At Echelon Philippines 2025, Karl Loo, COO and co-founder of 3Cat, shared insights on building an omnichannel retailer for used electronics — a growing market bridging affordability with sustainability.

He discussed the realities of fundraising in a more cautious venture capital landscape, where founders must demonstrate clear unit economics and a credible path to profitability rather than relying on growth narratives alone.

Central to his talk was the concept of the “unicroach” mentality — a hybrid of the unicorn’s ambition and the cockroach’s resilience. Loo argued that founders who embrace frugality, adaptability, and survival-first thinking are better positioned to build lasting, fundable companies in today’s environment.

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The total market capitalisation fell by 2.05 per cent to settle at US$2.1T within a single 24-hour window. This downward movement stems primarily from a massive leveraged long squeeze cascading directly out of Bitcoin derivatives rather than from an isolated fundamental news catalyst.

When speculative traders take on excessive leverage, sharp downward movements trigger automated liquidations that force rapid selling, which in turn overwhelms existing buy orders and erodes vital technical support levels. Interestingly, the broader digital asset market currently exhibits a strong 85 per cent correlation with gold, illustrating how shifts in inflation hedge positioning influence these digital assets during macro-driven market adjustments.

Looking deeper into the mechanics of this primary catalyst, data from global crypto derivatives metrics reveal that over US$401 million in Bitcoin positions faced liquidation within 24 hours. Long positions accounted for a staggering US$319 million of that total aggregate volume. This massive volume of forced selling created a technical unwind that dragged the total market cap down to its pivotal US$2.1T baseline. For analytical observers looking to spot a reversal, the market requires a clear stabilisation in Bitcoin open interest alongside a sustained reduction in overall liquidation volume to signal that this painful deleveraging phase has finally concluded.

Beyond the immediate mechanics of the derivatives market, sentiment and funding pressures acted as secondary forces that heavily amplified the velocity of the sell-off. The Fear and Greed Index collapsed into deep territory, hitting a reading of 18, which signals extreme fear and marks its lowest level in several months.

Also Read: The great rotation: How AI stocks are stealing billions from crypto

Simultaneously, the average perpetual funding rate turned deeply negative to settle at -0.0015125, representing a massive drop of 177 per cent over the course of a single day. This negative turn means short sellers are actively paying to maintain their positions, while long holders are fleeing, which reflects a pervasive lack of confidence across global trading desks. To gauge when a true sentiment recovery might begin, market participants must look for these funding rates to cross back into positive territory.

This technical and emotional downturn sets up a critical near-term outlook centred entirely around the US$2.1T support level, which functions as the current market pivot point. If the market successfully stabilises above this US$2.1T pivot, a short-term relief bounce could carry the total valuation upward toward the 78.6 per cent Fibonacci retracement level located at US$2.19T. A decisive break below this floor could accelerate panic selling toward the yearly low.

Outside of pure price action, the next major structural catalyst for the digital asset space will be the legislative progress surrounding the upcoming CLARITY Act, a regulatory framework that institutional participants hope will finally provide concrete legal guidelines for digital assets in the United States.

Evaluating the broader horizon reveals a deeply distressing structural reset that has quietly wiped out US$2.03 trillion from the ecosystem in only eight months since October 10th. This massive macro liquidity flush has sent total market capitalisation tumbling down from a high of US$4.2T to its current resting place of US$2.17T. The damage report across individual assets highlights the severity of this capital flight, with Bitcoin shedding 54.02 per cent of its value, Ethereum plunging by 65.68 per cent, and low-cap alternative tokens getting absolutely decimated by an average of 98 per cent. This scale of destruction proves that retail participants and speculative tourists are completely exiting the space.

Also Read: Gold, stocks, and crypto are all falling together: The correlation trap

A granular look at recent institutional flow data further illustrates why individual investors feel so incredibly vulnerable to these whales. For example, recent transaction records for Ethereum show that BlackRock sold a massive US$164 million worth of the asset in a single day. Even though two new prominent whales stepped in to buy a combined US$58 million and market commentator Tom Lee purchased another US$58 million, their collective buying power failed to offset the institutional distribution. When a single entity like BlackRock possesses the systemic size to completely overwhelm market demand, it creates an environment where smaller participants are easily crushed by institutional rebalancing.

This concentration of power forces a blunt realisation regarding the actual utility of popular blockchain protocols. Many market participants remain blind to the reality that major financial corporations have no intention of utilising public networks like Ethereum, Solana, or Binance Chain for their core operations. Blockchain technology itself is merely an immutable recording tool, and when global enterprises eventually deploy it at scale, they will inevitably build upon their own private, permissioned networks to maintain total control.

Furthermore, the reliance on stablecoins pegged directly to the United States dollar reveals a massive ideological contradiction, because investors who claim to despise traditional fiat currency are still anchoring their entire financial survival to the exact digital representations of that same sovereign currency.

The underlying data demonstrates that survival depends on whether Bitcoin can stabilise above the crucial psychological level of US$60,000 and whether the total market capitalisation can hold its ground at the US$2.1T support line. If these technical levels crack, a swift test of the ultimate cycle low looks completely unavoidable. Investors must stop treating these tokens like traditional technology stocks and instead demand a fundamental shift that drives true, structural decentralisation to the next level before the current institutional tide washes away the original promise of the ecosystem.

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Olive AI raised US$902 million, deployed automation across 900 hospitals in 40 states, and was valued at US$4 billion at its 2021 peak. By October 2023, it was gone. Not because the AI failed — but because a routine Epic module update broke the bots, and hospitals found themselves adding human monitoring on top of the automation they’d paid to replace. A minor interface change. A catastrophic systems mismatch. The product worked perfectly in the lab. The lab was not where nurses actually worked.

Pear Therapeutics received FDA approval for prescription digital therapeutics, then collapsed because doctors had no workflow to prescribe them, pharmacies had no system to fulfil them, and insurers had no billing code to reimburse them. The product existed in a system vacuum. Babylon Health scaled AI diagnostics to millions of users, then watched clinicians run parallel manual checks on every AI output — functionally doubling the workload it was built to eliminate. Both companies shut down in 2023.

These weren’t technical failures. They were a category error: treating a workflow intervention as a product launch.

Bain’s 2024 analysis of over 900 companies found that 88 per cent of business transformations fail to achieve their original ambitions. IDC puts the annual cost at US$2.3 trillion, more than the GDP of Italy, gone every year from systems that worked and were still rejected. The common finding across McKinsey, BCG, and Harvard Business Review is consistent: the failure driver is not a technical limitation. It is the gap between what a product can do and how people actually work. This is not a medtech story. It is not an agritech story. It is the story of every industry where a human being stands between your technology and its purpose, which is to say, every industry that exists.

The real constraint is human bandwidth, not computation

Ask a clinician why they rejected a diagnostic tool with 15 per cent better accuracy. The answer is almost never distrust of the algorithm. It is four minutes. Four extra minutes per patient is trivial in isolation. Across a 12-hour shift with 30 patients, it is catastrophic — especially when the pharmacy call, the handover note, and the attending physician’s interruption are all queued behind it.

The same dynamic plays out in a fulfilment warehouse where a new routing system adds two extra taps per package scan. In a law firm where a contract review tool requires a different login than the document management system. In a retail bank where a fraud-detection upgrade changes the screen flow that branch staff have navigated by muscle memory for six years. The technology improves the outcome. The friction destroys the adoption.

Also Read: Bridging the AI trust gap: Why ad diversification and creative differentiation are the future of customer connections

Research published in NEJM Catalyst identifies the primary barrier to clinical technology adoption not as accuracy distrust but as muscle memory disruption. The same principle holds everywhere humans operate under time pressure and cognitive load, which is most places where technology is now being deployed. Mayo Clinic created a new executive role — Chief Clinical Systems and Informatics Officer — specifically because hospitals now push hundreds of software changes per quarter to clinical staff. Each one is a tax on attention. Accumulate enough taxes, and the immune system activates: staff quietly revert to what they know, regardless of what the trial data showed.

What IDEO actually did, and why it matters

When the American Red Cross hired IDEO to address declining blood donation rates, the instinctive solution would have been to optimise the process: faster check-in, better needles, shorter waits. IDEO did something different. They observed.

What they found was not a logistics problem. It was an emotional one. Donors came in anxious about the needle and left feeling like a transaction. The post-donation routine — sit for 15 minutes, drink juice, eat a cookie — treated recovery as a waiting room problem. Nobody asked what had brought the donor in. Nobody made the moment mean anything.

IDEO’s intervention was not a product. It was a ritual redesign. During the post-donation observation period — when donors had to remain seated anyway — staff handed them a card and a pen and asked them to write down why they had donated. Not for a form. Not for a database. Just to hold, and to keep. The cards were photographed and pinned to a display board in the donation centre, as Post-it notes from a first date, casual and personal and visible to the next person who walked in.

The intervention cost almost nothing. It changed the emotional architecture of the entire experience. Donors who had articulated their own motivation — in their own handwriting, in their own words — returned at dramatically higher rates. They hadn’t just given blood. They’d made a statement about who they were. The Red Cross hadn’t improved the needle. They had changed what the act meant.

The breakthrough wasn’t a better product. It was the recognition that behaviour follows meaning — and meaning, if you design for it, can change everything

This is what anthropological design actually is. Not user research as a checkbox before engineering starts. Not a UX audit after launch. It is treating technology, behaviour, and context as a single system — where the human workflow is not a constraint to be managed around, but the primary design surface.

Over three decades as an investor, I’ve listened to thousands of founders and CEOs explain their technology, their product roadmaps, and their market strategies. Almost none could articulate how customer experience would be architected over time — or how workflow integration would be continuously tested, retrained, and adapted as real-world conditions evolved. The implicit assumption was always the same: build the product, and adoption will follow. It rarely does. And the gap between that assumption and reality is where most of the US$2.3 trillion goes.

Also Read: Solving multiple medtech problems with a single device powered by AI

The companies getting this right

John Deere’s See & Spray — built on a US$305 million acquisition of computer vision startup Blue River — uses AI to identify weeds and spray only them, cutting herbicide use by up to 77 per cent. It could have been another brilliant system ignored in a barn.

Instead, Deere built the adoption architecture before the product reached the market: three pricing tiers structured around farmers’ capital constraints, software designed so existing precision-ag users were “more than halfway to full autonomy” before touching a new feature. Deere’s CFO framed the goal explicitly as meeting farmers “at every stage of their precision tech journey.” By the end of 2024: record adoption across the entire technology stack.

The insight is not complicated. Farmers — like clinicians, like warehouse workers, like anyone operating under time pressure in a high-stakes environment — are not resistant to technology. They are resistant to discontinuity. Products that require behavioural rupture fail. Products that slip into existing rhythms without announcing themselves compound quietly until they’re indispensable.

Organisations with a structured change-management strategy are seven times more likely to meet their digital transformation goals, per Mendix’s analysis. Not from a better model. From understanding the human system, the model is entering.

A question worth sitting with

The US$2.3 trillion graveyard of failed transformations is not primarily an engineering failure. It is a failure of scope — a discipline that stopped at the boundary of the product and called it done. Superior technology is necessary. It is no longer sufficient. The bottleneck has migrated from the lab to the deployment environment, and most organisations are still staffed for the old bottleneck.

So here is the uncomfortable question — not just for medtech founders or agritech operators, but for anyone building anything that a human being will eventually have to use, adopt, or trust:

If you cut your technical team in half tomorrow and replaced them with anthropologists, ethnographers, and workflow specialists, would your product get worse?

If the answer is no — or if you’re not sure — that uncertainty is the finding. The next defensible moat will not be built in a model. It will be built on the accumulated institutional knowledge of how adoption actually works — knowledge that compounds with every deployment, cannot be licensed, and cannot be replicated from a term sheet.

Start there.

This article is part of David Kim’s Value Creation column. It sits alongside the Asia Value Creation Awards, which aim to recognise PE and VC teams driving long-term, fundamentals-led value creation across the region.

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Swedfund, Sweden’s development finance institution, has committed US$15 million to Navegar Fund III, a private equity vehicle targeting mid-sized companies in the Philippines.

The fund, managed by Manila-based Navegar, is seeking to raise US$250 million and will invest in businesses across consumer and business services, including healthcare, food distribution, and logistics. These sectors sit close to the country’s domestic consumption story but are also exposed to deep operational bottlenecks: fragmented supply chains, limited access to institutional capital, uneven governance standards, and a labour market where informal employment remains widespread.

Also Read: Great Deals raises US$12M from Navegar to be the Alibaba of Philippines

For Swedfund, the investment is part of a broader strategy to back private sector growth in developing markets through fund commitments rather than only direct company investments.

For Navegar, it adds development finance capital to a fund focused on the Philippine middle market, a segment often too large for microfinance and early-stage venture capital, but too small or under-institutionalised for many large global investors.

The deal also reflects a wider Southeast Asian theme: as startup funding has slowed and investors have become more selective, private equity and development finance institutions are increasingly looking at profitable, cash-generating, mid-sized businesses that serve domestic demand.

Why the Philippines’ mid-market matters

The Philippines has remained one of Southeast Asia’s more resilient growth markets, supported by remittances, business process outsourcing, domestic consumption, and a young workforce. But capital access remains uneven.

Large conglomerates and listed firms can tap banks and capital markets. Early-stage startups may attract venture capital if they fit regional narratives around fintech, e-commerce, software, or artificial intelligence. Between those two ends sits a broad layer of mid-sized businesses that employ thousands, serve local communities, and move goods and services across the archipelago but still often lack patient, long-term capital.

This is the space Navegar Fund III is targeting.

Mid-market businesses in sectors such as healthcare, food logistics, and business services can play an outsized role in the Philippines. Healthcare access remains uneven across provinces. Food distribution is complicated by geography, infrastructure gaps, and cold-chain limitations. Logistics companies operate in a country of more than 7,000 islands, where delivery efficiency is not merely a commercial advantage but a structural economic need.

Capital alone will not fix these problems. But private equity funds can bring a mix of growth financing, governance discipline, reporting standards, operational support, and strategic guidance, especially to founder-led businesses preparing for scale.

Jobs, formalisation, and the informal economy

Swedfund’s stated rationale is job creation, particularly more formal and productive employment. The Philippines continues to face a large informal labour market, with around 70 per cent of the workforce employed informally. Such jobs frequently lack stability, benefits, social protection, training pathways, or clear routes for wage progression.

That makes mid-sized companies important. They are often big enough to formalise employment practices and invest in systems, but not always strong enough to do so without external support. A company that raises institutional capital may need to improve financial controls, labour standards, compliance, and governance — changes that can lift job quality if implemented seriously.

“Creating more productive and formal jobs is essential for inclusive economic development. By helping growing businesses access the capital they need to expand, this investment aims to strengthen the private sector and contribute to sustainable job creation in the Philippines,” said Helen Hagos, Investment Director, Food Systems & Strategic Investments at Swedfund.

Also Read: The hidden tax on Philippine SMEs: Unreliable infrastructure

The quote captures the development finance logic behind the deal. The harder question is execution: whether portfolio companies can turn capital into durable employment rather than simply faster expansion.

In Southeast Asia, this tension is familiar. Investors often speak of inclusion, formalisation, and productivity, but outcomes vary depending on ownership discipline, sector dynamics, and management capacity. The most meaningful impact tends to come when capital is tied to operational improvements, such as better systems, improved worker retention, stronger supply chains, and measurable gains in productivity.

A Southeast Asian private equity story

The Swedfund-Navegar deal lands at a time when Southeast Asia’s funding landscape is being recalibrated.

After years of VC enthusiasm, investors across the region have shifted towards profitability, sustainable unit economics, and businesses with clearer cash flows. In markets such as Indonesia, Vietnam, and the Philippines, this has pushed renewed attention towards private equity-style investing in traditional sectors that are being modernised, rather than purely digital-first models.

The Philippines has not attracted the same volume of venture funding as Indonesia or Singapore, but its mid-market opportunity is significant. Many domestic companies operate in large service categories, benefit from growing consumer demand, and have room to professionalise. For investors willing to work closely with management teams, these businesses can offer scale without relying on the high-burn growth models that characterised the previous startup cycle.

Development finance institutions have become increasingly relevant in this environment. Their capital can help anchor funds, attract other institutional investors, and extend investment horizons in markets where perceived risk remains high. In turn, fund managers are expected to deliver not only financial returns but also measurable development outcomes.

Swedfund said the commitment is aligned with its thematic fund investment strategy and strengthens its exposure to Southeast Asia. That matters because the region remains a priority for investors seeking growth beyond China and India, but capital is still unevenly distributed. Singapore attracts headquarters and fund structures; Indonesia draws scale narratives; Vietnam benefits from manufacturing and supply-chain interest. The Philippines, despite its large population and consumption base, is often underweighted in regional investment strategies.

A fund like Navegar Fund III helps address that gap by focusing specifically on Philippine companies rather than treating the market as an extension of a broader Southeast Asian mandate.

What Navegar brings

Navegar is a Manila-based private equity firm focused on the Philippine market. Its third fund will provide long-term capital and active ownership to mid-sized companies in key domestic sectors.

That local presence is important. Mid-market investing in Southeast Asia is relationship-heavy and operationally demanding. Unlike late-stage tech deals, where investors may rely on regional comparables and standardised metrics, private equity in traditional sectors often requires deeper market knowledge: family ownership dynamics, regulatory relationships, supply-chain realities, regional expansion constraints, and management succession issues.

For Philippine companies, bringing in a private equity investor can be transformative but also challenging. It can mean tighter reporting, more formal boards, clearer performance targets, and sometimes uncomfortable operational changes. The upside is access to capital and expertise that banks may not provide, particularly for companies pursuing expansion, acquisitions, technology upgrades, or governance improvements.

The bigger picture

Swedfund’s US$15 million commitment will not, by itself, reshape the Philippine economy. But it signals confidence in a segment that is central to Southeast Asia’s next phase of growth: mid-sized companies serving domestic markets with essential products and services.

Also Read: Philippine AI is no longer a footnote. Here are the 15 startups proving it

The investment also highlights a shift in how impact and growth capital are converging. Rather than backing only high-profile startups or infrastructure megaprojects, DFIs are increasingly using private equity funds to reach companies that sit closer to everyday economic activity — clinics, distributors, logistics operators, food businesses, and service providers.

For the Philippines, where informality remains high and long-term capital is scarce, that approach could be meaningful if it produces stronger companies and better jobs. For Southeast Asia, it is another sign that the region’s investment story is broadening beyond venture-backed tech into the less glamorous but economically vital middle market.

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Most Board packs on cyber, privacy, vendor exposure, and resilience fail in the same way. They contain activity, metrics, and updates, yet still leave senior decision makers unclear on what they are being asked to govern.

One page shows phishing rates. Another shows patching. Another shows third-party incidents, privacy breaches, or resilience testing. Each page may be accurate on its own, but the Board still leaves without clear answers to the questions that matter. What could disrupt the bank’s most important services? Where customer harm is most likely to emerge. Which dependencies have become strategically dangerous? Which weaknesses can be tolerated for now, and which require action before the next incident forces the decision?

Boards rarely suffer from too little information. They suffer from information organised around functions rather than decisions.

Supervisory expectations increasingly point in the same direction. Boards are expected to understand important business services, consider severe but plausible disruption, receive timely reporting on material weaknesses, and use that reporting to make investment and risk decisions. That is not a standard built for fragmented dashboards. It is a governance standard built for judgment.

The mistake is to report by domain instead of by consequence

Most institutions still report cyber, privacy, vendor, and resilience as separate disciplines.

The Board does not govern those areas as isolated territories. It governs the bank’s ability to operate safely, protect customers, withstand disruption, and remain within risk appetite. Once reporting is divided into specialist slices, the most important relationships disappear. A third-party weakness no longer looks like a resilience issue. A privacy control gap no longer appears connected to cyber exposure. A resilience weakness no longer looks like a conduct issue. The Board receives a set of departmental truths rather than one decision grade view of institutional risk.

Also Read: ESG as strategic value: Why Asian boards must move beyond disclosure

A Board paper should answer one question

What are we being asked to decide?

A Board does not need another description of open high-severity vulnerabilities unless that information is linked to a consequence it can govern. It does not need a recital of privacy incidents unless management can explain whether those incidents point to weak design, poor third-party control, weak customer communication, or a deeper failure in data stewardship. The same applies to resilience testing. The governance question is not simply whether a test happened, but whether the outcome changes management’s confidence in staying within impact tolerances for important business services.

The strongest Board narratives, therefore, start with business consequence, not control category. They begin by showing which services, customer outcomes, regulatory obligations, or strategic dependencies are at risk. Only then do they explain which cyber, privacy, third-party, or resilience factors are driving that exposure. The order matters because it forces management to translate control data into a decision about risk acceptance, investment, sequencing, or intervention.

What a joined-up Board narrative should contain

First, it identifies the service or outcome that matters. Not a generic technology issue, but a business service, customer process, regulatory duty, or strategic dependency that the Board would recognise as material.

Second, it shows the chain of exposure. This is where cyber, privacy, vendor, and resilience become one story. A critical service may depend on a concentrated third party, a weak privileged access model, poor data lineage, or an untested recovery path. A privacy issue may be the downstream result of weak identity governance, excessive access, or poor vendor oversight. The Board needs to see the chain, not just the symptom.

Third, it sets out management judgment. What is already being done? What is improving? What remains outside the target state? What assumptions is management making? Where confidence is high and where it is not.

Fourth, it states the decision required. Does the Board need to support a risk acceptance, a control uplift, a delay to a strategic initiative, a change in tolerance, or a sharper intervention on execution? Without this final step, the pack informs but does not govern.

A credible challenge depends on narrative quality

Boards are often told they must provide effective challenge. That is true, but incomplete. A Board cannot challenge credibly if management presents risk through a structure that obscures cause, consequence, and uncertainty.

Directors then end up asking weaker questions. Why is the number red this month? Why is this metric worse than last quarter? Why has this vendor issue not been closed? Those are reasonable questions, but they do not reach the real issue when several risks are combining to threaten a major service or customer outcome.

Also Read: The always-on boardroom: When strategy stops being an event

This is why Boards need fewer comfort metrics and more explicit statements of uncertainty. Where is management relying on vendor attestation rather than direct evidence? Which recovery assumptions have not been tested end-to-end? Which privacy controls look compliant on paper but remain weak in practice? Which cyber improvements reflect genuine resilience, and which simply reflect better measurement? These are the questions that improve governance.

Third-party and privacy reporting need business language

One of the biggest weaknesses in Board reporting is the way third-party risk is still presented as a procurement topic when it is increasingly a strategic resilience issue. A Board does not need a longer supplier inventory. It needs to understand where concentration, substitutability, recovery dependency, and service integration create fragility in the bank’s ability to deliver important services.

The same logic applies to privacy. Privacy reporting often becomes either legalistic or reduced to incident counting. Both approaches are too weak. A stronger approach is to report privacy as a question of trust, customer treatment, and decision quality. Are we using customer data in ways we can genuinely defend? Are controls reducing operational data sprawl or merely documenting it? Are cyber weaknesses, poor access design, or third-party handling creating conditions for privacy harm at scale?

What Board ready reporting should feel like

A good Board paper should leave directors able to answer a small number of hard questions with confidence. Which important services and customer outcomes are under the greatest pressure? Which dependencies and control weaknesses are creating that pressure? Which issues management is handling, and which require Board support or intervention. Where is the institution relying on an assumption rather than proof?

Also Read: What to actually prioritise when your board wants AI and everything feels urgent

Report in the language of consequence. Show the chain from cause to business impact. Make uncertainty visible. Connect control issues across domains. End with the decision management is really asking the Board to make.

If a pack cannot do those things, it is probably not Board-ready, no matter how polished the metrics may look.

Final thought

The future of governance in banking will not be won by institutions that collect the most cyber, privacy, vendor, and resilience data. It will be won by institutions that translate those issues into clear choices about service continuity, customer trust, risk appetite, investment, and management accountability.

Boards do not need another pile of fragmented indicators. They need a coherent narrative that tells them what matters, why it matters now, how confident management really is, and what decision is needed before the next disruption turns an unmade choice into a visible failure.

That is what decision-grade governance looks like.

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Editor’s note: e27 aims to foster thought leadership by publishing views from the community. You can also share your perspective by submitting an article, video, podcast, or infographic.

The views expressed in this article are those of the author and do not necessarily reflect the official policy or position of e27.

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Vietnam is preparing to test a more interventionist model for building technology companies, with the Ministry of Science and Technology proposing a National Venture Capital Fund with initial capital of US$100 million for the 2026-2028 period.

The proposal, discussed at a meeting of the government’s science, technology, and innovation committee on Tuesday, is designed to accelerate the commercialisation of strategic technologies and support the creation of competitive technology enterprises.

Also Read: Vietnam isn’t just inviting private capital in. It is structurally dependent on it

While US$100 million is modest by global venture capital standards, the plan is significant for Vietnam and the wider Southeast Asian startup ecosystem. It signals Hanoi’s intent to move beyond policy support and infrastructure building and towards direct participation in venture financing, particularly in sectors where private investors remain cautious because of long development cycles, uncertain exits, and high technical risk.

The fund is being modelled on Israel’s Yozma programme, one of the most cited examples of state-backed venture capital catalysing a private VC industry. Under the Vietnamese proposal, the state would lead the fund’s initial capital structure. From 2028 to 2035, the fund would gradually mobilise more private capital, with private investors expected to account for 30 to 40 per cent of total capital. The ministry has also proposed the development of separate funds for different technology sectors.

Vietnam’s deeptech funding gap

The timing is notable. Vietnam has emerged as one of Southeast Asia’s more dynamic startup markets, supported by a young digital population, a growing engineering workforce, and increasing interest from regional and global investors. However, much of the country’s startup funding has flowed into consumer internet, fintech, e-commerce enablement, and software businesses rather than harder technology categories.

That is not unique to Vietnam. Across Southeast Asia, deeptech, advanced manufacturing, semiconductors, climate technologies, biotech, and other research-heavy sectors often struggle to secure early-stage risk capital. These companies typically require longer gestation periods, specialised evaluation, patient funding, and stronger links between universities, laboratories, corporates, and investors.

Vietnam is trying to position itself more aggressively in strategic technologies as global supply chains shift and as multinational technology companies expand their presence in the country. The country has already attracted attention as a manufacturing base for electronics and is attempting to move up the value chain into higher-value technology development.

A national venture capital fund could help bridge the gap between research and commercialisation, especially if it can back companies emerging from universities, research institutes, and incubators. But the challenge will be turning a state-funded vehicle into a credible venture investor rather than another public-sector grant mechanism.

The Yozma inspiration and its limits

Israel’s Yozma programme, launched in the 1990s, helped seed the country’s venture capital industry by using government capital to attract foreign and domestic private investors. Its structure gave private investors strong incentives and helped create a commercially disciplined investment culture.

Also Read: Vietnam’s biggest PE bet of 2025 was not on tech. It was on what 100M people eat every day

Vietnam’s proposal borrows from that logic: state capital comes first, private capital follows, and specialised funds are created around priority sectors. In theory, this allows the government to absorb some early risk while encouraging private investors to participate once the model matures.

But transplanting Yozma-style models is rarely straightforward. Israel already had strong research universities, defence-linked technology capabilities, global diaspora networks, and deep connections to US capital markets. Vietnam has different institutional realities, including a younger VC ecosystem, fewer proven deeptech exits, and a capital market still developing mechanisms for valuing high-growth technology businesses.

The ministry appears aware of these constraints. It has identified the tension between venture capital’s risk-tolerant nature and the public-sector principle of preserving state capital as a major challenge. That tension is central to whether the fund can function effectively.

Risk cannot be managed deal by deal

Venture capital works because a small number of outsized winners compensate for many failures. Public capital management, by contrast, often penalises losses on individual investments, even when the overall portfolio performs well. If officials managing the fund are exposed to personal or legal liability for failed startup investments, the vehicle could become too conservative to achieve its purpose.

To address this, the ministry has proposed that fund performance be evaluated across the entire portfolio rather than on individual deals. It has also called for protection mechanisms for decision-makers who follow proper procedures.

This is a crucial point. Without such protections, fund managers may avoid genuinely risky strategic technologies and instead back safer, later-stage, or politically favoured companies. That would undermine the rationale for creating a venture fund in the first place.

The ministry has recommended that the government report to the National Assembly to issue a resolution creating a specific mechanism for the fund. This would include liability exemptions for officials managing state-funded venture capital, provided they comply with regulations. The goal is to enable controlled risk-taking in investments involving strategic technologies.

Governance will decide credibility

The proposed governance structure also points to lessons from past state-backed investment efforts in the region. The ministry has recommended market-based recruitment and compensation, autonomy for the fund’s investment council, and stronger ties with research institutes, universities, and technology incubators.

These details are important. A venture fund needs experienced investors, sector specialists, and the ability to make decisions quickly. If compensation is not competitive, the fund may struggle to attract talent from the private market. If investment decisions are too bureaucratic, promising startups may look elsewhere for capital.

Autonomy will also be closely watched by private investors. For the fund to crowd in capital rather than crowd it out, it must be seen as commercially disciplined, transparent, and free from excessive administrative intervention.

Southeast Asia has no shortage of government-backed funding initiatives, from Singapore’s deep pool of state-linked capital to Malaysia’s startup financing schemes and Indonesia’s efforts to mobilise domestic capital for technology and innovation. The strongest models tend to combine public-sector strategic direction with professional investment management and clear accountability frameworks.

Also Read: Why Vietnam is the next big thing for startups and corporate partnerships

Vietnam now appears to be moving in that direction, but execution will be decisive.

The exit problem

Perhaps the most difficult issue is not capital deployment but capital recovery. The ministry highlighted Vietnam’s underdeveloped exit ecosystem, including limited mechanisms for valuing technology companies and insufficient channels for investors to recover capital.

This is a broader Southeast Asian problem. IPO markets remain uneven for technology companies, M&A activity is still limited compared with the US or China, and many regional startups depend on later-stage funding rounds rather than clear exit pathways. For deeptech companies, the problem is even more acute because buyers are specialised and commercialisation timelines can be long.

If Vietnam wants private investors to account for 30 to 40 per cent of the fund’s capital in later phases, it will need to improve exit visibility. That could involve strengthening domestic capital markets, encouraging corporate acquisitions, creating clearer valuation standards, and deepening cross-border links with regional and global investors.

The proposed US$100 million fund is therefore not just a financing instrument. It is a test of whether Vietnam can build the institutional architecture required for a more sophisticated innovation economy.

If designed well, the fund could help turn public research into commercially viable companies and give Vietnam a stronger position in Southeast Asia’s emerging deeptech landscape. If designed poorly, it risks becoming another state capital vehicle constrained by caution, weak incentives, and limited exits.

For now, Hanoi has identified the right problems. The harder task will be building a fund that is allowed to take the risks venture capital requires.

The post Vietnam looks to Israel’s Yozma model for US$100M national venture fund appeared first on e27.

Global financial markets are currently undergoing a severe recalibration as the artificial intelligence trade unwinds. This paradigm shift is triggering a broad rotation out of high-flying momentum stocks and into defensive sectors. The contagion is evident across major Western indices. The S&P 500 retreated by 1.4 per cent to settle near 7,375, while the technology-focused Nasdaq Composite suffered a sharper 2.2 per cent decline. The Dow Jones Industrial Average demonstrated relative resilience, slipping a mere 0.09 per cent. Across the Atlantic, European markets also felt the pressure, with Stoxx 600 futures dropping approximately 0.9 per cent as they pulled back from recent record peaks.

The correction hit the Asia-Pacific region with exceptional force, driven by a sharp rout heavily weighing down high-flying technology and semiconductor firms. The MSCI regional benchmark plummeted 2.9 per cent. South Korea experienced the most dramatic fallout, with the KOSPI plunging roughly 10 per cent and triggering an automatic 20-minute trading halt. This massive wipeout was spearheaded by memory chip giants SK Hynix and Samsung Electronics, both of which cratered by over 12 per cent.

Japan saw the Nikkei 225 fall 3.6 per cent to close at 69,788.38, breaking below the critical psychological threshold of 70,000. In Greater China, the Hang Seng Index dropped 1.8 per cent to 23,445, cementing a bearish head-and-shoulders technical pattern, while local artificial intelligence software names like MiniMax tumbled 16 per cent intraday. The mainland saw the Shanghai Composite ease 1.4 per cent to 4,106 points, and the technology-reliant Shenzhen Component shed 3.2 per cent.

Beyond equities, the risk aversion sentiment extended to commodities and private technology valuations. Global oil prices retreated as geopolitical tensions in the Strait of Hormuz cooled, sending Brent crude down over one per cent to near US$76.95. In the technology sector specifically, Alphabet dived five per cent, and private aerospace titan SpaceX experienced a massive 16 per cent valuation crash. Investors are aggressively booking profits and pivoting out of growth areas into defensive pockets of the market, including select European semiconductor plays and financial institutions.

Also Read: From frontier to emerging: How Vietnam’s stock market rewrote the ASEAN playbook in 2025

This massive unwinding of the technology trade has created a direct spillover effect into digital assets, proving once again the tight correlation between traditional technology markets and cryptocurrency. Bitcoin has lost its clear upward direction and is currently wobbling in the US$62,000 to US$62,500 range.

The cryptocurrency broke key support levels two times during the Asian session before attempting to consolidate near US$62,370. Crypto buying power remains heavily constrained by stalled United States exchange-traded fund inflows and broader market anxieties regarding upcoming Federal Reserve monetary guidance.

The underlying catalyst for this synchronised selloff is a fundamental reevaluation of Federal Reserve interest rate expectations, accompanied by a slight spike in United States Treasury yields. Investors are aggressively pricing in the potential for a rate hike, forcing a rapid rotation out of growth assets. Market sentiment has turned decidedly bearish in the short term. This shift has triggered active prediction hedging on platforms like Kalshi and Polymarket, where speculative volume is surging as traders place bets on whether Bitcoin will test lower handles around the US$58,000 mark.

At the point of writing, Asia market has not started. Let’s see if it will go down further.

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When Meta announced that CRED founder and one of India’s most celebrated fintech entrepreneurs, Kunal Shah, would become the global CEO of WhatsApp, the Indian internet went predictably delirious. LinkedIn filled with tributes. Venture capitalists took victory laps. Across Southeast Asia, the story landed as another chapter in the South Asian diaspora’s march through Silicon Valley’s upper echelons.

But after more than a decade covering startup ecosystems across India and Southeast Asia, I have learnt one thing: the most important story is rarely the one generating the most LinkedIn posts.

The acquisition behind the appointment

The sequencing here is enormously crucial, and most celebratory coverage has glossed over it entirely. Meta did not simply hire Shah but it acquired his loyalty and credit-card management platform CRED for US$4.5 billion, with US$900 million injected as fresh capital. The CEO title came bundled with the deal. These two events are inseparable.

Also Read: China blocks Meta’s AI bet on Manus: What it means next

Founded in 2018, CRED raised over US$1 billion in VC funding and posted net losses of approximately US$175 million in its most recently reported financials. Its core product, a rewards platform for credit card holders, was never a conventional revenue-generating business. What it built, meticulously over the years, was something far more valuable to Meta: roughly 25 million verified, curated profiles of affluent, creditworthy Indians.

At US$4.5 billion, that works out to approximately US$180 per user or, stripped to essentials, around US$36 per high-quality financial profile. Meta did not buy an app but bought a dataset and a monetisation shortcut.

WhatsApp’s long-standing India problem

To understand why that dataset matters so urgently, consider WhatsApp’s peculiar India paradox. The county is WhatsApp’s largest market, accounting for approximately 26 per cent of its global user base, with around 15 million active WhatsApp Business accounts. By every measure of adoption, India is a triumph.

By when it comes to revenue, it is an embarrassment. WhatsApp contributes less than 2 per cent of Meta’s total global revenue, and India’s contribution to even that meagre figure is disproportionately small.

WhatsApp Payments, launched in India in 2018 amid breathless predictions that it would render the entire Indian fintech industry obsolete, never came close to delivering. PhonePe and Google Pay dominate UPI transactions. The failure was never about Indian consumers — they adopted digital payments with extraordinary enthusiasm — but about Meta’s inability to commit to the local execution focus the market demanded.

Also Read: Meta × Manus: The misread AI deal

That is the mandate Shah has actually been handed: fix the India monetisation problem, then export the playbook to Indonesia, Brazil, Nigeria, and every other large emerging market where WhatsApp dominates daily communication.

The question nobody is asking

This is where the celebration deserves serious scrutiny.

If CRED’s core asset is 25 million verified financial profiles of affluent Indians, what exactly happened to those profiles when the acquisition closed? India’s Digital Personal Data Protection Act 2023 requires explicit user consent before personal financial data is transferred to any third party. It restricts cross-border data transfers to countries on an approved whitelist, a list that remains unfinished, with the United States not yet on it.

Did CRED’s 25 million users individually and knowingly consent to their credit profiles being transferred to an American technology conglomerate? Or did nobody check?

Not a single Indian regulator publicly raised this question, nor a parliamentary inquiry was filed. The mainstream Indian press was too busy writing about a middle-class founder’s inspiring journey.

The contrast with how China handled a structurally similar situation is striking, not because Beijing’s authoritarian methods are worthy of admiration, but because the underlying principle is worth acknowledging.

When Meta reportedly invested US$2 billion in Manus AI, a Chinese startup that had relocated to Singapore, Beijing forcibly unwound the deal and called it a national security matter. Citizen data, it declared, is sovereign infrastructure. One need not endorse Beijing’s governance to recognise that this position is increasingly mainstream in serious technology policy circles, from Brussels to Singapore itself.

What the ecosystem is choosing not to see

Shah’s earlier venture, Freecharge, was sold to Snapdeal in 2015 for approximately US$400 million. Snapdeal offloaded it to Axis Bank two years later for around US$53 million, an 87 per cent write-down. As recently as FY25, Freecharge was still posting net losses of approximately US$5.6 million. One LinkedIn commentator put it bluntly: the business was never real. The exit was.

CRED followed a similar arc. Enormous capital raised, persistent losses, and then a multi-billion-dollar exit priced not on business fundamentals but on the future value Meta believes it can extract from the underlying data.

Shah, to his credit, is one of Indian startup culture’s more intellectually honest voices, and his elevation carries genuine symbolic weight. The critique here is not personal but systemic. He played by the rules the ecosystem created. The real question is why nobody changed those rules.

Two cheers, with conditions

For readers across Southeast Asia, the lesson is clear: the most consequential technology policy is the kind enforced before a deal closes, not debated after the data has already moved.

Also Read: Autonomous agents in performance marketing: A critical look at Meta’s US$2B Manus AI

Shah may yet prove to be exactly the leader who turns WhatsApp into the financial services giant Meta desperately needs. That possibility is genuinely exciting. But enthusiasm is not a substitute for accountability. And a good story is not the same thing as the whole story.

The post WhatsApp’s new CEO is the headline. India’s data is the story appeared first on e27.

As AI blurs the boundary between human and machine online, a new platform is making the case that proving you are a real person should be as fundamental and private as having a password.

World ID, developed by Tools for Humanity, is a digital identity credential designed to verify that a user is a unique human being without collecting or retaining personal information. The platform is now expanding across Asia, with Singapore serving as a key regional hub.

At its core, World ID functions as a modern proof of personhood. Andrew Hsu, General Manager for Singapore and Taiwan at Tools for Humanity, describes it in an email interview with e27 as “a modern-day blue checkmark for personhood” — one grounded not in celebrity or social standing, but in the simple fact of being human.

The practical applications span a wide range of industries. Concert ticketing platforms can use World ID to ensure tickets reach genuine fans rather than automated bots. Dating apps can confirm that profiles belong to real people. Enterprise tools can verify that the individual on a video call or behind a digital signature is who they claim to be. Partners already integrating the tech include Tinder in Japan, Zoom, DocuSign and Concert Kit, which has announced plans with the band 30 Seconds to Mars.

The bot problem World ID is built to solve

The platform emerges at a moment when traditional verification methods are under significant strain. Bots can now bypass CAPTCHAs more reliably than humans, and AI-generated documents are increasingly capable of deceiving legacy systems. Fraudulent accounts, deepfakes, and synthetic identities are no longer edge cases. They are, according to Tools for Humanity, a growing structural threat to digital trust.

Also Read: Vietnam looks to Israel’s Yozma model for US$100M national venture fund

“As AI advances, it is blurring the line between human and machine interactions online,” Hsu says, “making it harder to prove with certainty that a person is truly a person.”

World ID addresses this by separating the question of identity — who you are — from the question of personhood — that you are human.

How the Orb works

Verification is conducted through a device called the Orb. When a user downloads the World App and presents themselves at an Orb station, the device photographs their face and irises. These images are used to generate an encrypted code, which is split into randomised fragments and sent to the user’s device before being permanently deleted from the Orb.

The encrypted fragments are then compared across independent compute nodes run by third parties including universities using a process called Anonymised Multi-Party Computation. This confirms that the individual has not previously verified without revealing who they are. Neither World nor Tools for Humanity retains any personal information from the process, and users may delete their data at any time.

Independent security audits of the Orb and its software have been conducted by cybersecurity firms Trail of Bits and Theori, with results made publicly available. The underlying tech is open-source.

Also Read: Who am I in the age of AI? Identity, displacement, and awakening

Singapore as a regional blueprint

In Singapore, Orb stations have been deployed at self-serve locations through partners including Collin’s and Sakae Sushi restaurants, with community pop-ups also under way. Hsu describes Singapore as a “bellwether” for Southeast Asia, citing its strong public-private collaboration and high awareness of digital safety issues.

The company acknowledges that building public confidence will take time. Hsu frames education, accessibility and regulatory engagement as the three pillars of its approach to new markets — noting that trust, ultimately, “is earned over time and through consistent action.”

World ID is currently available to users aged 18 and above.

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Image Credit: World ID

The post Can World ID solve the internet’s fake human problem? appeared first on e27.

What does it take to tell a winning story? Through my experience working in public relations, insights management, and tech entrepreneurship, I’ve come to see that storytelling isn’t a soft skill. In 2026 and beyond, it’s analytical output.

The big companies know this. Job listings mentioning “storytelling” as a skill or headlined with titles like Head of Storytelling or Narrative Strategist now feature on Indeed at a growing rate, instead of the traditional communications manager or head of marketing titles. Job postings featuring the word “storyteller” have grown significantly.

Rapid growth of AI content has shifted messaging into a new territory: one where good-quality messaging has a chance to stand out in a pile of ever-growing AI slop.

Through my own successes and failures in business and entrepreneurship, I’ve realised that to communicate persuasively, to investors, customers, or partners, you cannot rely on surface-level messaging. When many businesses compete in trying to tell the same story, sell similar products, and stand out in a cluttered market, my advice is to follow one simple rule: be the most reliable.

For SMEs and startups, this can seem challenging. How can a small business seem more reliable than a large player?

How do we stand out in the noise of everyone yelling, “I’m the best!”?

The rise of AI sloppytelling

The harsh truth is that most businesses were not strong communicators to begin with, so many of us now turn to AI to write a convincing pitch deck, transform our slide headlines into winning mantras, or write our business plans for us: the one-click-win. We’ve come to depend on it because AI messaging is better than no messaging, right?

As a result, inauthentic AI-devised content is taking over. Much of this output lacks focus and conviction to make audiences feel at ease. A generic story doesn’t do the job of putting prospective customers at ease, especially when your competitor is larger, has bigger teams, a longer runway, or more experience.

Using AI to write your story will not make you reliable or convincing. It will make you unremarkable. I call it Sloppytelling!

AI produces stories that often lack impactful key messages. The one-liners that make people stop and think, evoke nodding heads, and build confidence in your offer. This is because AI is based on analysis of past collections of vast generic data sets, and your story is based on your data and yours alone. It comes from the conversations you’ve had with clients who signed on the dotted line, and from those who opted not to.

Also Read: The storytelling myth: Why narrative-first leadership is overrated

AI is also not a replacement for real stakeholder or customer feedback. The actual data about your product or service shapes the story you tell. Remember: storytelling is analytical.

Finally, I argue that you should not use AI for developing well-structured responses to tough questions. Tough questions almost deserve their own section here, but we know them well from job interviews, investor meetings, and our business development presentations. It’s the questions that broke us.

Strong storytelling is as much about creating those powerful one-liners as it is about building our defensive comebacks, the fortress of words that protects our business from scrutiny.

A framework for analytical storytelling

Storytelling that can change minds or close deals is usually built on lessons accumulated over time, often through difficult experiences with customers and stakeholders. We start to form an idea of the optimal story through our repeated encounters with the word “no.”

After nearly two decades in business, listening and learning from strong storytellers, my consultancy focuses, among other things, on helping SMEs learn to tell their stories well and build lasting connections through their words and messaging. I argue that there are ways to bypass the painful rejections, the time spent hearing our least favourite word, through approaching storytelling in a structured and analytical way.

As mentioned earlier, the first part of this is to focus on insights, specifically around answering three questions about your business:

• What makes our proposition unique?
• Why do we do this better than others?
• Which questions will kill our business?

While most companies focus on the first two questions, many fail to focus on the final question. This one is complicated because there are many questions that can kill us, and our stakeholders ask different questions based on their needs or concerns. You have strong storytelling when your pitch incorporates the answers to these questions, not just once, but repeatedly, until this is what your audience remembers.

How AI can support your storytelling

You should certainly use AI to build your story! The tools are there to make our work more efficient and save us time. The strongest value AI can provide is to support the analytical work and insights generation that feeds your story, the legwork you need to do before formulating your winning pitch. It can also help dot the i’s and cross the t’s after your story is written.

Also Read: How brands are crafting communities through the art of visual storytelling

Here is how I propose you use AI in your storytelling process:

• To get clarity into your business and support analytical insights
• To filter your content and spot patterns behind your key messaging
• To devise questionnaires for stakeholders or customers to uncover weaknesses
• To clean up grammar and phrasing

AI can save you time and handle some of the legwork, but it can’t get you all the way there in answering the three core questions.

The takeaway

Many people still think of storytelling as something soft, artistic, or nostalgic: a campfire, a childhood book, a good writer’s craft. But in business, storytelling is not a cosy blanket. It is the bare-bones framework that holds your relationships with stakeholders, customers, and prospective clients in place. For SMEs and startups, it can be one of the most powerful tools for competing with larger players.

In a market saturated with generic, AI-assisted messaging, the winners will not be the companies producing the most content. They will be the ones whose stories make a lasting impact. That starts with investing in analytical storytelling today.

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The post Why storytelling is no longer a soft skill but analytical output appeared first on e27.