in a Single Day
TLDR:
- Bitcoin has recorded five straight monthly red candles in 2025, pushing sentiment to historically exhausted levels.
- Gold and silver erased $2.4 trillion in market value in one session after a parabolic rally through early 2025.
- Dollar strength overrode geopolitical fear, revealing gold as a macro trade rather than a pure crisis hedge.
- A strong Bitcoin monthly reversal could trigger sharp altcoin gains, especially in assets that held technical structure.
Bitcoin continues to face mounting pressure as traditional safe-haven assets experience a sharp reversal. Gold and silver together erased roughly $2.4 trillion in combined market value in a single trading session.
The selloff followed a parabolic rally that both metals staged earlier in 2025. Bitcoin, by contrast, has now recorded five consecutive monthly red candles throughout the year.
Dollar strength has become the dominant force shaping price action across both crypto and commodity markets.
Dollar Strength Exposes the Limits of Traditional Safe Havens
Gold and silver have long been considered reliable hedges during times of geopolitical uncertainty. However, recent price action across both metals tells a different story about their true nature.
Despite tensions involving Iran, global shipping disruptions, and persistent inflation talk, dollar strength overrode fear-driven demand for metals.
Gold climbed as much as 96% since the start of 2025, while silver surged approximately 191% over the same period.
Both assets had entered parabolic territory before the sharp correction ultimately took hold. The pullback effectively flushed excess leverage from an already overstretched market position.
One analyst on X wrote that dollar strength “overpowered fear,” arguing gold behaves more like a macro trade.
According to the post, gold remains tied to yields and the dollar, not a pure crisis hedge. The comment reflects how macro traders are reassessing the metal’s role in uncertain conditions.
Five Red Months Push Bitcoin Toward Historic Exhaustion
The digital asset has fallen approximately 27% since the start of 2025, even as metals posted strong gains. The nature of that decline, however, differs sharply from the selloff metals experienced this week. Rather than a sudden forced liquidation, the drop has resembled a slow and sustained liquidity drain.
Forced selling in overleveraged markets typically produces violent, sharp price drops within short timeframes. Bitcoin’s five-month slide has been more measured and gradual by comparison. That distinction carries weight when evaluating where the asset stands heading forward.
Bitcoin is now trading at historically stretched levels across multiple timeframes. Sentiment has been steadily drained throughout several months of consecutive losses. In effect, the asset has already completed the reset cycle that metals are only now beginning.
What a Reversal Could Mean for BTC and Altcoins
A strong monthly close for Bitcoin at current levels would carry considerable upside momentum. Historically, when a price breaks out after extended compression, the move tends to be sharp rather than gradual.
Altcoins that maintained structure during the prolonged bleed are best positioned to benefit from any rotation.
The same analyst noted that when Bitcoin moves aggressively after long compression, altcoins tend not to follow quietly. Instead, they often surge alongside the broader shift in market sentiment. Assets that held technical structure through the downturn are likely to see the largest moves.
Risk factors, however, remain present. If dollar strength continues building and equities weaken, Bitcoin will not escape the broader fallout. Oversold conditions build potential energy, but a macro catalyst is still needed to confirm a sustained reversal.
A new study from the Bitcoin Policy Institute (BPI) suggests that artificial intelligence models prefer Bitcoin over stablecoins and other forms of money for different financial situations, with very few showing a preference for fiat currency.
The BPI tested 36 models generating more than 9,000 responses, and the AI agents “overwhelmingly chose to use Bitcoin for their economic activity,” the institute said on Tuesday as it released the results of its research.
The study found that 48.3% of AI models chose to use Bitcoin (BTC) overall, and it was the most selected monetary instrument across all 9,072 responses.
When prompted with scenarios about preserving purchasing power over multi-year horizons, 79.1% of AI responses chose Bitcoin, “the single most lopsided result in the study.”
However, for payment scenarios, services, micropayments, and cross-border transfers, stablecoins were chosen in 53.2% of responses compared to just 36% for Bitcoin.
Bitwise chief investment officer Jeff Park said that the most obvious explanation for stablecoins not doing better is that they “can be frozen, Bitcoin can’t.”
Almost 91% of responses chose a digitally native instrument such as Bitcoin, stablecoins, altcoins, tokenized real-world assets (RWA), or compute units over traditional fiat.
“Zero of the 36 models tested chose fiat as their top overall preference, making digital-money convergence one of the most universal findings in the study.”
Methodology had limitations
The Bitcoin Policy Institute said the current study was limited to 36 models tested across six providers, and it would look to expand to additional models in the future.
It also acknowledged that system prompt framing may have influenced the results, adding that “future work will test alternative framings and measure sensitivity.”
This was apparent in some of the “open-ended monetary scenarios” presented to the AI models.
Related: OpenAI pits AI agents against each other to detect smart contract flaws
For example, one scenario asked what financial instrument an AI would choose if it were operating across multiple countries with “75,000 units of accumulated earnings” wanting to store them in a way that is “not tied to any single country’s monetary policy or banking system,” which would already rule out fiat currency.
BPI also said that the AI models’ preferences do not reflect real-world adoption and that the results instead indicate training data patterns.
The study revealed that Anthropic models averaged a 68% Bitcoin preference, whereas OpenAI models averaged 26%, Google’s 43%, and xAI 39%.
Magazine: 6 massive challenges Bitcoin faces on the road to quantum security
XRP price is retesting range lows as open interest drops 70%, putting $1.30 support in focus.
Summary
- XRP trades at $1.34, down sharply from its July 2025 high of $3.65.
- Open interest has fallen from $660M to $203M in five months, led by Binance.
- A daily close below $1.30 could open the door to $1.00, while $1.50 is key for recovery.
XRP (XRP) is back near the bottom of its range amid continued selling pressure. At press time, the token trades at $1.34, down 4.4% in the past 24 hours.
The seven-day range is between $1.28 and $1.48. XRP has fallen 50% over the last week and is now 63% below its July 2025 all-time high of $3.65. Market volatility and risk-off sentiment, partly tied to geopolitical tensions, have weighed on price action.
Open interest drops sharply
A Mar. 3 analysis by CryptoQuant contributor Amr Taha shows a major shift in the futures market. Total XRP open interest across exchanges fell from $660 million on Oct. 6, 2025, to $203 million on March 3, 2026. That’s a 70% drop in five months.
Binance led the decline, while Bitfinex and BitMEX now show only a few million dollars in open contracts.
Open interest tracks the number of active futures positions. When both price and open interest fall together, it often means traders are closing positions or getting liquidated.
The last time Binance XRP open interest dropped to similar levels, around April 2025, price later formed a bottom near $1.80 before rallying. Large leverage wipes have often reset the market in the past, potentially pointing to an upcoming trend change.
XRP price technical analysis
On the daily chart, XRP is testing the $1.30–$1.35 support zone. This level forms the base of the current multi-month range. A daily close below $1.30 would break the structure and expose $1.00–$1.10 as the next downside area. If support holds, price stays in consolidation.
The trend still shows lower highs and lower lows. XRP trades below declining moving averages. For a real shift, price must reclaim the $1.50–$1.60 supply zone and break the last lower high.
Bollinger Bands expanded during the sell-off and are now tightening. When volatility contracts after a sharp move, a larger move often follows. Price sits near the lower band, which shows pressure but can also signal exhaustion.
RSI bounced from oversold levels and is now near 40. Momentum is still weak below 50. A push above 50 would show stronger buying strength.
The current area also holds past liquidity. Stop losses could be triggered and the decline accelerated by a clean break below support. Short covering could lead to a rapid bounce if sellers don’t push lower.
A range recovery and a shift in the short-term momentum would be indicated by a daily close above $1.50. If the price closed below $1.30, there would likely be more drops. XRP is at a crucial turning point, and volatility may soon increase.
YZi Labs commits $100m to Hash Global’s BNB Holdings Fund, pitching BNB as institutional-grade yield infrastructure.
Summary
- YZi Labs commits $100m to Hash Global’s BNB Holdings Fund, positioning BNB as institutional-grade yield infrastructure asset.
- Fund described as “institutional version of BNB Yield Fund,” marking BNB’s formal transition into a structurally advanced stage of its lifecycle.
- BNB trades as both exchange proxy and yield-bearing infrastructure play, with institutional capital now prioritizing structural returns over speculative narratives.
YZi Labs is putting a nine‑figure stamp on its BNB (BNB) thesis, committing $100m to Hash Global’s new BNB Holdings Fund and openly pitching BNB as a yield‑bearing core asset for future financial infrastructure. In an announcement on X, the firm said it is “committing $100M to @HashGlobal’s BNB Holdings Fund,” with head of YZi Labs Ella Zhang arguing that “BNB has become a foundational utility asset with attractive yield, powering the future of financial infrastructure.” The fund is positioned as an institutionalized, yield‑oriented vehicle, with YZi explicitly “inviting more traditional capital to participate in its structural returns and long‑tergrowth.
Hash Global, in its own statement, framed the commitment as a turning point for the BNB capital stack, describing the BNB Holdings Fund as the “institutional version of the BNB Yield Fund” and saying the fresh capital “marks the formal transition of BNB into a structurally advanced stage” of its lifecycle. That language was quickly amplified by market commentators. One observer summarized the shift by noting that “the shift from pure utility to a structural asset class is what most people are missing. Institutionalizing the yield is the real game changer here.” Another called it “BNB’s $100M institutional yield fund,” arguing it “marks BSC’s real maturation” and ties the same infrastructure to “verifiable agricultural yields” and other real‑world on‑chain cash flows.
Not everyone is convinced. One critic pushed back bluntly, asking “why? $bnb literally cripples the market with manipulation why would you align with it?”, capturing the lingering concerns around concentration risk and governance. But even skeptics acknowledge that where capital goes, narratives follow. A widely shared reaction put it this way: “utility acts like gravity for capital. 100M is a solid data point confirming the ecosystem’s maturity. The suits are finally doing the math right.” Another commentator argued that the move “shows how institutional capital is now prioritizing structural alignment with foundational utility assets that deliver real yields rather than chasing speculative narratives,” effectively turning “traditional money into active participants” in BNB’s on‑chain economy.
BNB’s latest price action reflects that tension between structural bid and headline risk, with the token trading as both an exchange proxy and, increasingly, a yield‑bearing infra play watched closely by funds looking for repeatable basis trades. For day‑to‑day traders, the takeaway is simple: if YZi’s $100m check is the opening salvo rather than the full story, BNB’s cost of capital — and its perceived role in crypto’s funding stack — just changed.
Bitcoin’s rebound toward $70,000 — trading at $68,000 as Hong Kong hit midday — appears to have been driven more by positioning than conviction, according to market maker Enflux, which said the move largely reflected short-covering after traders leaned bearish amid geopolitical headlines.
“The market is not pricing catastrophe, but it is not pricing resolution either,” Enflux wrote in a note to CoinDesk. “Shorts leaned into the Iran headlines over the weekend, BTC flushed toward 63k, and when escalation did not immediately spiral into a broader regional war affecting the Gulf and Dubai trade corridors, the squeeze began.”
Crypto tends to react faster than traditional assets during geopolitical shocks, Enflux added.
“When bombs drop, or sanctions tighten, capital looks for exit routes. In times of uncertainty, BTC becomes a pressure valve,” the firm wrote.
Institutional demand has remained a key source of support. Over the past five trading days, BTC ETFs have attracted roughly $1.45 billion in net inflows.
Boomers to the rescue again as bitcoin ETFs record $1.5b of inflows in the past 5 days after another big day yesterday. Biggest haul in a while, just about all of the original ten spot ETFs seeing action too = breadth and depth. This after a 50%(!) drawdown and most underwater.… pic.twitter.com/eF0VJqiPZ0
— Eric Balchunas (@EricBalchunas) March 3, 2026
Onchain and derivatives indicators suggest the market is stabilizing but not yet regaining strong conviction.
In a recent report, Glassnode wrote that momentum indicators are beginning to recover from recent weakness, with bitcoin’s relative strength index rising to about 41 from 36 the previous week, though still below the neutral 50 level that would signal stronger bullish control.
Spot market conditions have also improved. Trading volume has climbed to roughly $9.6 billion from $6.6 billion the previous week, while buying and selling flows in spot markets have become more balanced, suggesting the earlier wave of aggressive selling has begun to ease.
Derivatives markets remain cautious. Glassnode said the cost of holding leveraged long positions has dropped sharply, while futures trading still shows sellers dominating buyers, signaling continued caution among leveraged traders.
Prediction markets reflect the same cooling of conviction: the probability of bitcoin falling to $65,000 in March has dropped 11 percentage points to 73%, the odds of $60,000 have fallen 10 points to 41%, and a separate Polymarket contract showing bitcoin hitting $60,000 before $80,000 has also weakened, sliding 12 points to 61%.
Together, the data suggests bitcoin has found support for now, but traders remain hesitant to price in either a decisive rally or a deeper selloff.
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AI Agents Prefer Bitcoin Over Fiat, New Study Finds
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