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How AI-Powered Decision Intelligence Transforms Business Outcomes

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Running a business? Still making million-dollar decisions based on the reports of the last quarter? Is your organization simply following the market trends instead of anticipating the changes? If so, you’re already falling behind.

In the current dynamic business environment, the key differentiators are speed and accuracy in decision-making. Companies that are still relying on conventional business intelligence tools, static dashboards, lagging indicators, and intuitive forecasting are being left behind by those who have already adopted Enterprise Predictive Analytics Services and Artificial Intelligence-Powered Decision Intelligence. The gap between reactive and predictive companies is no longer operational; it’s existential.

As McKinsey suggests, companies that leverage data and analytics at scale are 23 times more likely to acquire customers, 6 times more likely to retain them, and 19 times more likely to turn a profit.

However, the truth is that the majority of companies are struggling to move past the basics of reporting.  The data exists. The technology exists. What’s missing, for most organizations, is a clear strategy to harness it.

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Let’s unpack how predictive analytics and decision intelligence are rewriting the rules of business performance and what industry leaders already know that most businesses are still figuring out.

What Industry Leaders Know About Predictive Analytics That Most Businesses Don’t

The myth is that predictive analytics is a technology for business giants and Fortune 500 companies, that the cost of entry is too high, the infrastructure too complex, and the ROI too uncertain. This myth has long been debunked by industry leaders. 

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Aspect Analytics Decision Intelligence
Core Question What happened? What do we do?
Primary Function Shows patterns Triggers action
Output Type Passive output (insights, reports) Active system (recommendations, actions)

This is what they know that most mid-sized and growing companies don’t:

1. Data Is an Asset, Not a Byproduct

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Most companies create massive amounts of data that are associated with transactions, operations, customer interactions, and supply chains. They view it as a byproduct, not as a strategic asset. Industry leaders, on the other hand, invest in Enterprise Predictive Analytics Services because they know that structured data in real-time is the raw material of competitive advantage.

Amazon, for instance, uses predictive analytics to predict demand and pre-position inventory before customers even click the “buy” button. It’s not just about operational efficiency; it’s a completely different philosophy about what data is for.

2. Reactive Intelligence Is Already Obsolete

The days of waiting for the end-of-month report to gain insight into business performance are now behind us. AI-Powered Decision Intelligence enables leaders to know what will happen and why, before it happens. This includes churn prediction, demand forecasting, fraud detection, and risk analysis,  all in real-time.

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A global logistics company that implemented an AI-Powered Decision Intelligence solution was able to reduce freight delays by 34% in one year, not by hiring more people or more trucks, but through predictive route optimization and demand analysis.

The goal is to turn data into information, and information into insight.” — Carly Fiorina, Former CEO of Hewlett-Packard

3. Consulting Expertise Is the Bridge Between Data and Decisions

Outcomes cannot be achieved through technology alone. The leaders who have been able to unlock real value from predictive analytics always emphasize the importance of Predictive Analytics Consulting Services in their success stories. These consultants not only focus on the implementation of technology but also ensure that predictive analytics are linked with the business key performance indicators, and the outputs from algorithms are converted into decisions that are at the executive level.

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Most analytics projects get stuck at the “proof of concept” stage.

4. Decision Intelligence Is a Layer Above Analytics

Here’s the key difference that most companies get wrong: Analytics shows you what has happened and what could happen. Decision Intelligence shows you what to do about it. A Decision Intelligence Platform for Business combines predictive analytics with business rules, business processes, and human expertise – building a closed-loop system that automatically acts on insights.

A financial services company with a Decision Intelligence Platform for Business can automatically identify high-risk loan applications, send them to the correct underwriters, and change credit policies in real-time.

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5. The ROI Is Real But It Requires the Right Foundation

According to Gartner research, for large companies with annual revenues of $1 billion or more, the average return on investment for emerging technologies in 2023 was 20x (or 2000%) in 2023, primarily due to AI and analytics, as reported in 2024. 

However, such ROI is not achieved instantly or by chance. The leadership is well aware that the underlying structure, such as clean data, strong infrastructure, scalable models, and sound interpretation of results, is of prime importance.

Those companies that perceive analytics as a one-time function, rather than an operational capability, are likely to be less successful than companies that perceive it as an operational function.

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Make faster strategic decisions with AI-powered decision intelligence services from Antier

The Science Behind Better Business Outcomes: Predictive Analytics & Decision Intelligence

Understanding the mechanics that drive the predictive analytics and decision intelligence processes will help to clarify these technologies for leaders who are skeptical or overwhelmed by them.

How Enterprise Predictive Analytics Services Actually Work

The architecture is not as mysterious as the vendors claim. Enterprise Predictive Analytics Services begin with data, structured input from your CRM, ERP, and supply chain systems, as well as external data such as market data, economic data, and sometimes unstructured data such as customer feedback or web behavior. This data is cleaned and integrated into statistical and machine learning models that are trained to find patterns that would never be detected by human analysts.

What comes out the other side looks like:

  • A probability score telling you which customers are most likely to churn in the next 30 days and why.
  • A demand forecast accurate enough to adjust inventory by SKU and region three months out.
  • A risk flag surfacing a supplier that’s showing early signs of financial distress before your procurement team has noticed.
  • A scenario model showing what a 7% price increase would do to volume across your top five customer segments.

None of this is theoretical. These are outputs that enterprise teams are using to make real decisions today.

What Makes a Decision Intelligence Platform for Business Different

A lot of companies have analytics. Fewer have decision intelligence. The difference is what happens after the prediction is made.

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A Decision Intelligence Platform for Business doesn’t just point to an insight, it links that insight to a particular decision, sends it to the right person or system, and tracks what happens when it’s implemented (or not). Over time, the platform learns which suggestions are being accepted, which are being overridden, and what the outcomes were. That’s the feedback loop that makes AI-Powered Decision Intelligence truly different from a dashboard with better charts.

How does it work?

A dashboard tells your supply chain manager that inventory is low. A Decision Intelligence Platform for Business tells them what to buy, from whom, at what price, based on current lead times and demand forecasts, and alerts it for approval or automatically implements it, depending on the dollar amount.

Advanced Analytics Services for Enterprises: Where It Works Across Industries

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Advanced Analytics Services for Enterprises have a set of diverse capabilities applied differently, depending on the business. Here’s what that looks like in practice across a few verticals:

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1. Financial Services

Banks using AI-Powered Decision Intelligence for credit underwriting have moved beyond static FICO scores to real-time models that factor in hundreds of behavioral and contextual signals. As a result, default rates went down 20–30% in documented cases, and credit was extended more accurately to customers who would have been declined by legacy models. Fraud detection teams are catching anomalies in milliseconds rather than reviewing flagged transactions the next morning.

2. Retail and eCommerce

Retailers applying Advanced Analytics Services for Enterprises to markdown optimization have reduced inventory carrying costs by 15–25% while improving margin recovery on aged stock. Customer lifetime value models are helping merchants stop spending acquisition budgets on customers who won’t return, and start investing in the ones who will often get back, by enabling personalized offers for each segment’s actual price sensitivity.

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3. Manufacturing and Supply Chain

Predictive maintenance is probably the most well-documented manufacturing use case, with unplanned downtime reductions of up to 50% when implemented well. However, supply chain disruption modeling, which became a survival skill during the pandemic, is now a standard application of Enterprise Predictive Analytics Services in industrial environments. Knowing three weeks early that a key supplier is at risk gives procurement teams options. Finding out when the shipment doesn’t arrive gives them nothing.

4. Healthcare and Life Sciences

Healthcare systems employing predictive models to identify patients eligible for high-risk readmission have been able to focus post-discharge follow-through efforts on those who can significantly lower 30-day readmission rates. For the pharmaceutical industry, predictive models for clinical trial site selection are reducing the time and expense of getting products to market by identifying the most likely sites for on-time and successful recruitment.

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What Predictive Analytics Consulting Services Actually Deliver

When companies engage Predictive Analytics Consulting Services, the deliverable isn’t a model. It’s a working capability that is part of the business. That usually means that there are a few different stages that you have to go through: understanding the current state of the data environment and where the actual gaps are, finding use cases that have the best ROI-to-effort ratio, developing and testing models that can withstand exposure to the actual production data, integrating those models into the systems that your teams are actually using, and then implementing governance to make sure that the models are correct as the world changes.

The change management component is the part that most technical vendors tend to underestimate. A model that frontline managers don’t trust or don’t know how to use . It is just an expensive science project. Getting adoption means explaining the output in plain language, giving people a way to flag when something feels off, and demonstrating over time that the model’s track record justifies the trust being asked of them.

Turn enterprise data into actionable insights with AI-powered decision intelligence today

Building a Scalable Advanced Analytics Services for Enterprises Foundation

Enterprises that get sustained value from Advanced Analytics Services for Enterprises don’t build one model and call it done. They build a platform, a unified data layer that all models draw from, a registry that tracks what’s deployed and when it was last validated, an environment where new use cases can be tested before they go live, and deployment infrastructure that makes updating a model straightforward rather than a months-long IT project.

The Decision Intelligence Platform for Business layer that sits on top of all this needs to do one thing exceptionally well, and that is to make it easy for the business to understand why a recommendation was made. In regulated industries, especially banking, insurance, and healthcare,  explainability isn’t a nice-to-have. Regulators expect it. Compliance teams require it. Frankly, business leaders shouldn’t be comfortable acting on recommendations they can’t interrogate.

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The ROI Conversation: What CFOs Actually Want to Hear

The global decision intelligence market is expected to climb from USD 17.7 billion in 2025 to approximately USD 72.3 billion by 2034, at a 16.9% CAGR.

The most effective AI-Powered Decision Intelligence solutions are built with measurement in mind from day one, with baseline metrics set up before deployment, decision influence tracked, and outcome data collected automatically so that the ROI discussion is always based on actual numbers, not forecasts.

Wrapping Up

The businesses that are pulling away from their competition right now aren’t necessarily smarter or better funded. Many of them simply made the decision earlier to stop operating in the dark. They invested in Enterprise Predictive Analytics Services when it felt premature. They built their Decision Intelligence Platform for Business before they fully understood how they’d use it. Now, they’re operating with a visibility and speed advantage that is genuinely difficult for later movers to close.

You don’t need to have solved your data challenges before starting this journey. You don’t need a perfect data warehouse or a team of in-house data scientists already on payroll. 

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That’s what Antier does. Our Advanced Analytics Services for Enterprises are built around your specific business context, not a generic platform deployed out of the box. We’ve worked across financial services, retail, healthcare, and manufacturing to help enterprise teams move from fragmented data to decisions they can trust. 

If there’s a decision your business is making today that you’re not fully confident in pricing,

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Crypto World

what happens beyond the yield

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what happens beyond the yield

In today’s newsletter, Nassim Alexandre from RockawayX takes us through crypto vaults, what they are, how they work and risk evaluation.

Then Lucas Kozinski, from Renzo Protocol, answers questions about decentralized finance in Ask an Expert.

Sarah Morton


Understanding vaults: what happens beyond the yield

Capital flowing into crypto vaults surged past $6 billion last year, with projections indicating it could double by the end of 2026.

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With that growth, a sharp split has emerged between vaults with robust engineering and controls and vaults that are essentially yield packaging.

A crypto vault is a managed fund structure deployed on-chain. An investor deposits capital, receives a token representing their share, and a curator allocates that capital in accordance with a defined mandate. The structure can be custodial or non-custodial, redemption terms depend on the liquidity of the underlying assets and portfolio rules are often encoded directly into smart contracts.

The central question around vaults is exposure: what am I exposed to, and can it be more than I am being told? If you can explain where the yield comes from, who holds the assets, who can change the parameters and what happens in a stress event, you understand the product. If you cannot, the headline return is irrelevant.

There are three risk layers worth understanding.

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The first is smart contract risk: the risk that the underlying code fails. When was the last audit? Has the code changed since? Allocation controls sit here as well. Adding new collateral to a well-designed vault should require a timelock that allows depositors to see the change and exit before it takes effect. Strategy changes should require multi-signature approval.

The second is underlying asset risk: the credit quality, structure and liquidity of whatever the vault is actually holding.

The third underappreciated risk is redemption: under what conditions can you get your capital back, and how quickly? Understand who handles liquidations in a downturn, what discretion they have and whether the manager commits capital to backstop them. That distinction matters most in the exact moments you would want to leave.

The quality of a vault is largely dependent on the quality of its curation. A curator selects which assets are eligible, sets parameters around them and continuously monitors the portfolio.

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For example, most real-world asset strategies on-chain today are single-issuer, single-rate products. A curated vault, by contrast, combines multiple, vetted issuers under active management, giving diversified exposure without managing single-name credit risk yourself.

Then there is ongoing monitoring. Default rates shift, regulations change and counterparty events happen. A curator who treats risk assessment as a one-time exercise is not managing risk.

What makes crypto vaults different from a traditional fund is transparency; investors don’t have to take the curator’s word for it. Every allocation, position and parameter change happens on-chain and is verifiable in real time. For advisors familiar with private credit, the underlying collateral may be recognisable. What requires attention is the on-chain structuring around it: whether you have genuine recourse, in which jurisdiction and against whom. That is where curator expertise matters. A curator is the risk manager behind a vault. They decide what assets are eligible, set the rules capital operates within, and actively manage the portfolio.

Curated vault strategies typically target 9-15% annually, depending on mandate and assets. That range reflects risk-adjusted return generation within defined constraints.

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Vaults also allow a more efficient way to access assets you already allocate to, with capabilities that traditional structures do not offer. For family offices managing liquidity across multiple positions, this is a practical operational improvement.

The key one is composability. On-chain, a vault can allow you to borrow against a collateral position directly, without the documentation overhead of a traditional loan facility. For family offices managing liquidity across multiple positions, this is a practical operational improvement.

Permissioned vault structures are also noteworthy, as they allow multiple family offices or trustees to deposit funds into a single managed mandate without commingling, each retaining separate legal ownership while sharing the same risk-management infrastructure.

The vaults that survive this scrutiny will be the ones where the engineering, mandate, and curator’s judgment are built to hold under pressure.

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Nassim Alexandre, vaults partner, RockawayX


Ask an Expert

Q: With “yield-stacking” and many layers of decentralized finance (DeFi) protocols, what is needed to mitigate risk in vaults?

The first thing is minimizing complexity. Every additional protocol in the stack is another attack surface. So if you don’t need it, cut it. We won’t deposit into protocols that have discretionary control over funds — meaning they can move capital wherever they want without user consent. We want transparency about what other protocols are doing with our capital, but privacy around our strategies so others can’t see anything proprietary.

Beyond that, it comes down to transparency and time. Users should always be able to see exactly where their funds are and what they’re doing. And any parameter changes — fees, strategies, risk limits — should go through a timelock so people have a window to review and react before anything goes live. Smart contract audits matter too, but audits are a baseline, not a safety net. The architecture has to be sound before the auditor even shows up.

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Q: At what point does institutional capital inflow compress DeFi yields to the level of traditional risk-free rates, and where will the next “alpha” be found?

It’ll happen eventually in the most liquid, simple strategies. But here’s what traditional finance (TradFi) can’t replicate: composability. The underlying instruments might be identical — take the USCC carry trade as an example — but in DeFi you can plug that same position into a lending market, use it as collateral, provide liquidity to a DEX pool and do all of that simultaneously. That’s not possible in TradFi without significant infrastructure cost.

The alpha won’t disappear. It’ll just move to whoever builds the most efficient capital pathways between strategies. The people who figure out how to stack yields across composable layers while managing risk properly will consistently outperform. And that gap between DeFi and TradFi infrastructure costs alone keeps the spread wide for a long time.

Q: How will the integration of Real World Assets (RWAs) into automated vaults change the correlation between crypto yields and global macro interest rate cycles?

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Yes, crypto yields will become more correlated with macro as RWAs come in. That’s just the nature of bringing rate-sensitive assets on-chain. But I think people underweight the other side of that tradeoff.

Before RWAs, crypto holders had a binary choice: keep stables on-chain and earn crypto-native yields, or pull everything out and deposit into a brokerage. Now you can hold stables on-chain and access the same strategies you’d find in TradFi, without leaving the ecosystem. And crucially, you can layer on top of them — borrow against your RWA position, deploy that capital into a lending market, LP against pools that use these assets as collateral. The capital efficiency you get from that kind of setup is just not available in traditional finance. So yeah, more macro correlation — but also more optionality for where to deploy capital, which should push rates up over time as liquidity deepens.

Lucas Kozinski, co-founder, Renzo Protocol


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Anchorage Digital Launches Regulated ‘Stablecoin Solutions’

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Anchorage Digital Launches Regulated 'Stablecoin Solutions'

Anchorage Digital has launched a new offering called Stablecoin Solutions, enabling banks to perform near-instant USD settlements.

Anchorage Digital has announced the launch of Stablecoin Solutions, a federally regulated service that enables banks to conduct near-instant USD settlements globally via blockchain technology. This move by Anchorage Digital, the first federally chartered crypto bank in the U.S., aims to modernize cross-border settlements while adhering to stringent regulatory standards.

The new offering consolidates minting, redemption, custody, fiat treasury, and settlement under Anchorage Digital Bank, N.A., operating under the oversight of the Office of the Comptroller of the Currency (OCC). This positions Anchorage to offer a seamless integration of stablecoin technology within traditional banking frameworks, eliminating the complexities of state-by-state licensing.

“Stablecoins are becoming core financial infrastructure,” said Nathan McCauley, co-founder and CEO of Anchorage Digital. “Stablecoin Solutions gives banks a federally regulated way to move dollars globally using blockchain rails, without compromising custody, compliance, or operational control. This is about modernizing settlement while preserving the standards the financial system depends on.”

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Stablecoin Solutions aims to compress settlement timelines from days to minutes, reduce trapped liquidity, and mitigate counterparty and settlement risks by replacing traditional banking methods like correspondent banking and nostro/vostro pre-funded accounts. The offering supports various stablecoins, including Tether’s USA₮ and Ethena Labs’ USDtb, providing banks with flexible, stablecoin-agnostic rails.

Anchorage Digital’s foray into stablecoin solutions aligns with broader trends in the crypto industry, where major players like PayPal are also expanding their stablecoin activities.

This article was generated with the assistance of AI workflows.

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Bitcoin price coils into a triangle formation, why a breakout is looming

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Bitcoin price coils into a triangle formation, why a breakout is looming - 1

Bitcoin price is compressing into a tightening triangle structure, signaling a major decision point as converging support and resistance suggest an imminent volatility expansion in the near term.

Summary

  • Triangle compression signals imminent breakout, volatility expansion approaching
  • Higher lows indicate growing demand, favoring bullish resolution
  • $76,700 resistance becomes key target, if breakout confirms with volume

Bitcoin (BTC) price action has entered a constructive consolidation phase, forming a clear triangle pattern that reflects growing market equilibrium. After recent volatility, the price has entered a period of compression, with dynamic support and resistance continuing to narrow. This behavior often precedes significant directional movement, as markets rarely remain compressed for extended periods.

Triangle formations typically represent a balance between buyers and sellers before a decisive breakout occurs. In Bitcoin’s case, price remains inside the structure, meaning the breakout has not yet been confirmed. However, as the price approaches the apex of the triangle, the probability of a volatility expansion increases substantially.

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The market is now nearing a macro decision point where momentum will likely return and determine Bitcoin’s next trend phase.

Bitcoin price key technical points

  • Bitcoin trading inside a clear triangle formation, signaling compression
  • Apex zone approaching, increasing breakout probability
  • $76,700 high-timeframe resistance becomes upside target, if bullish break occurs
Bitcoin price coils into a triangle formation, why a breakout is looming - 1
BTCUSDT (2H) Chart, Source: TradingView

The current triangle formation is defined by converging dynamic support and resistance aligned closely with the value area low and value area high. Each rejection from resistance and defense of support has gradually tightened price action, reducing volatility and forming a classic apex structure.

Such formations indicate that neither buyers nor sellers currently dominate the market. Instead, liquidity builds on both sides as participants wait for confirmation of direction. As compression increases, even modest momentum can trigger a sharp expansion once price escapes the pattern.

Importantly, Bitcoin has not yet broken out. Until a confirmed move occurs, price remains in consolidation rather than trend continuation.

Higher Lows Suggest Constructive Momentum

One notable feature within the triangle is the development of higher lows forming near the value area low. These higher lows indicate that buyers are stepping in earlier on each pullback, gradually applying upward pressure on price.

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While this does not guarantee a bullish breakout, it does suggest constructive underlying demand. Markets forming higher lows during consolidation often lean toward upside resolution, particularly when support continues to hold consistently.

This behavior reflects accumulation rather than distribution, strengthening the possibility of a bullish expansion once the triangle resolves.

Apex zone becomes the market decision point

The apex of the triangle represents the most critical area in the current structure. As the price reaches this narrowing zone, the market is forced into a decision. Breakouts from triangle patterns frequently occur near the apex because the price has little room left to consolidate.

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However, direction alone is not enough. Volume confirmation will be essential. A breakout accompanied by increasing volume would validate participation returning to the market and significantly improve the probability of sustained follow-through.

Without volume expansion, breakouts risk becoming false moves that quickly reverse back into the range.

Upside scenario targets $76,700 resistance

If Bitcoin breaks to the upside with strong volume confirmation, attention shifts toward high-timeframe resistance near $76,700. This level represents a major technical objective and aligns with prior supply areas within the broader trading structure.

A successful breakout would signal the end of the consolidation phase and the beginning of a new expansion leg, potentially attracting momentum traders and renewed market participation.

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What to expect in the coming price action

From a technical, price-action, and market-structure perspective, Bitcoin is approaching a macro decision point. The triangle formation indicates compression, and compression almost always leads to expansion.

In the immediate short term, traders should expect increasing volatility as price interacts with the apex zone. A confirmed breakout supported by rising volume will likely dictate the next major move.

While higher lows favor a bullish resolution, confirmation remains essential. Until the breakout occurs, Bitcoin remains in consolidation, but the technical evidence suggests that a significant move is approaching rapidly.

The upcoming sessions are likely to define Bitcoin’s next directional trend as the market prepares for an imminent expansion of volatility.

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ProShares Debuts Stablecoin-Ready ETF Compliant with GENIUS Act

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Nexo Partners with Bakkt for US Crypto Exchange and Yield Programs

TLDR

  • ProShares launched the GENIUS Money Market ETF (IQMM), designed to support stablecoin issuers with liquid, short-term U.S. government securities.
  • The ETF is structured to comply with the GENIUS Act, which mandates stablecoin issuers to back their tokens with safe, liquid assets.
  • IQMM focuses on cash and Treasury bills with maturities of 93 days or less, ensuring liquidity for stablecoin issuers.
  • The GENIUS Act, signed into law in July, requires stablecoins to be backed 1:1 by assets that are easily convertible to cash.
  • The launch of the ETF comes as the stablecoin market approaches $300 billion, with projections for significant growth in the coming years.

ProShares introduced the GENIUS Money Market ETF (IQMM) on Thursday, a product designed for the growing stablecoin market. This fund aims to support stablecoin issuers by investing in highly liquid assets that meet the requirements of the GENIUS Act. The move comes as the stablecoin sector is projected to grow significantly in the coming years.

ProShares IQMM ETF Targets Stablecoin Issuers

The ProShares GENIUS Money Market ETF (IQMM) was launched to address a gap in the stablecoin market. Under the GENIUS Act, stablecoin issuers must back their tokens with assets that are liquid and low-risk, such as U.S. Treasury bills. IQMM is designed to invest solely in short-term, liquid U.S. government securities, meeting the law’s reserve criteria.

The law restricts eligible reserve assets to Treasury bills with maturities of no longer than 93 days. ProShares designed the fund to comply with these rules, ensuring that issuers can quickly access liquidity without selling longer-term bonds at a loss during periods of market volatility.

GENIUS Act Compliance Ensures Stability

The GENIUS Act, signed into law last July, is central to the structure of IQMM. The law aims to create a safer, more stable environment for the stablecoin market by requiring 1:1 backing with liquid, safe assets. ProShares’ ETF aligns with the law’s requirement, ensuring that stablecoins are supported by assets that can easily be converted to cash.

By focusing on cash and short-dated government securities, the fund provides issuers with the liquidity needed for daily redemptions. This ensures that stablecoin issuers can meet user demands without having to sell more volatile, longer-dated securities during times of stress in the financial markets.

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Stablecoin Market Growth Prompts Regulatory Action

The launch of the IQMM fund occurs as the stablecoin market approaches $300 billion in circulation, with Tether’s USDT and Circle’s USDC leading the sector. Policymakers are preparing for rapid expansion, with some forecasts suggesting stablecoin circulation could reach $2 trillion by 2028. Wall Street projections are more optimistic, with some firms predicting the market could grow as large as $4 trillion.

Treasury Secretary Scott Bessent has indicated that stablecoins could become a significant part of the financial system in the coming years. His forecasts suggest the market could grow substantially by the end of the decade.

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U.S. Federal Reserve researchers sing praises of prediction markets

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U.S. Federal Reserve researchers sing praises of prediction markets

A research paper at the U.S. Federal Reserve praised the usefulness of prediction markets — specifically looking at Kalshi — in getting a real-time handle on economic policy.

“Kalshi’s forecasts for the federal funds rate and [the U.S. Consumer Price Index] provide statistically significant improvements over fed funds futures and professional forecasters, all while providing continuously updated full distributions rather than infrequent point estimates,” according to the paper published on Thursday.

And the markets, in which retail investors can buy contracts in virtually any yes-no question in such diverse fields as economics, politics and sports, are looking at topics on a live basis that other sources of information don’t.

Prediction markets “provide unique insights — particularly for variables like [gross domestic product] growth, core inflation, unemployment and payrolls, for which no other market-based distributions currently exist.”

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And in this study, Kalshi predictions “perfectly matched the realized federal funds rate by the day of each meeting since 2022, a feat not achieved by either surveys or futures.”

Part of the secret sauce that sets prediction markets apart as a useful tool may be the inclusion of retail participants, which makes them “distinct from institutionally dominated markets,” the paper noted.

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Bitcoin Miners Plan 30GW AI Capacity Amid Margin Pressure

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Bitcoin Miners Plan 30GW AI Capacity Amid Margin Pressure

Public Bitcoin miners are planning about 30 gigawatts of new power capacity aimed at artificial intelligence workloads, nearly three times the 11 GW they currently have online, as they race to offset shrinking mining margins and reposition for the next growth cycle.

The buildout, compiled by TheEnergyMag across 14 publicly traded Bitcoin (BTC) miners, underscores how aggressively the industry is pivoting away from traditional hashpower amid persistently weak hashprice conditions.

On paper, the planned expansion amounts to what TheEnergyMag described as “a small country’s worth of power infrastructure.” In reality, much of the 30 GW sits in development pipelines, interconnection queues or early-stage plans, rather than operational facilities.

Current and proposed power capacities of public Bitcoin miners. Source: TheEnergyMag

The widening gap suggests competition is shifting from ASIC efficiency to securing power, financing and delivering data centers on time.

“This is the megawatt arms race of the AI boom,” TheEnergyMag said, adding that monetization ultimately depends on whether AI demand remains strong enough to justify the scale of investment.

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Related: The real ‘supercycle’ isn’t crypto, it’s AI infrastructure: Analyst

AI pivot delivers early revenue gains for some miners

The shift toward artificial intelligence infrastructure reflects an increasingly hybrid strategy among established Bitcoin miners, with some companies already reporting meaningful revenue contributions from AI and high-performance computing (HPC) workloads.

One example is HIVE Digital, which recently posted record quarterly revenue driven in part by its AI and HPC business lines. The company reported fourth-quarter sales of $93.1 million, up 219% year on year, even as Bitcoin prices declined during the period.

Investors, too, are attuned to the shift. Earlier this week, Starboard Value went public with its suggestion to Riot Platforms management that they accelerate the miner’s expansion into HPC and AI data centers.

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The push to diversify comes as mining profits have taken a hit since the 2024 Bitcoin halving, which cut block rewards and squeezed margins across the industry.

Conditions have gotten even tougher since the fourth quarter, when heavy selling pressure sent Bitcoin tumbling from its record high above $126,000. Prices eventually stabilized in February, after briefly falling to below $60,000.

Despite these headwinds, US-based miners showed resilience at the start of the year, with output rebounding after a severe winter storm temporarily disrupted operations.

Source: Julien Moreno

Related: Paradigm reframes Bitcoin mining as grid asset, not energy drain