Instead, wealthy families are increasingly moving capital into private credit, infrastructure, climate-linked investments, strategic commodities, farmland, energy assets, and alternative jurisdictions.

This transition is happening at a time when the global economy faces overlapping pressures. Wars in Eastern Europe and the Middle East, supply chain fragmentation, rising protectionism, debt concerns, inflation volatility, and political polarisation have challenged assumptions that shaped investment strategies for more than two decades. For many wealthy investors, the old framework of diversification through public markets alone no longer appears adequate.

As a result, the modern family office is evolving from a relatively passive wealth management structure into a highly strategic investment institution that increasingly resembles a sovereign wealth fund in both scale and sophistication.

The Declining Appeal of Traditional Portfolios

For decades, wealthy families relied heavily on a classic portfolio mix of equities, bonds, real estate, and cash deposits managed through large private banks. That model delivered stability during periods of globalisation, low inflation, and predictable monetary policy.

Today, many of those assumptions are under strain.

Bond markets, historically viewed as safe havens, have become more volatile as central banks battle inflation and governments carry record debt burdens. Equities remain vulnerable to geopolitical shocks, regulatory intervention, and sudden swings driven by artificial intelligence optimism or macroeconomic fears.

At the same time, inflation has fundamentally altered how wealthy investors think about preserving purchasing power. Families with multigenerational wealth are increasingly focused on maintaining real value rather than chasing aggressive growth.

This shift has become especially visible among family offices, which collectively manage trillions of dollars globally. Unlike institutional investors constrained by quarterly performance targets, family offices often prioritise long-term strategic positioning over short-term returns.

That flexibility is allowing them to move more aggressively into alternative assets.

Private Credit Emerges as a Preferred Asset Class

One of the clearest winners from this shift has been private credit.

As banks face tighter regulations and reduced risk appetite following years of financial reform, private lenders have stepped into the financing gap. Wealthy investors are increasingly allocating capital to direct lending funds, specialty finance platforms, and private debt vehicles that offer higher yields and stronger downside protection than many traditional fixed-income products.

Private credit has become particularly attractive because it offers predictable cash flow during uncertain market conditions. Many family offices view direct lending as a way to generate income while maintaining greater control over risk exposure.

The appeal has grown further as borrowers increasingly seek non-bank financing solutions. Middle-market companies, infrastructure projects, renewable energy developers, and real estate operators are all turning to private lenders for capital.

For wealthy investors, the sector provides not only returns but also influence. Unlike public markets, private credit transactions often allow investors to negotiate terms directly, obtain collateral protection, and maintain visibility into underlying assets.

This level of control is becoming increasingly valuable in a world where macroeconomic shocks can rapidly destabilise public markets.

Climate Investments Are Becoming Strategic, Not Symbolic

Sustainable investing has also evolved significantly among wealthy families.

A decade ago, environmental, social, and governance investing was often viewed as a branding exercise or ethical overlay. Today, many family offices see climate-linked investments as strategic necessities tied to future economic competitiveness.

This change is driven partly by regulation and partly by economics.

Governments worldwide are directing enormous capital toward energy transition projects, clean infrastructure, battery supply chains, carbon markets, and climate resilience technologies. Wealthy investors increasingly believe these sectors will define the next phase of global industrial growth.

Importantly, many family offices are not merely investing through passive ESG funds. They are taking direct stakes in infrastructure assets, private climate technology firms, and long-duration sustainability projects.

This approach reflects a broader preference for tangible investments with strategic value.

Real assets linked to energy security, food production, and critical infrastructure are now viewed as essential geopolitical hedges as much as financial investments.

Geopolitical Diversification Is Reshaping Capital Allocation

Geopolitical risk has become one of the defining themes influencing global wealth management.

The fragmentation of globalisation is forcing wealthy families to reconsider where they store capital, hold citizenship, establish businesses, and invest assets.

Many investors are increasingly diversifying not only across asset classes but also across political systems and geographic jurisdictions.

This trend has accelerated following sanctions disputes, trade wars, banking crises, and rising tensions between major powers, including the United States and China.

For wealthy families, concentration risk now extends beyond markets into governments and regulatory regimes.

As a result, family offices are increasingly expanding operations into financial hubs perceived as politically stable and globally connected, including Singapore, Dubai, Switzerland, and parts of the Gulf region.

Cross-border diversification now includes multiple dimensions:

• Multi-currency exposure
• International property ownership
• Alternative residency programmes
• Overseas banking relationships
• Distributed business operations
• Strategic commodity investments

The rise of geopolitical hedging reflects growing concern that financial systems themselves are becoming politicised.

Sanctions, capital controls, taxation changes, and trade restrictions are no longer viewed as isolated risks. They are increasingly incorporated into long-term wealth planning.

Real Assets Are Regaining Strategic Importance

Another major shift involves the growing appeal of hard assets.

Farmland, logistics infrastructure, energy assets, ports, data centres, and industrial real estate are increasingly viewed as defensive investments capable of preserving value during periods of inflation and geopolitical stress.

Data centres, in particular, have become highly attractive due to the rapid expansion of artificial intelligence infrastructure and cloud computing demand.

Similarly, agricultural assets are gaining attention amid concerns about food security, water scarcity, and supply chain disruption.

Many wealthy investors now prioritise assets that generate both stable income and strategic relevance.

This represents a departure from purely financialised investment models toward ownership of critical infrastructure tied to long-term economic necessity.

The trend is particularly strong among Middle Eastern and Asian family offices, many of which are aggressively acquiring stakes in logistics corridors, renewable energy projects, healthcare infrastructure, and technology ecosystems.

Why Private Banks Are Reinventing Their Wealth Businesses

The transformation in investor behaviour is forcing major global banks to adapt rapidly.

Institutions such as UBS, JPMorgan Chase, and HSBC are increasingly repositioning their private banking divisions around alternative investments, family office services, geopolitical advisory capabilities, and customised wealth planning.

Traditional portfolio management alone is no longer sufficient for many ultra-wealthy clients.

Instead, private banks are being asked to provide highly specialised services, including:

• Access to private markets
• Co-investment opportunities
• Cross-border tax planning
• Succession structuring
• Political risk analysis
• Climate investment advisory
• Digital asset infrastructure
• Family governance consulting

Banks are also investing heavily in technology and artificial intelligence to improve personalisation and operational efficiency within wealth management.

At the same time, competition for wealthy clients is intensifying.

Independent family offices are becoming more sophisticated and increasingly capable of managing investments internally. This pressures banks to justify their fees through exclusive deal access and strategic expertise rather than conventional advisory alone.

The acquisition of Credit Suisse by UBS highlighted the growing importance of scale in global wealth management. Larger institutions are seeking to consolidate client assets while expanding their alternative investment capabilities.

Meanwhile, banks in Asia and the Middle East are aggressively competing to attract internationally mobile wealth.

The Rise of the Global Family Office

Perhaps the most important structural change is the rise of the institutionalised family office.

Historically, family offices primarily handled administrative and estate matters for wealthy dynasties. Today, many operate as highly sophisticated investment organisations with direct exposure to private equity, venture capital, infrastructure, and geopolitically strategic sectors.

Some family offices now rival major institutional investors in scale and influence.

This evolution reflects both opportunity and necessity. Wealthy families increasingly believe they must take greater control over investment strategy rather than rely solely on external managers.

The modern family office is often deeply global, technologically advanced, and politically aware.

It may include specialists in cybersecurity, artificial intelligence, climate science, tax law, and geopolitical analysis alongside traditional investment professionals.

Importantly, younger generations are also influencing priorities.

Millennial and Gen Z heirs often place greater emphasis on sustainability, technology, social impact, and long-term resilience compared to previous generations focused primarily on capital accumulation.

This generational transition is accelerating changes in portfolio construction and investment philosophy.

Technology, AI, and the New Wealth Infrastructure

Artificial intelligence is also reshaping wealth management itself.

Private banks and family offices are increasingly using AI tools for portfolio analysis, risk modeling, operational automation, and personalised financial planning.

However, AI is also influencing investment strategy more broadly.

The enormous infrastructure requirements tied to AI expansion are creating investment opportunities in semiconductors, energy grids, cooling systems, fiber optics, cloud infrastructure, and data centres.

Wealthy investors increasingly see AI not only as a technological trend but also as a long-term industrial transformation requiring massive capital deployment.

This explains why family offices are increasingly allocating money toward infrastructure linked to digitalisation and computing power.

At the same time, AI-driven market volatility and rapid technological disruption reinforce concerns about concentration risk in public equities.

For many wealthy families, owning underlying infrastructure appears safer than betting solely on technology stocks.

A New Era of Defensive Capitalism

Ultimately, the shift underway among wealthy families reflects the emergence of a more defensive form of capitalism.

The goal is no longer simply maximising returns during an era of expanding globalisation and cheap capital. Instead, the focus has shifted toward resilience, strategic positioning, and long-term wealth preservation amid fragmentation and uncertainty.

This does not mean wealthy investors are abandoning growth opportunities. Rather, they are becoming more selective, more global, and more politically conscious in how they deploy capital.

Private credit, infrastructure, sustainable assets, geopolitical diversification, and strategic real assets all serve a common purpose: reducing vulnerability to systemic shocks while preserving flexibility.

The implications for the broader financial industry are profound.

Banks, asset managers, and advisory firms must increasingly operate not just as investment providers but as strategic partners capable of navigating geopolitical complexity, technological disruption, and climate transition.

In many ways, the future of wealth management is becoming less about outperforming benchmarks, and more about surviving an increasingly unpredictable world.

For the world’s wealthiest families, capital preservation is no longer passive. It is becoming an active geopolitical strategy.

The post Where are World’s Wealthiest Families Investing appeared first on International Finance.

The reason for this is that EPR doesn’t just charge you for the volume of packaging you place on the market; it charges you based on how that packaging is designed, how recyclable it is, and how accurately it’s reported. That means two organisations with similar products can end up paying very different fees, depending on how well they understand and manage their data.

This is where many businesses are missing value. Packaging data is often incomplete, inconsistent, or pulled together at the last minute. Materials get grouped into broad categories, assumptions are made to fill gaps, and in some cases, packaging is effectively treated as ‘worst case’ just to ensure compliance. The result is that organisations can default into higher fee categories without realising it, paying more than they need to year after year.

An EPR assessment changes that. It looks beyond submission and focuses on what’s genuinely increasing cost. Through analysing packaging formats, increasing data accuracy, and identifying where materials fit within recyclability criteria, inefficiencies can be identified, and exposure to higher fees reduced. It is about turning ambiguous data into unambiguous decisions and, in many cases, high-cost packaging into lower-cost alternatives.

As EPR reporting requirements continue to evolve, the organisations that treat EPR as a cost lever rather than a compliance exercise will be in a much stronger position. Not just to stay compliant, but to actively reduce costs and make more informed packaging decisions over time.

The Growing Financial Impact of EPR

One of the most significant developments within EPR is the introduction of modulated fees, which are designed to reflect the recyclability of packaging materials. From April 2026, these fees will be adjusted using the Recyclability Assessment Methodology (RAM), a framework that assigns each packaging format a recyclability rating. This marks a clear shift in direction, moving away from flat or generalised cost structures toward a more targeted approach that incentivises better packaging design.

Under RAM, packaging is assessed and categorised using a Red, Amber, or Green (RAG) rating system. Red-rated packaging is considered difficult to recycle, often due to material composition, lack of infrastructure, or contamination risks. Amber-rated packaging represents transitional materials, which may be recyclable under certain conditions but are not yet widely supported. Green-rated packaging, on the other hand, is widely recyclable and aligns with existing collection and processing systems.

This classification system has direct financial consequences. Packaging that falls into the Red category will incur increasing surcharges over time, with a 20% increase applied in 2026–27, rising to 60% in 2027–28, and reaching 100% by 2028–29. In contrast, Green-rated packaging will benefit from reduced fees, with the exact level of discount determined by the scheme administrator. This structure is designed to encourage organisations to move away from difficult-to-recycle materials and toward more sustainable alternatives.

While the intention of this system is to support the transition to a circular economy, it also introduces a level of financial exposure that many organisations have not previously had to manage. Packaging decisions that were once driven by cost, functionality, or branding, must now also account for recyclability and compliance costs. As a result, businesses that do not fully understand how their packaging is assessed may find themselves facing higher fees than expected.

Why Many Organisations Are Overpaying

Despite the increased focus on EPR, many organisations are not yet fully equipped to manage these new requirements efficiently. EPR reporting often relies on data that is inconsistent or incomplete. Packaging information may be stored across multiple systems, owned by different departments, or sourced from suppliers who do not provide the level of detail required for accurate reporting.

This creates several areas where unnecessary costs can arise. In some cases, organisations may over-report packaging volumes due to duplication or conservative assumptions, leading to inflated fees. In others, materials may be incorrectly classified, resulting in packaging being assigned a higher-cost category than necessary. There may also be gaps in data, particularly for imported goods, where visibility over packaging composition is limited.

These challenges are compounded by the fact that EPR reporting requirements are still evolving. As guidance becomes more detailed and enforcement increases, the margin for error is reduced. What may have been acceptable in earlier reporting cycles may no longer meet the required standard, increasing the risk of non-compliance or financial penalties.

Without a structured approach, organisations can find themselves reacting to EPR requirements rather than managing them proactively. This can increase the administrative burden and make it more difficult to identify opportunities for cost reduction.

The Role of an EPR Assessment

An EPR assessment provides a structured way to address these challenges by bringing together data, processes, and packaging design into a coherent view. It allows organisations to understand how their packaging decisions translate into reporting requirements and into cost.

The first step in an EPR assessment is typically to establish an understanding of your obligations. This involves reviewing your products, packaging formats, and market activities to determine which regulations apply, and what data needs to be reported. For organisations operating across multiple regions, this can be particularly important, as requirements may differ between jurisdictions.

Once obligations are defined, the focus shifts to data collection and validation. This involves gathering detailed information on packaging materials, weights, and formats, and ensuring that this data is accurate and consistent. In many cases, this process highlights discrepancies or gaps that would otherwise lead to incorrect reporting.

From there, the assessment can begin to identify cost drivers. By mapping packaging formats against RAM criteria, it becomes possible to see which materials are likely to attract higher fees, and where there may be opportunities to improve recyclability. This does not necessarily require a complete redesign of packaging. In many cases, relatively small changes, such as simplifying material composition or improving labelling, can have a tangible impact on recyclability scores.

Reducing Costs Through Better Data

One of the most immediate benefits of an EPR assessment is improved data quality. While this may seem like an operational detail, it has a direct impact on cost. Accurate data ensures that organisations are only reporting what is required, avoiding overpayments caused by duplication or incorrect assumptions.
It also enables more precise classification of packaging materials. Rather than defaulting to higher-cost categories due to uncertainty, organisations can confidently assign materials based on verified information. This reduces the risk of overpaying while also supporting more robust compliance.

In addition, better data creates a stronger foundation for future reporting. As EPR reporting requirements become more detailed, organisations with well-structured data systems will be better positioned to adapt. This reduces the time and effort required for each reporting cycle, lowering administrative costs and freeing up internal resources.

Influencing Packaging Design Decisions

Beyond data, an EPR assessment also provides valuable insight into how packaging design influences cost. By understanding how different materials and formats are assessed under RAM, organisations can make more informed decisions about future packaging strategies.

This does not mean that all packaging must immediately shift to Green-rated materials. In many cases, there are practical constraints related to product protection, supply chain requirements, or customer expectations. However, having visibility over the cost implications of different options allows organisations to make balanced decisions that consider both functionality and compliance.

Over time, this can lead to a more strategic approach to packaging design. Rather than reacting to regulatory changes, organisations can plan ahead, gradually transitioning toward more recyclable formats and reducing their exposure to increasing fees. This supports compliance and aligns with broader sustainability objectives.

Streamlining Internal Processes

Another important aspect of an EPR assessment is the opportunity to improve internal processes. EPR reporting often involves multiple teams, including procurement, operations, sustainability, and finance. Without coordination, this can lead to inefficiencies, duplicated effort, and inconsistent data.

Organisations can reduce these inefficiencies by developing structured processes for data collection, validation and reporting. This could involve standardised templates, specific roles and responsibilities, and systems for tracking packaging data over time. Although these changes may seem operational in nature, they are an important part of making sure that EPR reporting is accurate and efficient.

Moreover, optimised workflows allow for scalability over time. As organisations grow or expand their footprint in new markets, a consistent approach to EPR means it is easier to manage additional reporting obligations and does not introduce significant complexity.

Looking Beyond Compliance

While the primary driver for EPR is regulatory compliance, the process of assessing and improving packaging data can deliver wider benefits. Organisations that take a proactive approach often find that they gain a deeper understanding of their packaging footprint, including material usage, waste generation, and opportunities for improvement.

This insight can support a range of broader objectives, from reducing environmental impact to improving operational efficiency. It can also strengthen engagement with suppliers, as organisations work collaboratively to obtain more accurate data and explore alternative materials.

In this sense, EPR can act as a catalyst for change. Rather than being seen solely as a compliance burden, it can provide a framework for making more informed and sustainable decisions.

Preparing for What Comes Next

As EPR reporting requirements continue to develop, the expectations placed on organisations are likely to increase. This includes more detailed data requirements, stricter enforcement, and greater alignment with international frameworks. For organisations that are not yet fully prepared, this presents both a challenge and an opportunity.

An EPR assessment offers a way to get ahead of these changes by establishing a clear understanding of your current position, and identifying practical steps for improvement. By addressing data quality, refining packaging design, and streamlining processes, organisations can reduce their exposure to rising costs while building a more resilient approach to compliance.

The value of an EPR assessment ultimately becomes that it makes a complex and evolving requirement manageable. It offers clarity, structure and actionable insight that enable organisations to shift from reactive compliance to a more strategic approach that not only meets regulatory expectations but generates tangible commercial benefits over time.

The post EPR is not a pain, but a means to reduce packaging cost appeared first on International Finance.

This near-universal smartphone ownership, as well as top-end phones costing over £1,200, and the UK facing a sharply escalating phone theft crisis, is driving up consumer demand for gadget insurance, as the latest figures from the Financial Conduct Authority (FCA) show. Indeed, the number of gadget insurance policies in the UK increased from 7.87 million in 2023 to 8.46 million in 2024, representing annual growth of 7.5%.

The financial opportunities are clear, yet they aren’t without growing pains.

In the gadget insurance market, Gen Z and millennials have become a key growth demographic. Coverage for smartphones and other devices is often the first policy that young customers will purchase, providing insurers with a prime opportunity to build brand loyalty early.

Those positive brand perceptions rely on providing fast, transparent, digital claims journeys akin to the instant services that younger, tech-savvy individuals use every day. However, insurers must balance providing leading customer experiences with a growing fraud challenge.

According to FCA General Insurance Value Measures data, UK gadget insurance gross written premium income increased from £496 million in 2023 to approximately £604 million in 2024, representing a 22% year-over-year increase, which in large part was driven by rising device costs and a typical claims’ frequency of 5-15%. With close to 8.5 million policies in place, that translates to hundreds of thousands of claims per year, with an estimated 660,000 in 2024.

With a fraudulent claims rate of 15%, approximately 99,000 fraudulent gadget insurance claims may have occurred in 2024 alone. With the UK market seeing typical payouts of £435 per claim, this would translate into a financial impact of more than £40 million in just one year. That’s before the operational costs of processing those claims are factored in.

The dual challenge facing gadget insurers

Stamping out this fraud is naturally a leading priority for insurers. However, in the UK market, this can be difficult to achieve.

Since ‘lost’ claims typically do not require a police report or crime reference number, stolen and damaged phones are often reported as ‘lost’ to avoid having to submit either police documentation or the device itself for inspection and repair.

Equally, while insurers have historically used rules-based profiling checks such as document review, assessing claims by requesting proof of purchase receipts, and confirmation with the network provider of where and when the device was last used, such methods are becoming increasingly at odds with both modern fraud and the expectations of modern customers.

Advances in AI, for example, have made it easier to generate fabricated invoices, receipts, and supporting materials. At the same time, documentation checks often involve back-and-forth communications that can frustrate customers. Manual validation is slow and bureaucratic, while Gen Z customers expect the same instant decisions they’re used to with other digital services.

As a result, insurers are left facing a two-pronged challenge. Gen Z customers expect rapid, often same-day resolutions – particularly as we all virtually run our lives on these devices. Yet, insurers cannot afford to relax fraud detection controls despite the fact that they are slow, resource-intensive, and limited in their ability to detect modern forms of opportunistic gadget insurance fraud.

A further complication lies in the fact that many legacy fraud checks are both reactive and evidence-led. They focus on whether supporting documentation exists rather than validating whether the claim itself is genuine, which creates scope for fraud to creep in. A customer may provide a valid invoice or a plausible account of events, while still misrepresenting how or when a device was actually lost or damaged.

The argument for modernised assessments

There are several structural safeguards beyond document reviews in place.

The Recipero database, for example, allows insurers to validate unique IMEI numbers against sales and recycling databases, as well as other insurers to mitigate the risk of duplicated claims. Network data requests can also verify when a phone was last used to validate claimed loss dates, while exclusion or ‘waiting’ periods can prevent customers from making a claim immediately after buying an insurance policy.

However, these measures are not foolproof. Consumers can still exploit timing gaps by taking out contracts and claiming losses shortly after the exclusion period ends.

Insurance is a two-way trust relationship between the consumer and the insurer. The insurer needs to trust that the consumer is providing accurate information about the device at the point that the policy is purchased, and in the situation that a claim needs to be made. Equally, the consumer needs to trust that the insurer is charging a fair price for the cover that is being provided, and that any claims will be handled expediently and fairly.

Clearly, fraud committed by a proportion of consumers challenges the trust element. Meanwhile, existing fraud detection processes clearly aren’t entirely effective, and they also create unnecessary friction and delays for genuine customers when they most need their claim handled efficiently and quickly
One way to address the dilemma is to look outside the industry at how other sectors address this ‘trust screening’ challenge, with one innovative approach being voice-based risk assessment.

Human vocal characteristics associated with risk are universal, regardless of language, geography, culture, or other demographics. By analysing these voice-based characteristics through a short series of simple yes-or-no questions, insurers can rapidly identify potential indicators of misrepresentation in real time, meaning that genuine applications for a policy and claims can be fast tracked with those consumers receiving a much more elevated level of service.

Rather than treating every claimant as a potential fraudster until proven otherwise, many insurers are adopting technologies designed to quickly identify low-risk customers and allow straightforward claims to move faster, while reserving deeper investigations for the smaller number of cases that genuinely warrant additional scrutiny. Technologies such as voice-based risk assessment, AI-assisted claims routing, and document verification tools are transforming insurance assessments, deterring fraudulent behaviour, while accelerating the resolution of low-risk claims.

Crucially, new approaches align with Gen Z expectations for near-same-day resolutions by enabling insurers to balance speed with robust fraud detection.

Ensuring regulatory alignment

Ultimately, this is about addressing fraudulent claims that create disproportionate financial damage, either by prompting those customers to think twice, or by identifying them more effectively. These technologies detect risk in ways that traditional methods cannot, focusing on confident triage where potential risk is flagged, while remaining transparent and defensible under regulatory scrutiny.

With that said, as with any technology adoption, implementation must be guided by responsibility as well as effectiveness. This is especially important in a large, regulated, and operationally complex market where decision accuracy, trust, and defensibility directly impact financial performance and reputation. The FCA’s Consumer Duty, for example, expects regulated companies to have controls to protect customer data, and prevent fraud from arising from misuse of PII.

For insurers, the challenge is not simply to prevent fraud, but to do so in a way that preserves the customer experience. In the case of Gen Z, that means meeting demands for speed, convenience, and fairness, with this demographic being quick to disengage when such demands aren’t met.

Long term, that is the key to building the trust that underpins sustainable, mutually beneficial customer relationships.

The post Meeting Gen Z demands while preventing fraud in gadget insurance appeared first on International Finance.

Traditional recurring payment models are still built around fixed schedules and fixed amounts, which often fail to reflect how people are paid or manage their money. Commercial Variable Recurring Payments (cVRPs) are, therefore, emerging as a foundation for the next phase of account-to-account payments, enabling variable amounts, customer-set caps, and explicit consent.

That opportunity is now underpinned by a more practical market framework. Since early June, the UK Payments Initiative (UKPI) has moved commercial VRP into live operation through a multi-lateral agreement, shared rulebook and common commercial model, reducing the need for providers to negotiate bank by bank. Importantly, Wave 1 is deliberately focused on lower-risk, regulated or trusted sectors, including energy, utilities, telecoms, government and regulated financial services. For energy and utilities providers, this makes cVRP less of a future concept and more of an actionable route to give customers greater payment choice while improving collections, consent management and debt prevention.

With energy debt rising, the timing matters. Energy UK forecasts that household energy debt could reach £7bn by the end of the year, up from Ofgem’s reported £4.5bn in Q1. As bills remain under pressure, suppliers need to support debt prevention and reduce the risk of escalation, rather than relying mainly on recovery once arrears have built up.

Where current payment models fall short

Customers typically have three choices for bill payments: direct debit, standard credit or prepayment. Each has strengths, but none fully reflects the financial reality faced by many households.

Direct debit works well for many households, but its rigidity can be a weakness. If a customer has £90 available and a £100 bill is due, the system takes nothing rather than a partial payment. The result can be arrears, stress and disengagement. Although 72% of households use direct debit for energy bills, it can be poorly suited to those with uneven cashflow, including the large proportion of the UK workforce that is not salaried.

Standard credit gives flexibility in theory, because customers pay when billed. In practice, large bills can arrive at the wrong point in a customer’s income cycle, and be deferred or ignored. It also carries a cost premium: households paying this way face around £131 more a year than those paying by direct debit, and many consumers are unaware of that gap. Energy UK estimates that standard credit accounts for around half of debt.

Prepayment can help customers monitor spending, but when funds run out, so does access to energy. That makes it an imperfect substitute for households needing flexibility rather than disconnection risk.

The gap is clear: customers need a flexible, variable payment alternative that reflects modern income patterns while helping providers reduce preventable debt.

Commercial Variable Recurring Payments, and why they present an opportunity

cVRPs offer a more adaptable alternative: consent-based payments with variable amounts, customer-defined caps and greater user control. They can support intelligent flexible payments where timing or amount needs to vary, or allow customers to break payments into smaller amounts that better match their financial situation.

For people with inconsistent monthly income, cVRPs can combine the convenience of direct debit with greater flexibility. Through open banking, they can also underpin secure, permissioned insight to support better timing, clearer prompts and more responsive payment journeys.

Successful cVRP utilisation

cVRPs are a hugely promising payment technology for both customers and businesses but making them work in practice depends on disciplined deployment across four key pillars:

• A simple, trustworthy customer consent journey: Customers must understand what they are agreeing to, their payment limits, when they will be prompted, and how to change or cancel the arrangement. If the journey is unclear, adoption will be weak, and bills are more likely to remain unpaid.
• Smarter prompting and timing: Payments should be requested when they are most manageable for the customer, rather than on a fixed collection date. Open banking can help identify better moments to prompt payment.
• Strong controls, exception handling and service operations: Providers must plan for ignored prompts, disputes, failed or partial payments, and integration with customer service and back-office systems.
• Data-led intervention and vulnerability identification: Payment insight can help providers identify temporary friction, financial distress, or emerging vulnerability earlier, then offer suitable options, or route customers to support more quickly.

When these pillars are in place and underpinned by the benefits of cVRP, intelligent flexible payments can create value for both sides. Customers gain more suitable options, and a stronger sense of control.

Providers can reduce payment failures, improve cashflow, and lower servicing and recovery costs, which are ultimately reflected in consumer bills. Moneyline has reported that customers using this capability for credit repayments experienced a 10% reduction in arrears compared with those using direct debit.

The opportunity is now

As cVRPs move from principle to deployment, they can change how recurring payments are managed. The question is whether organisations, particularly in sectors such as energy with high levels of recurring billing and debt risk, can deploy them in a way that is trusted, operationally resilient and designed around customer need. If they can, the industry has an opportunity to shift from debt recovery to debt prevention in an intelligent and flexible way.

The post Intelligent Flexible Payments: An Innovative Solution to Preventable Debt appeared first on International Finance.

The trigger was a new category of advanced AI model, a system capable of identifying and exploiting software vulnerabilities faster than human security teams can detect them, let alone respond. These models have demonstrated the ability to produce working exploits on their first attempt in the majority of attempts during controlled testing. In some evaluations, they managed to clear expert-level cybersecurity benchmarks that no previous AI system could pass as recently as a year ago. The ECB’s message to eurozone banks was blunt: patch faster, govern better and act now.

The Access Asymmetry Problem

There is a structural problem at the centre of this situation that demands direct attention. The most capable AI systems for discovering vulnerabilities – the same systems now defining the threat horizon – have been made available to a small group of organisations, predominantly based in the United States. That group includes major hyperscalers, large cybersecurity firms and a number of significant American financial institutions. It does not include any European bank.

The ECB supervises 111 of the largest eurozone banks. As of the time of this meeting, none of them had access to the frontier models regulators are asking them to defend against. Elderson acknowledged the gap directly, calling the disparity ‘unfortunate’ while making clear it cannot justify inaction.

European banks are facing an obligation to build defences against attack capabilities they have not yet been permitted to evaluate. That’s an uncomfortable position, one which regulators have made explicit.

The asymmetry is not a temporary administrative inconvenience because it carries material implications for how European banks plan, test and invest in their security posture. Defensive programmes built on yesterday’s threat models will inevitably fail against adversaries who are using today’s offensive tools.

No Room for Hesitation: ECB Expectations

ECB Vice-President Luis de Guindos has been equally clear that the pressure applies universally, not just in the largest institutions. Every supervised bank both large and small will need to spend significantly more on cybersecurity to keep pace. That is a structural shift in the cost base of operating a regulated financial institution in Europe.

The practical expectations are well-defined, but the implementation demands considerable scrutiny and effort. Banks are being asked to accelerate software patch cycles, given that advanced AI models can reverse-engineer fixes within minutes of their release, and reconstruct exploitable vulnerabilities from the patch itself. The already narrow window between disclosure and exploitation has effectively collapsed. Banks operating on monthly or quarterly patching cycles are running an exposure risk they can no longer afford.

Beyond the patching cycle, the ECB’s intervention reinforces obligations that already existed under the EU’s Digital Operational Resilience Act (DORA), which came into effect in January 2026. DORA places binding requirements on financial entities to manage Information and Communication Technology (ICT) risk, govern third-party dependencies, and demonstrate operational resilience. Institutions that treated its introduction as a compliance exercise rather than a structural prompt are now receiving a second, harder signal. Resilience frameworks must now be reassessed through the lens of AI-driven attack scenarios, including recovery testing and incident response.

UK banks are facing a parallel dynamic. A joint statement from the Financial Conduct Authority, the Bank of England and His Majesty’s Treasury stopped short of implementing new rules, but it did sharpen expectations considerably under existing operational resilience frameworks. That statement noted that these latest AI systems are already performing certain cyber tasks beyond what individual skilled practitioners can achieve, and at far greater speed. The expectation is that continuous testing must replace scheduled cycles.

The Financial Sector’s Identity Crisis

Regulation is effective for directing attention, but it cannot substitute for actual structural remediation. The vulnerabilities that advanced AI models are most effective at exploiting are the accumulated effects of poor identity governance at scale.

Research conducted across 3,200 IT and security professionals globally reveals the underlying weakness. Among finance sector respondents, 75% found managing the growing number of identities – both human and non-human – at least moderately challenging. Finance sector professionals also rated the governance of AI-driven access and automation as a top security gap (45%). Globally AI-related Non-Human Identity (NHI) Management ranked among the top three AI security concerns.

These metrics underline a genuine gap in governance. Every AI agent, automated workflow and machine account introduced into a financial institution creates an NHI that requires privileged access to function. Those identities are routinely provisioned quickly, governed poorly, and rarely revoked with the same rigour applied to human accounts. In a traditional threat environment, that was a meaningful but manageable risk. In an environment where advanced AI can systematically probe every access point at machine speed, it becomes a critical one.

Keeper research points to where finance sector institutions are investing in response to this new threat environment. Improved monitoring and detection of identity-based threats was the most notable area of increased implementation over the past 12 to 18 months, cited by 45% of finance sector respondents. That’s notably higher than the global average of 38%. Passkey and passwordless adoption are being prioritised at above average rates. Both trends are the right direction of travel.

Closing the Gap

The institutions that will convert regulatory pressure into genuine resilience are those that treat identity governance as operational infrastructure rather than a compliance layer. That means enforcing least-privilege access across every AI agent and automated process, extending privileged access management to cover machine credentials and secrets, and building continuous governance into how access is provisioned, monitored and revoked.

The ECB’s intervention is significant because it calls out a present-day obligation rather than a future risk. Advanced AI has already altered the threat landscape. Yes, the access asymmetry between European banks and the frontier models shaping the environment is real. What banks can control, however, is the rigour of the security architecture they build in response.

The post European banks have been banking on borrowed time appeared first on International Finance.

International Finance asked Susannah Streeter, the Chief Investment Strategist at Wealth Club, the United Kingdom’s largest non-advisory investment service for high net worth and experienced investors, whether Wall Street will be able to absorb the IPOs of SpaceX, OpenAI and Anthropic, whose combined valuations may exceed $3.5 trillion.

Here are some excerpts from the interview:

With more than 200 IPOs in Q1 2026 and listings from SpaceX, Anthropic and OpenAI, can Wall Street absorb the likely IPO issuance associated with companies whose combined valuations may exceed $3.5 trillion?

Wall Street has shown a remarkable capacity to absorb huge amounts of capital when investor enthusiasm is running high, and right now AI is proving a powerful magnet for money. However, even deep capital markets have limits. If several mega-listings arrive in quick succession, as we are seeing, competition for investor attention and capital could intensify. The appetite appears strong, but the scale of these offerings means there may well be a test of demand, especially if market sentiment turns.

Given the strong IPO activity in Q1 2026, can we say Wall Street has fully recovered from the slowdown of 2023–24?

The rebound in IPO activity suggests confidence has returned, but it’s probably premature to declare a full recovery. Much of the momentum has been concentrated around a relatively narrow group of companies linked to artificial intelligence and other high-growth themes. A truly broad-based recovery would require robust issuance across multiple sectors and market capitalisations, not just a handful of headline-grabbing deals.

Are the IPOs of SpaceX, Anthropic, and OpenAI evidence that the AI investment boom is becoming concentrated in a handful of dominant players?

There are certainly signs that capital is gravitating towards a small group of companies perceived as having the scale, talent and computing power needed to dominate the AI race. Investors increasingly appear willing to pay a premium for firms controlling critical infrastructure, foundation models, and distribution networks. However, technological revolutions rarely follow a straight line. The rules of the AI race are evolving so quickly that some of tomorrow’s winners may still be under the radar. That’s why investors need to remain selective, diversified and realistic about risk.

Could mega-IPO listings, such as SpaceX and Anthropic, divert capital away from existing tech stocks, smaller AI firms, and other speculative assets like cryptocurrencies?

Large IPOs often trigger portfolio reshuffling as investors free up capital to participate in highly anticipated listings. Given the scale and profile of these companies, some rotation away from existing technology holdings and more speculative corners of the market isn’t surprising. Crypto is feeling the whiplash effects of AI enthusiasm and volatility.

It’s winter in the crypto world, with Bitcoin falling roughly 50% from its late-2025 peak of over $126,000. This steep decline has been triggered by massive ETF outflows. Although the sell-off intensified after the most recent wobble on the Nasdaq, it’s a multi-month trend, and has occurred as the AI trade has been played hard. It’s likely that some crypto money has been released to buy equities.

Even if existing shareholders retain most shares, could institutional demand for SpaceX and Anthropic create a significant liquidity and capital-allocation shock in the market?

The biggest impact may come less from the number of shares available and more from the scramble among institutional investors to gain exposure. When companies of this size and prominence come to market, fund managers often feel pressure not to be left behind. That can create significant shifts in capital allocation, particularly if several mega-listings arrive within a relatively short period.

Is Wall Street underestimating the risks of investing in long-term, capital-intensive ambitions such as SpaceX’s plans for Mars colonisation and space-based infrastructure?

What we’ve been seeing in this intense period of market enthusiasm is investors focusing more heavily on future opportunities than present-day risks. SpaceX’s ambitions are stratospheric and potentially transformative, but they are also highly capital-intensive and dependent on technological breakthroughs, regulatory approvals and long-term execution.

Investors will need to balance the excitement of the vision against the realities of the investment horizon. One risk that isn’t being paid much attention to is the potential for geopolitical tensions to spill into the space domain. Space based infrastructure like satellites could become increasingly vulnerable, and we could see degradation of critical satellite networks through cyber-attacks, electronic warfare, jamming, or even direct anti-satellite actions.

How should investors evaluate SpaceX’s IPO given its substantial revenue growth but continued net losses?

The key question is likely to be whether investors view current losses as a by-product of aggressive expansion, or as a sign of structural challenges. Many high-growth companies have prioritised investment over profitability during periods of rapid scaling. Investors are likely to focus closely on revenue quality, cash generation potential, and the extent to which SpaceX can turn its technological leadership into sustainable long-term returns.

Should investors be concerned that Elon Musk is expected to retain overwhelming voting control of SpaceX even after the company goes public?

Dual-class and founder-controlled structures have become increasingly common among large technology companies, particularly where founders argue that long-term innovation requires protection from short-term market pressures. However, concentrated voting control inevitably raises governance questions because it limits the influence of minority shareholders. Investors will need to decide whether confidence in the leadership and strategy outweighs concerns about accountability.

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Could Anthropic’s public warnings about the risks of advanced AI conflict with its decision to pursue an IPO, and raise additional capital?

Anthropic’s position has generally been that advanced AI development should be accompanied by strong safeguards and responsible oversight. Right now, regulators are still playing catch up, and there are crucial questions about AI adoption for societies to answer.

Pursuing an IPO and raising capital could be viewed as part of building the resources needed to develop and govern increasingly sophisticated systems. Being responsible about people and the planet is generally considered to be a sound investment strategy, and one which should be applauded. Nevertheless, there is likely to be scrutiny of how the company balances commercial growth with its stated commitment to AI safety.

The post Premature to declare a full recovery for Wall Street: Susannah Streeter appeared first on International Finance.

When renowned economist Javier Milei won Argentina’s presidency in late 2023, he came armed with a chainsaw. Not a literal one, though he had famously wielded one on the campaign trail. The chainsaw was a metaphor for what he promised to do to the Argentine state: cut it down, fast and without mercy.

Nearly two-and-a-half years into his presidency, that chainsaw has done real damage to government spending. Whether the cuts have healed the patient or simply reduced the bleeding while leaving deeper wounds untreated is the central question facing Argentina today.

The honest answer is, both things are happening at once. At the national accounts level, Argentina looks better than it has in years. Investors are calmer. The currency has stabilised. The government is, for the first time in almost two decades, spending less than it earns. But zoom in from that altitude, and a different picture emerges.

Factories are running at half capacity. Small businesses are filing for bankruptcy at record rates. Ordinary Argentines are putting groceries on credit cards because their wages have not kept pace with prices. The country is experiencing a split reality, and understanding that split is essential to understanding where Argentina goes from here.

The Surplus and What It Cost

For most of its modern history, Argentina spent more than it collected in taxes. The gap was filled by printing money, which fed inflation, which eroded savings, which triggered crises. The most devastating of these came in 2001, when a rigid currency peg to the US dollar, years of fiscal deficits, and a mountain of foreign debt combined to produce the largest sovereign default in history at the time.

Banks froze deposits overnight. Five presidents came and went within two weeks. The economy contracted by nearly 11%. Recovery came slowly, driven largely by a commodity boom and debt restructuring, but the institutional scars ran deep. Milei’s government decided that ending this cycle required fiscal discipline above all else, which meant that the government must not spend more than it earns.

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By that measure, the policy has worked. In the first four months of 2026, Argentina ran a primary fiscal surplus equivalent to roughly 0.5% of GDP. Including interest costs, the country still managed a positive financial balance of around 0.2% of GDP. April 2026 marked the fourth consecutive monthly surplus of the year.

Before Milei took office, Argentina had not managed a full-year financial surplus since 2008.

These numbers came primarily from cutting spending rather than raising taxes. In fact, tax revenues have been falling in real terms for months. The government eliminated 211 public programmes across various ministries, saving roughly two billion US dollars. Public sector wages were cut in real terms. Subsidies were slashed. Infrastructure investment was curtailed. The state was made smaller, fast.

The outside world noticed. Argentina’s sovereign risk premium, which measures how much extra interest investors demand to hold Argentine debt, fell below 500 basis points for the first time since 2018, and has held roughly there since. The IMF completed its second review of a 21 billion dollar lending arrangement in May 2026, releasing a further billion dollars, and bringing total disbursements to nearly 16 billion dollars.

Restoring credibility in international markets is a genuine achievement, and a lower risk premium eventually means lower borrowing costs for businesses and households alike.

The Factory Floor is Dark

The problem is that the path to fiscal balance has run straight through the country’s productive economy, and the damage there is severe.

Argentina’s industrial sector has been contracting for over a year. The Argentine Industrial Union tracks factory performance through a monthly index where a score above 50 signals expansion, and below 50 signals contraction.

In January 2026, that index stood at 36.5 points, its fifteenth consecutive month below the neutral threshold. Industrial capacity utilisation fell to 53.8% by the end of 2025, down from 65.6% two years earlier. In the automotive sector, factories are running at just 31.2% of capacity. In textiles, rubber, and plastics, conditions are at historical lows.

What does this look like in practice? Machines sit idle. Workers are sent home early. Shifts are cut. Companies that cannot pay their bills enter legal proceedings to restructure their debts before going bust entirely.

Filings for concurso preventivo, the Argentine legal process allowing a struggling company to restructure before formally going bankrupt, have risen by more than 130% compared to the same period last year, now exceeding the levels recorded during the worst months of the Covid-19 pandemic.

Daniel Rosato, President of Industriales Pymes Argentinos, did not mince words while describing what his organisation is witnessing on the ground, “We had warned that this year we were going to arrive at the closure of more than 1,000 SMEs, but the rhythm we see in the degradation of the local economy and the presentations of concursos preventivos demonstrates that the damage to the productive framework is much worse. There is no time to debate ideologies, only to save companies and their workers, who are the ones harmed by so much inaction.”

Industry associations have petitioned Congress for emergency support through temporary freezes on debt enforcement, tax payment deferrals, and extended restructuring timelines. Without intervention, they warn, the wave of factory closures will accelerate.

The asymmetry between large and small firms is significant. Large and medium-size companies are suffering, but they have access to lawyers, financial advisors, and bank relationships that help them manage the crisis. Micro and small enterprises, which form the backbone of Argentine manufacturing and retail employment, have almost none of those buffers. Their production and sales figures are deteriorating nearly twice as fast as those of larger competitors.

The Credit Card Kitchen Table

The industrial downturn has a human face, and it sits at the kitchen table.

Argentine wages have fallen by 20% in real terms since 2018, the steepest drop of any country in Latin America over that period. By comparison, Mexican workers saw real wages rise by more than 22% over the same period. The Latin American average was a modest gain of 2%.

Under Milei, public sector workers have seen their real wages fall by more than 17% since the administration took office. Private sector workers have fared somewhat better, losing around 1.5 per cent in real terms. For households already stretched by years of wage erosion, even small additional losses are deeply felt.

The response has been to borrow. Credit card debt has doubled relative to historical averages, with delinquency rates at their highest in more than 20 years. What makes this particularly troubling is not the amount of debt itself but what it is being used for. Credit cards in Argentina were once primarily used to buy televisions or refrigerators. Now, an estimated 75% to 80% of households are using credit to buy basic food. Around 60 per cent are using debt to pay electricity and gas bills. Nearly half are borrowing to cover basic healthcare. This is not consumer finance. This is survival on credit.

Retail sales confirm the picture. Real retail volumes fell by 13.3% in March 2026 compared to the same month a year earlier. Nominal sales grew slightly, purely because prices are still rising, but the actual volume of goods purchased is shrinking steadily across nearly every category.

The Feedback Problem

Here the story gets structurally complicated, because the collapse in domestic activity is now threatening the very fiscal programme it was meant to support.

Argentina’s tax system is heavily dependent on domestic economic activity. When factories produce less and people buy less, those tax bases shrink. In April 2026, national tax revenues fell by around 4 per cent in real terms compared to April 2025, the ninth consecutive month of real decline.

Independent analysts estimate that roughly 97% of this fall is due to depressed domestic activity, not deliberate tax cuts. Export duties on beef and grains, cut in July 2025, compounded the shortfall, with receipts from those levies falling by more than 34% in real terms in April 2026.

The government’s response to falling revenues has been to cut spending further. But each additional round of spending cuts reduces economic activity, which reduces tax revenues, which requires further spending cuts.

This self-reinforcing spiral is not unique to Argentina. Many countries that pursued aggressive austerity during debt crises, including Greece in the early 2010s, found themselves trapped in precisely this loop. Argentina is living that lesson in real time.

Where the Money Goes

When Milei launched Phase 3 of his economic programme in early 2025, it liberalised the foreign exchange market significantly, removing restrictions on companies paying dividends to foreign shareholders.

Before the liberalisation, foreign companies were remitting an average of about 24 million dollars per month in profits. By early 2026, that figure had risen to an average of 333 million dollars per month, peaking at 882 million dollars in March 2026.

Between December 2023 and early 2026, Argentina generated a trade surplus of 47 billion dollars, and received foreign financing of 46 billion dollars. Yet, net international reserves rose by only about 14.7 billion dollars. The remainder was absorbed by private capital flight, debt interest payments, and profit remittances.

To attract and retain capital, the central bank must maintain high domestic interest rates, but those same rates raise borrowing costs for businesses and households, depressing the activity needed to generate tax revenues.

The Mining Future

To compensate for the contraction in domestic industry, the administration is betting on large-scale resource extraction. The Large Investment Incentive Regime, known as RIGI, offers substantial tax advantages to investors committing more than 200 million dollars. By early 2026, over 27 projects had been submitted, representing commitments exceeding 30 billion dollars, including Rio Tinto’s 2.5 billion dollar lithium project in Salta, and a 15 billion dollar copper joint venture between BHP and Lundin Mining in San Juan.

A bilateral trade agreement signed with the United States in February 2026 embeds RIGI as the primary channel for American investment in Argentine critical minerals. Over a 100 explicit legal obligations in the agreement bind Argentina to specific actions, including accepting American technical standards and modifying environmental and agricultural laws.

American commitments are largely aspirational rather than binding. Whether this arrangement allows Argentina to process raw minerals domestically rather than export them unprocessed remains a serious open question.

The Poverty Numbers and Their Limits

In March 2026, Argentina’s official statistics agency announced that the national poverty rate had fallen to 28.2% in the second half of 2025, down from a peak of 52.9% in the first half of 2024. Independent researchers have urged caution. The official measure does not reflect sharp rises in deregulated energy and healthcare costs, treats credit-financed consumption the same as wage-financed consumption, and conceals the fact that quarterly data shows poverty rising back to 32.5% in the final three months of 2025.

Community kitchens receiving public food supplies were cut from roughly 4,000 to 5,000 annually, down to 1,552 by mid-2025, worsening real food insecurity without affecting the monetary statistics. The Catholic University’s Social Debt Observatory estimates that 53.6% of Argentine children live in poverty, with 28.8% experiencing food insecurity.

The Question Ahead

Argentina in mid-2026 is a country in genuine tension with itself. The macro numbers are better than they have been in years. The micro reality, for millions of households and hundreds of thousands of small businesses, is one of sustained hardship.

Juan Pablo Filippini, an economist and PhD candidate in finance at IESE Business School, captures the distinction precisely, “Progress is not the victory lap. Argentina’s reserves are rising, sovereign risk is falling, and fiscal discipline is returning. But recovery is not measured by headlines alone. The real test is durability: stronger institutions, sustained reserve accumulation, tax compliance, and employment that catches up with growth.”

The administration has demonstrated that fiscal discipline is achievable even in a country with Argentina’s turbulent history. What it has not yet demonstrated is that fiscal discipline alone can generate the broad-based recovery that would make the hardship sustainable rather than indefinite. The path forward runs through targeted relief for small and medium businesses, a credible rebuilding of household purchasing power, and a strategy for converting booming mining revenues into domestic jobs and industrial capacity rather than profits remitted abroad.

However there is hope.

Javier Milei, said in his inaugural address at Buenos Aires on December 10, 2023, stated: “It will not be easy. One hundred years of failure cannot be undone in one day, but one day begins, and today is that day.”

Many Argentinians are clinging to this hope that the austerity measures will revive their economy to the golden age of early 20th century, when Argentina rivalled the United States of America as an economic powerhouse.

The post Argentina’s Chainsaw Balance Sheet at a Crossroads appeared first on International Finance.

It is heavy, it needs to be stored securely, and moving it across borders or between owners is slow and expensive. In a world that increasingly runs on digital speed, gold has remained stubbornly analogue.

Tokenised gold is changing that. It takes the oldest store of value in human history, and gives it a passport into the digital economy. As more of our everyday devices and systems begin talking to each other and to blockchains directly, tokenised gold may end up being just one small piece of a much larger transformation. To understand why this matters, it helps to break the concept down from the ground up.

As David Tait, CEO of the World Gold Council, put it earlier in 2026, “Gold faces a rapid and pervasive digital transformation.” In financial services, the metal must evolve to keep its place in the system.

At its simplest, tokenised gold is a digital token that represents ownership of a specific amount of physical gold. Each token is typically backed by a fixed quantity, often one gram or one troy ounce, of real gold bullion sitting in a vault somewhere in the world. The token itself lives on a blockchain, the same technology that underpins cryptocurrencies like Bitcoin and Ethereum.

Smart Contracts Explained

The link that connects the digital token to the physical metal is something called a smart contract. A smart contract is essentially a self-executing computer programme stored on a blockchain. It automatically carries out an agreement once certain conditions are met, without needing a bank, broker, or middleman to approve each step.

In the case of tokenised gold, smart contracts manage the rules around minting new tokens, transferring ownership, and redeeming tokens for physical gold. When a company issues new tokens, the smart contract typically requires proof that an equivalent amount of gold has been added to the vault.

When someone wants to redeem their tokens for actual gold bars, the smart contract handles the process of burning, or permanently removing, those tokens from circulation while triggering the physical delivery process.

This automation removes a lot of the friction and human error that traditionally came with gold trading. There is no need to physically inspect a vault every time a trade happens. The smart contract and the blockchain record do that verification work continuously.

Trust You Can Verify

Of course, none of this works without trust in the actual gold sitting in storage. This is where audited vaults come in. Companies that issue tokenised gold typically store their physical reserves in secure, professional-grade vaults, often located in established gold trading hubs.

To maintain credibility, these vaults are regularly checked by independent third-party auditors. These auditors verify that the amount of gold physically stored matches the number of tokens issued. If there are one million tokens in circulation, each representing one gram of gold, the audit confirms there really are one million grams, or one thousand kilograms, sitting in the vault.

Many issuers also allow token holders to view detailed information about the specific gold bars backing their holdings, including serial number, weight, and purity. Some go a step further by publishing real-time, or near real-time, proof of reserves, giving people an ongoing window into whether the digital tokens remain fully backed.

This question of trust sits at the heart of how the wider industry is now thinking about the asset class.

Matthias Tauber, managing director and senior partner at Boston Consulting Group, observed, “The question is no longer whether gold will be digital. It’s how it can participate in modern financial systems without compromising physical integrity.”

How Ownership Actually Works

For an everyday investor, the process of getting involved with tokenised gold is surprisingly straightforward. Most platforms allow users to purchase tokens using either traditional currency or cryptocurrency. Once purchased, the tokens sit in a digital wallet, similar to how you might hold Bitcoin or Ethereum.

From there, the tokens can be used in several ways. They can simply be held as a long-term store of value, much like owning physical gold but without the storage headaches. They can be sent to other people anywhere in the world in minutes, regardless of time zones or banking hours. They can also be sold back to the issuer, or traded on cryptocurrency exchanges for other digital assets or cash.

Interestingly, many tokenised gold products allow holders to redeem their tokens for actual physical gold, provided they meet certain minimum quantity requirements. This means the digital token is not just a representation, it carries a real claim that can be converted back into the tangible asset whenever the holder chooses.

Plugging Into Decentralised Finance

One of the most transformative aspects of tokenised gold is how it connects to the broader world of decentralised finance, often shortened to DeFi. DeFi refers to a growing ecosystem of financial services, including lending, borrowing, and trading, that operate without traditional banks or financial institutions acting as middlemen.

Since tokenised gold exists on a blockchain, it can plug directly into these DeFi platforms. Someone holding tokenised gold could use it as collateral to avail a loan in a digital currency, without ever selling their gold.

They could provide it to a lending pool and earn interest from other users who borrow against it. They could swap it instantly for other digital assets on decentralised exchanges, all without needing approval from a bank.

This idea of gold actively working within financial systems, rather than sitting passively in a vault, is exactly what industry leaders are now pushing toward.

Tait has spoken about infrastructure that would let participants ‘pass gold digitally around the gold ecosystem, as collateral, for the first time’, pointing out that gold has traditionally been viewed as a static, unyielding asset with untapped potential.

This is a genuinely new development in financial history. For the first time, an asset that has represented stability and tradition for millennia can now actively participate in fast-moving, programmable financial systems, all while the underlying physical gold remains safely locked away in a vault.

A World Where Everything Is on Chain

To really appreciate where tokenised gold might be heading, it helps to zoom out and look at a much bigger trend reshaping technology, the Internet of Things, or IoT. IoT refers to the growing network of everyday physical objects, from refrigerators and thermostats to shipping containers and factory machines, that are connected to the internet, and capable of collecting and exchanging data automatically.

Right now, most of this data sits in private company databases, isolated from each other and largely invisible to the public. But a powerful idea is gaining momentum. What if these devices could record their data directly onto a blockchain, creating permanent, verifiable, and shared records that anyone could check?
Imagine a vault holding gold reserves equipped with IoT sensors that continuously measure weight, temperature, humidity, and even motion. Instead of relying solely on periodic human audits, these sensors could feed real-time data straight onto the blockchain, automatically confirming, moment by moment, that the gold backing each token is exactly where it should be. A sudden change in weight could trigger an automatic alert, or even pause trading of the related tokens, all without a single human needing to intervene immediately.

This is part of a much larger shift that many technologists believe is coming, a future where blockchain becomes the invisible infrastructure connecting almost everything. Shipping containers could log their location and condition as they cross oceans, with smart contracts automatically releasing payments once goods are confirmed delivered in good condition.

Solar panels and electric vehicle batteries could trade excess energy with neighbours automatically, with payments settling instantly on a blockchain. Supply chains for food, medicine, and electronics could become fully transparent, with every step from factory to shelf permanently recorded and impossible to fake.
In this kind of world, tokenised gold is not an isolated experiment. It is an early example of a much broader pattern, physical things and real-world data being represented, verified, and exchanged through blockchain technology, often with little or no need for human middlemen. Gold just happens to be one of the first and most natural assets to make this leap, given how closely its value has always depended on questions of authenticity, location, and trust.

Why This Matters for Global Financial System

The importance of tokenised gold extends well beyond convenience for individual investors. On a global scale, it represents a meaningful step toward democratising access to an asset that has historically been difficult for ordinary people to own in meaningful quantities, especially in regions with limited banking infrastructure.

In many parts of the world, buying and securely storing physical gold is simply not practical for the average person. Tokenised gold removes that barrier. Someone with just a smartphone and an internet connection can own a fraction of a gold bar, something that would have been unthinkable a generation ago.
It also offers a potential hedge against currency instability. In countries where local currencies are volatile or where access to stable foreign currencies is restricted, tokenised gold provides an alternative way to preserve value, all while remaining liquid and easily transferable.

From a broader financial systems perspective, tokenised gold represents a bridge between two worlds that have often operated separately, traditional commodity markets and the emerging digital asset economy.

As more real-world assets, from real estate to bonds to commodities, follow gold’s lead and become tokenised, and as IoT devices increasingly feed real-world data onto blockchains, we may be witnessing the early stages of a fundamental shift in how value itself is stored, verified, transferred, and used.

Tokenised gold has taken one of humanity’s oldest and most trusted assets and equipped it with the speed, accessibility, and programmability of modern digital finance. It does not ask people to abandon what gold has always represented, security, permanence, and tangible worth. Instead, it simply gives that value a new way to move through the world.

As physical objects become increasingly connected, and as more of the data and assets that matter to our lives find their way onto blockchains, tokenised gold offers an early glimpse of what this future might look like, one where trust is not just promised by institutions, but continuously demonstrated by the technology itself.

The post Gold Gains Mobility In Blockchain Age appeared first on International Finance.

The United States government ordered an AI company to pull its most advanced products from the hands of every non-American user on the planet, with almost no warning. Within hours, a piece of software that had been available to hundreds of millions of people was gone. Nothing was broken or glitchy. It didn’t go temporarily offline; it disappeared simply because of a government decree.

The company was Anthropic. The products were Claude Fable 5 and Claude Mythos 5, two AI models the company had launched just three days earlier on June 9. The order came from the US Department of Commerce, acting through its Bureau of Industry and Security. The directive told Anthropic that it must prevent foreign nationals from accessing either model. Because Anthropic had no reliable technical system to check the nationality of every person trying to use its products, the only option was to disable both models for everyone, everywhere. The global shutdown was complete within hours.

What Made These Models Different

Claude Fable 5 and Claude Mythos 5 were not ordinary software updates. They represented a genuine leap in what AI could do. Both models could process enormous amounts of information at once, equivalent to reading roughly 750 novels simultaneously, and could produce sophisticated, detailed work in return. They could write complex computer code, analyse legal documents, design scientific experiments, and reason through problems in a way that previous AI systems could not match.

The commercial results were startling. Stripe, the global financial technology company, used Fable 5 to rewrite 50 million lines of computer code in a single day. A team of human engineers would have taken over two months to do the same job. In the life sciences sector, Mythos 5 generated viable drug candidate designs that laboratory testing subsequently confirmed as biologically sound.

ALSO READ | China’s GLM-5.2 open-source model narrows gap with OpenAI and Anthropic

There was, however, a crucial difference between the two models. Fable 5, the version intended for general public use, came with built-in safety filters designed to refuse requests for dangerous information, such as instructions for cyberattacks or hazardous chemical processes. Mythos 5 had no such filters. It was the raw, unrestrained version of the same underlying intelligence, offered only to a small number of vetted organisations through a restricted programme called Project Glasswing.

The absence of safety filters in Mythos 5 was not negligence. The idea was that certain trusted organisations, particularly those doing defensive security work, needed to probe the model’s full capabilities in order to understand and protect against potential threats. What nobody outside a classified briefing room fully appreciated was just how threatening those capabilities turned out to be.

The Moment That Changed Everything

In an authorised internal test under Project Glasswing, Mythos 5 was paired with defensive cybersecurity tools and pointed at the US National Security Agency’s own classified systems. The model broke into almost all of them within hours, rather than the weeks such an exercise would normally require. It identified thousands of serious security vulnerabilities and demonstrated what experts call autonomous exploit chaining, the ability to link together multiple weaknesses in a system to escalate an attack automatically. One of the vulnerabilities it exploited had been sitting undetected in a widely used computer operating system for 17 years.

The NSA chief Joshua Rudd delivered these findings in a classified briefing to the Senate Intelligence Committee. The message was stark.

Mythos-class intelligence could function as an automated cyber weapon. It could be used not just to probe defences, but, in the wrong hands, to attack civilian infrastructure, financial networks, and military systems on a scale and at a speed that no human hacker could match.

Then a second problem emerged. Researchers at Amazon discovered a way to bypass the safety filters built into Fable 5, the supposedly safe public version of the model. This meant that anyone who knew the right way to phrase their requests could unlock capabilities very close to those of the unfiltered Mythos 5. Amazon chief executive Andy Jassy raised these concerns directly with US Treasury Secretary Scott Bessent on June 11. The next day, the shutdown order arrived.

ALSO READ | White House’s tech ‘lock and key’ strategy shifts to OpenAI

A third trigger also contributed. Days before the blackout, the White House asked Anthropic to revoke access to Mythos 5 for SK Telecom, the South Korean telecommunications giant, over concerns about business connections between its parent conglomerate and Chinese affiliates. The incident illustrated how even allied companies could be caught in the crossfire of US-China strategic competition.

A New Kind of Weapon Control

Previous US export controls had focused on physical objects. The country restricted the export of advanced chip-making machinery, of high-performance computer processors, of military hardware. The logic was, if a dangerous piece of equipment never leaves the country, it cannot be misused abroad.

The Fable 5 and Mythos 5 directive applied that same logic to cloud-based software for the first time. No physical object moved. The AI models ran on servers inside the United States. Anyone in the world could access them through the internet. The government’s position was that this remote access itself constituted a form of export, one that fell under existing law.

The legal mechanism used was something called the deemed-export rule, a provision in US export law that treats giving a foreign national access to controlled technology, even within the United States, as equivalent to physically exporting it to their home country. By applying this rule to cloud software, the government established an extraordinary new precedent. Now typing a query into an AI system from abroad is legally comparable to receiving a shipment of military hardware.

This precedent created immediate chaos for Anthropic’s own workforce. Several of the company’s most senior technical staff were not American citizens, including researchers and executives from Germany, Canada, Slovakia, the United Kingdom, and Brazil. Under the directive, these individuals were legally prohibited from accessing the very models they had spent years building. The people best placed to fix the security vulnerabilities that had prompted the shutdown were locked out of the systems that needed fixing.

The Political Dimension

The abruptness of the shutdown could not be separated from a longer-running conflict between Anthropic and the Trump administration. Since early 2025, the company had clashed with the government over how its AI models could be used. Anthropic had refused to allow its products to be deployed in fully autonomous weapons systems or domestic surveillance programmes. In February 2026, the Pentagon responded by placing Anthropic on a national security blacklist, restricting military contractors from working with the company. Legal battles followed in courts in Washington and California.

When the export control order arrived, senior administration figures were not shy about their satisfaction. Defence Secretary Pete Hegseth stated publicly that the decision vindicated the Pentagon’s earlier blacklisting.

The Pentagon’s chief information officer Kirsten Davies was equally blunt. Writing on X the day after the shutdown, she declared: “Some things are simply more important than revenue cycles, clickbait, and pre-IPO valuation. America First. Always.” The post was a pointed reference to Anthropic’s anticipated stock market listing, and left little ambiguity about where the Defence Department stood.

Critics in the cybersecurity community were unconvinced. More than 60 leading security experts signed an open letter arguing that Fable 5’s defensive capabilities were themselves a tool for protecting networks, and that removing it from the hands of defenders was itself a security risk. They also pointed out that OpenAI’s GPT-5.5, a model with broadly comparable capabilities, faced no such restrictions, a disparity that suggested political motivation rather than consistent security logic.

The First Lawsuits

The commercial fallout was immediate. On June 23, a San Jose-based litigation technology company called Legion LegalTech filed a lawsuit against the US Commerce Department in Washington federal court. Legion had built its entire product, an AI-powered platform for attorneys handling drafting and case management, on top of Fable 5. Its engineering and development team was based in Canada. When the export directive took Fable 5 offline, Legion’s Canadian developers were locked out overnight.

In its legal filing, Legion described the damage as immediate, irreparable, and existential. In a fast-moving, highly competitive market, the company argued, the competitive ground lost during a forced suspension cannot be recovered.

The case exposed a vulnerability that thousands of companies around the world share. Many businesses have built their products directly on top of AI models provided by third parties, assuming those services will remain reliably available. The standard agreements that govern such relationships are service contracts, not supply guarantees. They do not protect against a government ordering the provider to switch off access at 90 minutes’ notice. Legion’s lawsuit was the first, but it was widely expected not to be the last.

The World Responds

Outside the United States, the shutdown was read as a warning about the fundamental risk of depending on foreign-controlled technology. If the world’s most powerful AI tools can be switched off by a single government directive, then any country or company that relies on them is exposed to a form of vulnerability that no contract, no service-level agreement, and no business continuity plan had previously accounted for.

The response was immediate and global. Canadian Prime Minister Mark Carney used the shutdown as a central justification for a 2.3 billion dollar national AI strategy, explicitly designed to reduce dependence on US cloud services. Speaking ahead of the G7 summit, he compared the risk of over-reliance on a small number of foreign AI providers to the systemic financial risks that produced the 2008 banking crisis.

India proposed a 5 billion dollar sovereign AI fund and backed 12 domestic AI development projects in the days following the ban. Indian policymakers argued that purchasing processors and building data centres was not enough. True technological independence required deep institutional research capacity built over years, not emergency spending in response to a crisis.

In Britain, a coalition including BT, HSBC, and BAE Systems began organising around the goal of building a sovereign frontier AI model independent of US administrative control. Senior political figures warned that modern sovereignty was increasingly defined by control over digital infrastructure rather than military hardware.

French presidential candidate Bruno Retailleau claimed that a nation that depends on others for its technology can be unplugged overnight.

The Chinese, who are the number one rival to the US in the AI race, took notice when Elon Musk commented on what was happening.

When Musk posted on X that China would ‘probably’ produce a Fable-class model by the first quarter of 2027, Tang Jie, founder and chief scientist of Beijing-based Zhipu AI, was unimpressed by that timeline and replied in four words: “Won’t take that long.”

The confidence was not without basis. Zhipu’s newly released GLM-5.2, a 744-billion-parameter model built entirely on Chinese Huawei processors without a single Nvidia chip, had just ranked second globally on a major coding benchmark, behind only Fable 5 itself.

The US decision to halt access to Fable and Mythos might be to ensure that the Chinese would not access Anthropic’s state-of-the-art technology.

But the race is tight. And the Pentagon might have unwittingly given the edge to Chinese competitors, who can roll out their products to millions of people and gather big data. It is only a matter of time before the Chinese catch up, and even surpass their US peers.

Europe’s Regulatory Counterplay

The European Union arrived with its own agenda already in motion. On June 3, nine days before the Anthropic shutdown, the European Commission had unveiled the Cloud and AI Development Act, known as CAIDA. The legislation establishes four tiers of certification for digital services used by public bodies and critical infrastructure operators. The highest tiers require that services be owned and controlled by European entities, beyond the reach of foreign legal jurisdiction.

The conflict between CAIDA and US law is structural. American cloud companies remain subject to the US CLOUD Act, which allows US authorities to compel American firms to disclose data held anywhere in the world. That requirement is irreconcilable with European data protection law. By reserving the highest certification tiers for European-controlled entities, the EU is in practical terms barring US companies from the most valuable segments of the European public sector market.

European officials argue that if US companies benefit from exclusive access to the world’s most powerful productivity tools while their European competitors are shut out by Washington’s export controls, that constitutes an unfair competitive advantage. The EU has a long and effective history of acting against such imbalances through competition law and financial penalties.

The Limits of Going It Alone

Very few countries have the resources to build a complete AI ecosystem independently. The full stack requires advanced chip manufacturing, enormous quantities of energy, elite technical talent, and sustained capital investment over years. Outside the United States and China, no single nation can credibly claim to have all of these.

The emerging response to this reality is what some policymakers are calling collective programmable sovereignty. It’s a model in which allied nations pool their different strengths to build shared infrastructure that no single government can switch off. South Korea and Taiwan provide semiconductor manufacturing. India provides engineering talent, and data diversity. Gulf states provide the energy needed to power massive data centres. The EU provides regulatory frameworks and research. Brazil and Indonesia provide market scale.

A coalition of this kind would represent an economy larger than that of the United States. It would be in a position to negotiate the terms of technology access rather than simply accept them.

What Comes Next

The shutdown of Claude Fable 5 and Mythos 5 has revealed something important about the world that AI has created. The most capable AI systems are now treated by at least one major government as critical national security assets, subject to the same logic of containment that once governed nuclear technology and advanced weaponry. The era in which cutting-edge AI tools were simply available to anyone with an internet connection and a credit card is over.

For businesses, the immediate lesson is the danger of concentration risk, of building core operations on a single provider’s infrastructure without the ability to switch rapidly to an alternative. For governments, it is the realisation that declarations of digital sovereignty mean nothing without the physical infrastructure, the talent, and the sustained investment to back them up.

The event was, in its own way, the clearest demonstration yet of how central AI has become to geopolitics, commerce, and national power. The question now is not whether AI will be treated as a strategic asset. It already is. The question is who will control it, and on whose terms.

The post US Shuts World’s Most Powerful AI, Triggers New Race appeared first on International Finance.

A growing number of power users, including software developers, financial analysts, academic researchers, and security-conscious companies, are pulling their data back. They are moving away from cloud platforms and building systems where their information lives locally, on their own devices, under their own control. The reasons are financial, legal, and deeply personal. Subscription prices have ballooned out of control. Platforms have quietly started using customer data to train artificial intelligence. Some services have simply shut down, leaving users stranded with no way out.

This is not a fringe reaction confined to paranoid engineers, but a structural shift in how organisations think about intellectual property, and it is being driven by hard numbers.

The Bill That Keeps Growing

The most immediate driver of this shift is cost. Cloud software is getting significantly more expensive, and far faster than almost anything else in the economy.

Data drawn from over $30 billion in tracked global software spending shows that SaaS-specific inflation, meaning price rises across subscription software products specifically, reached 13.2% in early 2026. In late 2025, it peaked even higher, hitting 14.7% just as most large enterprises were going through their year-end renewal cycles, which is hardly a coincidence. For context, general consumer price inflation across G7 economies sits around 2.7%. Software costs, in other words, are rising nearly five times faster than the price of everything else.

The consequences are visible on corporate balance sheets. The average company now spends roughly $9,100 per employee per year on software, a rise of 27% over just two years. Software’s share of total IT budgets has climbed from 13% five years ago to 21% today, a jump so steep that in several companies it now exceeds what they spend on employee healthcare coverage. Roughly 79% of IT leaders reported facing price increases at their last renewal cycle, suggesting this is no longer an occasional shock, but the new default behaviour of the industry.

The price increases themselves are not subtle. Salesforce has pushed its top-tier enterprise licencing cost to $500 per seat per month, after consecutive price hikes in 2023 and 2025. Slack raised its Business+ subscription by 20%, taking it to $15 per user monthly. Zendesk has been charging customer service teams up to $115 per agent monthly, with AI features tagged on as a separate $25 to $50 add-on. Adobe quietly restructured its Creative Cloud offering, stripping mobile apps and AI features out of its cheaper standard tier, and rebranding a pricier version as the new default for anyone who wants the full toolkit.

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Beyond these headline increases, software companies have become increasingly creative about extracting more money without technically raising the sticker price, a practice sometimes called shrinkflation. Standard features quietly get moved into higher, costlier pricing tiers. The number of API calls a customer is allowed gets reduced. Monthly usage credits expire before they can be fully used, forcing customers to either upgrade or simply lose value they already paid for.

Atlassian’s Rovo platform, for example, caps users at 25 credits a month. Adobe’s Firefly platform uses non-rollover credits that get consumed faster for more advanced generative tasks. Microsoft, in its mid-2026 updates, bundled tools like Copilot Chat, Defender, and Intune into existing subscription tiers, using the bundling itself as justification for a higher overall list price, forcing organisations to pay for features many of them never asked for, or needed. Companies trying to build custom AI tools on Microsoft’s Copilot Studio platform face a flat $200 monthly fee capped at 25,000 messages, with anything beyond that triggering metered overage charges.

The cumulative effect of all this is a corporate software bill that grows substantially every year, regardless of whether the underlying product has actually improved.

The Privacy Shock

The financial squeeze on its own would already be reason enough for companies to rethink their cloud dependence. But it has been compounded by something arguably more serious. There is a deep erosion of trust around what platforms actually do with the data their customers store on them.

The rise of generative AI has created an almost insatiable demand for training material. Large language models need enormous quantities of text to learn from, and some of the richest, most detailed text in existence sits quietly in the documents, internal chats, and notes that businesses store on cloud platforms every single day. Several major vendors have been caught treating this material as fair game for their own AI ambitions, often without making that intention obvious to the customers footing the bill.

ALSO READ | US Shuts World’s Most Powerful AI, Triggers New Race

A widely cited Stanford study found that several leading AI developers feed user conversational data back into their own models by default, relying on lengthy data retention periods, and offering very little clarity about how customers can actually opt out. Even Anthropic, the company behind Claude, changed its terms of service in September 2025 to train its models on user conversations by default, unless customers actively chose to opt out themselves.

Slack faced its own wave of public backlash after users discovered that its privacy terms permitted the company to scan messages and files in order to train machine learning models. Customers were automatically enrolled into this without any active choice, and had to email a specific address to request removal, a process most users never even knew existed until it was reported on. Slack later clarified that its newer AI features rely on outside large language models rather than directly retraining on raw private message content, but for many businesses, the explanation arrived only after the trust had already been damaged.

Adobe ran into a similar storm. An update to its terms of use appeared to grant the company access to active, in-progress user files through both automated and manual review processes. Designers and creators working under strict client confidentiality agreements suddenly realised that unpublished, unreleased work sitting in their Adobe cloud storage could potentially be scanned. Adobe later clarified that its main generative tool, Firefly, is not trained on customer cloud files. That clarification did little to stop the fallout, and the company was hit with a shareholder lawsuit accusing its executives of misleading investors about how its AI training data was actually being sourced.

The starkest cautionary tale, however, is the story of Skiff. Skiff was a privacy-focused productivity startup that had built a loyal base of nearly two million users on the strength of its end-to-end encrypted email, calendar, and document storage. It had raised meaningful venture funding, including from Sequoia Capital, and represented exactly the kind of privacy-first alternative that security-conscious users were looking for. In February 2024, Notion acquired Skiff, and then chose to shut the entire product down.

Users were left scrambling to manually export their own email archives, contacts, and files, since automatic migration tools simply were not available. The transition itself became a case study in how not to handle an acquisition: promised email forwarding broke due to expired security certificates, customer support was replaced by unresponsive automated chat loops, and user-owned domains stopped functioning correctly.

For an audience that had specifically chosen Skiff because they cared about owning their own data, watching the company they trusted vanish almost overnight was a stark wake-up call.

The lesson these episodes left behind, across the developer and research communities, was simple and hard to unlearn: when your data lives on someone else’s server, it ultimately lives by their rules, not yours.

The Local-First Alternative

The response to all of this now has a name. It’s called local-first software. The term was formally defined back in 2019 by a research group called Ink and Switch, but the underlying instinct it captures, that your own files should belong to you first and foremost, is far older and has become newly urgent.

Local-first software is built on one simple, almost old-fashioned principle. Your files live on your own device first. The hard drive of your computer, tablet, or phone is treated as the primary, authoritative home for your data. Any synchronisation across multiple devices, or any sharing with collaborators, happens quietly in the background over the network, as a secondary convenience rather than as a precondition for the software to work at all.

This distinction matters enormously in practice. If the software company behind the app goes out of business, your files remain exactly where they were, fully readable. If your internet connection drops, you can keep working without interruption. If the vendor changes its terms of service, hikes its prices overnight, or gets quietly acquired and shut down, none of that changes what is already sitting safely on your own hard drive.

The clearest real-world example of this model working at scale is Obsidian, a note-taking and knowledge management application now used by over 1.5 million people every month. Obsidian stores everything as plain text Markdown files inside a folder on your own computer, what the app calls a vault. There is no proprietary file format, and no cloud lock-in involved. Any basic text editor on any device can open these files, with or without Obsidian installed.

When Obsidian introduced a new feature called Bases in 2025, which lets users build searchable, structured databases directly from their notes, many longtime Notion users found they could finally replicate everything they relied on Notion for, except now it all lived entirely on their own machine.

Obsidian generates revenue through optional paid add-ons, like encrypted cross-device syncing, priced between $48 and $96 a year, and a separate publishing feature. But the core application itself remains free, including for full commercial and enterprise use, after the company relaxed its licencing terms.

Independent security firms have audited the underlying architecture and confirmed its claims. When users do choose to sync their notes across devices, the files are encrypted directly on their own device before they ever leave it, which means even Obsidian’s own servers are mathematically incapable of reading the contents.

Where Governments Come In

This move toward local control is not limited to individual users or small companies. Governments, particularly across Europe, are now pushing hard to bring entire categories of national and corporate data infrastructure back under their own legal jurisdiction.

The distinction driving this effort is a subtle but important one. The difference between data residency and data sovereignty. Data residency simply means your data physically sits on a server located in a particular country. Data sovereignty means that data is actually governed by that country’s own laws, and meaningfully protected from interference by foreign governments, which is a much higher bar.

Under existing American law, US technology companies can be legally compelled to hand over data stored on their servers anywhere in the world, including servers physically located inside Europe. This creates a genuine problem for European organisations relying on American cloud platforms, no matter where those platforms’ physical data centres happen to be.

France has responded by formalising a framework that requires government bodies and operators of critical national infrastructure to host sensitive data exclusively on cloud services that meet strict, French-controlled standards. The requirements include European legal control over the provider, European-based management of encryption keys, and an entirely EU-based staff.

In response, major American technology giants have formed European joint ventures specifically to meet these requirements, including a Microsoft partnership with Orange and Capgemini inside France, and a Google partnership with the defence contractor Thales.

Amazon went a step further, opening a dedicated European Sovereign Cloud in Germany in January 2026. It was built as a legally and operationally separate entity from Amazon’s global cloud business, staffed exclusively by EU residents, and specifically engineered to insulate customer data from American legal jurisdiction.

Germany’s Hetzner and DanubeData, alongside France’s OVHcloud and Scaleway, offer virtual private servers, managed databases, and object storage at 40% to 70% lower cost than AWS, Google Cloud, or Microsoft Azure. Because these providers are headquartered and operated entirely within European jurisdictions, they sidestep the complex data transfer assessments that come with using American platforms, and crucially, they fall outside the reach of US surveillance law.

For cost-sensitive startups and mid-market developers, this combination of cheaper pricing and cleaner legal standing has made them an increasingly default choice rather than a niche one.

At the government level, the stakes are higher, and the providers more specialised. Bleu, a joint venture between Capgemini and Orange, delivers Microsoft Azure and Microsoft 365 services hosted entirely within France, operated by EU citizens, and built specifically to meet SecNumCloud 3.2, the French government’s strict cloud security qualification. Bleu is designed for public administrations, and so-called ‘Operators of Vital Importance’, the institutions running hospitals, utilities, and other critical infrastructure.

A similar logic applies to S3NS, a French entity formed by Google in partnership with defence contractor Thales, also structured around SecNumCloud compliance.

In Germany, Delos Cloud, an SAP subsidiary, has been built to satisfy federal sovereignty requirements for government workloads.

At the most sensitive end of the spectrum sits Google Distributed Cloud (GDC), which can run fully air-gapped, physically isolated from the public internet. This mode is built for governments and intelligence agencies that require absolute immunity from remote shutdowns or foreign data extraction, allowing classified workloads to run entirely on sovereign, disconnected infrastructure.
A Recalibration, Not a Rejection

None of this means the cloud is going away, nor should it. Collaborative, real-time tools still make perfect sense for a great deal of everyday business work. But the old assumption that cloud-first automatically means best-first is no longer something organisations can take for granted.

For companies and individuals generating sensitive research, proprietary analysis, or client-confidential work, the question of where exactly that data lives, and precisely who else can access it, has become a genuine strategic decision rather than a default setting nobody bothers to question. The tools needed to answer that question differently are now mature, widely available, and in many cases, considerably cheaper than the cloud subscriptions they are quietly replacing.

The post The Great Cloud Exodus and Return to Data Sovereignty appeared first on International Finance.