How Venture Builders Reduce Startup Failure Risks

Startups often feel like walking a tightrope in a storm: one wrong step, one misstep in timing, market, or team, and everything falls. It’s no surprise that about 90% of startups fail overall. But in 2025, a different model is proving it can lower those odds: the venture builder. These are organizations that don’t just invest - they build. They nurture ideas, assemble teams, offer infrastructure, and walk alongside founders through early storms.

Here’s how venture builders are reducing failure risks - and what data and case studies show about their effectiveness.

The Stakes: Understanding Startup Risk

The numbers are stark. Many reports show failure rates over time are steep: roughly 10% of new startups fail within their first year, and between years two through five, majority of failures happen. By year ten, few survive. These aren’t just abstract stats, they represent teams who ran out of runway, misread market demand, or couldn’t piece together strong execution. That’s the baseline. Venture builders aim to shift those odds by intervening early on the common failure triggers.

What Venture Builders Do Differently

Venture builders provide what many startups struggle to assemble quickly: clarity of idea, team strength, operational support, and effective validation.

You can think of it this way: instead of solo founders trying to juggle everything - product, user-feedback, hiring, legal, finances - the builder supplies scaffolding. They often supply shared services (legal, HR, strategy), access to domain experts, and a process for iterating ideas before major investment. This means startups born inside builder models often avoid big, early mistakes.

There are multiple pieces to this, but one that researchers call out often is the capacity to test product-market fit before “going big.” Because builders usually demand early user feedback, safe prototyping, proof of concept. That early feedback loop weeds out ideas with weak demand.

Data & Case Studies: Proof in Practice

• Venture Studio Survival & Alive Ratios

A study called Big Venture Studio Research 2024 looked at hundreds of venture studios, hybrid builders, and corporate builders. They found that hybrid venture studios (those that combine venture studio activities with things like corporate building, accelerator, VC fund) have much higher survival rates: for every studio that closes, there are ~10.86 that remain alive. Corporate builders had ~9.3:1. Pure venture studios had lower survivorship: ~4.73:1.(That means builders which diversify or bring in hybrid functions tend to reduce risk further.

• Experienced Builders vs Novice Ones

McKinsey recently published findings in “The Three Building Blocks of a Successful Venture Factory” that more experienced venture builders are about twice as likely to achieve success compared to newcomer studios. Over time, with repeat efforts, their output (in revenue in fifth year) can be 12 times higher than that of novice studios. That suggests that venture builders don’t just reduce risk by the model - they get better at reducing risk as they build more companies.

• Corporate Venture Building vs Traditional Startup Paths

An article by CreativeDock noted that corporations using venture building (internally creating new startups or spin-outs) report success rates around 66% for their ventures, far above the 20-30% or so typical for venture capital backed startups or corporate ventures without structured building. They also say that venture building-born startups achieve better IRRs (~44% higher on average) compared to traditional startups, faster transitions from seed to Series A, and earlier exits (on average under 4 years) compared to 6-7 years typical elsewhere.

Human Stories Behind the Data

Consider a venture builder that continuously launches several projects per year. With the builder model, a given project might start not with a blank page, but with a research phase. Founders test assumptions: Is there demand? Can the technology or product be built affordably? Who is competition? These early experiments expose flaws early - low demand, wrong features - so adjustments are made before major investment.

Another important case is around the “business-building muscle.” McKinsey points out that entities that build many ventures develop repeated systems: standard ways to onboard teams, validate ideas, launch MVPs, spin-outs. Over time, they make fewer rookie mistakes - less duplicated effort, fewer misfires - so each new project starts from a stronger foundation.

What Failures Are Reduced

By virtue of these mechanisms, venture builders tend to reduce risk in several specific ways:

• Team risk: builders often match people with complementary skills rather than solo founders. They bring in domain experts early.

• Market risk: they test demand, refine product-market fit before big spends.

• Execution risk: shared infrastructure and expertise mean better supply chain, legal, hiring, finance practices early.

• Timing & capital risk: because builders tend to pace investment, control burn, and have staged funding, they avoid over-extension before product is solid.

These interventions don’t eliminate risk entirely. But they shift the risk curve substantially.

Broader Trends & What Investors Are Saying

Investors in 2025 say they want a higher floor - some guarantee of minimal failure, clearer paths from concept to growth. They like models where founders aren’t isolated. Where you can see how an idea was validated, how the team was assembled. Where overhead is shared and costs are lean early.

Corporations also find benefit: many large firms are adopting corporate venture building to create new growth engines. In one survey by EY-Parthenon, nearly 45% of executives from surveyed companies reported they have launched ventures in the last five years that now generate $100 million+ in annual revenue. Venture building gives them structure to do that.

Looking Ahead: What Makes a Builder Even More Robust

The data suggests certain traits make some venture builders better at reducing risk:

• Repetition: builders who launch many ventures learn faster.

• Hybrid or diversified models: studios that also do corporate venturing, VC funds, accelerators tend to have higher survival of their ventures.

• Strong validation early: demand testing before full build.

• Deep domain or technical competence: where builders understand industry/technology well, they avoid mis-positioning or under-estimating costs.

The Next Chapter

Startups will always carry risk. That’s part of what gives them upside. But a model growing in legitimacy in 2025 is one that doesn’t treat failure as inevitable, but as something to manage. Venture builders are showing how structured support, domain expertise, shared infrastructure, and repeated experience can tilt the odds in favor of survival.

For founders thinking of starting under a builder, the message is hopeful: you don’t have to brace for failure alone. For investors, it means better early signals, stronger teams, and less wasted cost.

In a world where capital is tighter and demands are higher, venture builders are proving to be more than trend - they might be the most reliable path through the startup storm.

Funding the Future: The Role of VCs and Sovereign Funds in Singapore’s Venture Studios

The venture studio model has redefined how startups are born. Instead of betting on lone founders, venture studios build companies from the ground up, pairing entrepreneurial talent with capital, infrastructure, and networks. But behind this model lies a critical question: who funds the future?

In Singapore, the answer increasingly comes from two powerful sources - venture capital firms and sovereign wealth funds. Together, they are shaping not just the trajectory of venture studios but the kinds of companies that will define Asia’s innovation landscape over the next decade.

Why Funding Matters in Venture Building

Traditional startups often begin with a small seed round, testing ideas with limited resources. Venture studios flip that dynamic. They require upfront investment to design infrastructure, hire operational teams, and support multiple ventures simultaneously. The model is capital-intensive, but it also increases the odds of producing sustainable startups.

This is why the involvement of venture capital (VCs) and sovereign wealth funds is so significant. They provide not only the capital but also the long-term vision needed to sustain venture studios through the uncertain early stages of building science-driven or industry-specific companies.

The Numbers Speak

In 2022, Singapore attracted more than US$11 billion in startup funding, according to Enterprise Singapore, with a growing share flowing into venture-building initiatives. The global venture studio market itself is projected to reach US$42 billion by 2027, up from around US$20 billion today, as reported by Global Startup Studio Network.

Within Singapore, sovereign wealth funds play a particularly influential role. Temasek Holdings, with assets exceeding US$287 billion, has been steadily increasing its exposure to early-stage innovation through vehicles like Xora Innovation, its venture-building arm. Meanwhile, GIC, with more than US$770 billion in assets under management, has also stepped up its participation in deeptech and sustainability-focused ventures, often co-investing alongside studios and VCs.

Case Study: Temasek and Xora Innovation

Temasek’s launch of Xora Innovation in 2019 was a milestone for Singapore’s venture building ecosystem. Xora focuses on commercializing breakthrough scientific research in fields like climate tech, healthcare, and advanced manufacturing. Unlike traditional VC, Xora doesn’t just invest - it co-builds, bringing together teams of scientists, operators, and entrepreneurs to create companies from scratch.
One example is its investment in Eavor, a geothermal technology startup developing closed-loop systems for renewable energy. By backing such ventures, Temasek shows how sovereign funds can align financial returns with global sustainability goals while anchoring these efforts in Singapore.

The Role of Venture Capital Firms

Venture capital firms, too, are leaning into the venture studio model. Global firms like Sequoia Capital and Vertex Ventures (the latter headquartered in Singapore) have backed startups emerging from studios, drawn by the de-risked nature of ventures that already have structured support and validation.

Antler, one of the world’s most prominent venture builders with a major base in Singapore, has partnered with VCs to scale its portfolio. Since its launch, Antler Singapore has created more than 100 startups, many of which have raised follow-on capital from leading VCs. This collaboration demonstrates a virtuous cycle: studios generate investable companies, while VCs provide the growth capital to scale them globally.

Why Sovereign Funds Matter More in Singapore

Singapore’s sovereign wealth funds bring something that private VCs alone cannot - patient capital. DeepTech, climate, and biotech startups often take years to become commercially viable. Sovereign funds like Temasek and GIC are uniquely positioned to absorb these long timelines while maintaining conviction in long-term returns.

Moreover, their participation signals confidence to the market. When a sovereign fund co-invests in a venture, it often catalyzes additional investment from global VCs, corporates, and even governments. This multiplier effect strengthens the ecosystem and accelerates the scale-up of ventures born in Singapore’s studios.

Singapore as a Regional Magnet for Capital

The presence of sovereign wealth funds also amplifies Singapore’s role as a capital hub for Southeast Asia. With over 650 million people, Southeast Asia represents one of the world’s fastest-growing digital economies, projected by Google and Temasek to reach US$330 billion by 2025. By anchoring venture studios in Singapore and funding them with sovereign-backed capital, the city-state effectively positions itself as the launchpad for ventures targeting this massive market.

The Challenges Ahead

While the alignment of VCs and sovereign funds has fueled the rise of Singapore’s venture studios, challenges remain. Venture building is resource-heavy, and not all studios will survive. There is also the question of focus: should capital prioritize moonshot DeepTech ventures with global ambitions, or scalable consumer-tech plays better suited for regional adoption?

Striking the right balance will be key. Too much emphasis on short-term gains risks diluting the transformative potential of venture building. Too much focus on moonshots without market validation risks creating science projects that never scale.

Looking Ahead: Funding the Next Decade

What’s clear is that the combination of VCs and sovereign wealth funds gives Singapore’s venture studios a uniquely powerful advantage. Venture capital brings agility and global networks, while sovereign funds provide stability and patience. Together, they create an ecosystem capable of nurturing bold ideas through the long road from concept to commercial success.

In the next decade, expect to see more sovereign-VC partnerships in Singapore’s venture building space, particularly in fields like climate tech, AI, and advanced manufacturing. These are areas where global challenges intersect with Singapore’s ambition to lead in innovation.

For founders, the message is clear: in Singapore, you don’t just get access to capital - you get access to aligned capital, designed to see you through the toughest years of building. For investors, the takeaway is equally strong: if you want exposure to the next generation of high-impact ventures in Asia, Singapore’s venture studios are where the story begins.

Singapore’s Role in Shaping the Next Wave of DeepTech through Venture Building

DeepTech refers to technologies rooted in scientific discoveries and engineering breakthroughs and it is increasingly seen as the foundation for solving humanity’s toughest problems. From climate resilience and quantum computing to advanced healthcare and space exploration, the promise of DeepTech extends far beyond incremental innovation. But building DeepTech startups is notoriously hard: they require long development cycles, heavy capital investment, and multidisciplinary expertise.

This is where Singapore is quietly taking center stage. Over the last decade, the city-state has positioned itself as one of Asia’s most compelling hubs for DeepTech innovation, not through chance but through a deliberate embrace of venture building. By pairing research talent with structured startup creation, Singapore is charting a path that could make it a global leader in translating science into scalable businesses.

The DeepTech Imperative

DeepTech is not just hype. According to Boston Consulting Group, DeepTech startups globally attracted more than US$60 billion in funding in 2023, double the levels seen in 2016. Yet the barriers to entry remain high. Unlike software startups, where a minimum viable product can be built in weeks, DeepTech ventures often require years of research before commercial viability.

Singapore has recognized both the challenge and the opportunity. With limited natural resources, the country has long invested in knowledge as its most strategic asset. Today, that strategy is paying off as its universities and research institutions - such as the National University of Singapore (NUS) and A-STAR - are increasingly integrated into venture-building pipelines.

A Government-Backed Ecosystem

The Singapore government has been one of the most active global backers of DeepTech venture building. Through initiatives like the SGInnovate Deep Tech Nexus Strategy, launched in 2017, the country committed more than US$150 million to support the translation of science into companies. SGInnovate itself has directly invested in over 100 DeepTech startups spanning fields like autonomous robotics, medtech, and agritech.

This model is designed not just to fund startups but to systematically derisk them. By offering labs, pilot facilities, and structured venture building programs, Singapore reduces the “valley of death” between academic research and commercial application.

Case Study: A-STAR Spinouts

One of the best examples of Singapore’s DeepTech venture building comes from A-STAR, the Agency for Science, Technology and Research. Over the past five years, A-STAR has spun out dozens of startups in biotech, advanced materials, and AI. Companies like Nanoveu, which develops nanotechnology-based films for optics and antiviral protection, have scaled regionally thanks to early support from A-STAR’s venture co-creation efforts.

Another case is RWDC Industries, a biodegradable plastics startup that originated in Singapore and has since raised more than US$135 million in growth funding. RWDC’s success underscores how research-driven ventures can become globally relevant with the right support structure.

Temasek and the Long-Term View

DeepTech requires patient capital, and few institutions embody patience better than Singapore’s sovereign wealth fund, Temasek. Through its venture-building arm Xora Innovation, Temasek partners with scientists and entrepreneurs at the very earliest stages, often before a commercial application is fully proven.

This long-term approach is critical. Traditional VCs often shy away from DeepTech because of long timelines, but venture studios like Xora de-risk the process by building operational capacity around founders. This allows breakthroughs in quantum computing or synthetic biology to be pursued without the pressure of unrealistic short-term returns.

Singapore as Asia’s Testbed

Another advantage lies in Singapore’s role as a testbed for emerging technologies. With its compact size, advanced infrastructure, and supportive regulators, the city-state often serves as a “living laboratory” for pilots.

For example, autonomous vehicle trials, drone delivery pilots, and next-gen biotech therapies have all been deployed in Singapore earlier than in most regional markets. This testbed status makes the country an attractive base for DeepTech venture builders: startups can validate complex technologies locally before scaling across Asia’s 650 million-strong Southeast Asian market.

Talent at the Core

DeepTech thrives on talent density, and Singapore has invested heavily in building a global research workforce. The country attracts scientists and engineers through initiatives like the Research, Innovation and Enterprise (RIE) 2025 Plan, which allocated US$25 billion to science and innovation over five years.

What sets Singapore apart is how this talent is integrated into venture building. Instead of leaving researchers isolated in academia, programs connect them with entrepreneurs, operators, and investors who can help translate breakthroughs into market-ready companies. This culture of collaboration is one reason why Singapore consistently ranks among the top 10 in the Global Innovation Index.

Looking Forward: Singapore’s DeepTech Ambition

The next decade will determine whether Singapore’s DeepTech bets pay off. The foundations are strong: government backing, venture studios, sovereign wealth participation, and global research talent. The challenge lies in scaling beyond local pilots into global leaders.

If Singapore’s studios can consistently produce DeepTech unicorns - companies solving real-world problems in energy, healthcare, and materials - it will cement its place not just as Asia’s DeepTech hub but as one of the world’s great innovation ecosystems.

For founders, Singapore offers a rare combination: scientific depth, supportive policy, and venture-building structures that reduce the odds of failure. For investors, it provides a gateway to high-potential DeepTech startups in Asia with the added security of government and sovereign fund alignment.

The message is clear: while Silicon Valley may dominate software, the next generation of world-changing science-driven startups could well be born in Singapore’s venture studios.

Why Singapore is Emerging as Asia’s Hub for Venture Building

Singapore has long been known as a global financial center, but in recent years, its ambitions have expanded beyond banking and trade. Today, it is carving out a reputation as Asia’s leading hub for venture building, the model where ideas are not just funded but systematically transformed into startups through the structured support of venture studios. While Silicon Valley remains the gold standard for startup culture, Singapore is demonstrating that the future of innovation in Asia might follow a different playbook.

The rise of venture building in Singapore is not accidental. It is the result of a deliberate strategy combining government foresight, investor appetite, and the city-state’s unique position as a connector between East and West. For founders and investors alike, Singapore is increasingly where the region’s most ambitious ideas are being tested, scaled, and launched into the world.

The Numbers Behind the Story

Singapore’s startup ecosystem has grown at a remarkable pace. According to Enterprise Singapore, the number of tech startups in the country jumped from around 2,800 in 2003 to more than 4,500 in 2023, employing tens of thousands of people and contributing significantly to GDP. In 2022 alone, venture funding in Singapore reached US$11 billion, accounting for more than 50% of all funding across Southeast Asia, according to DealStreetAsia.

But what’s most striking is not just the raw funding numbers. It is the structural shift toward venture building. More than 30 venture studios now operate in Singapore, ranging from independent builders like Antler, which has a strong base in the city, to corporate-backed and government-supported studios that focus on deeptech, fintech, and sustainability. This density is unmatched anywhere else in Asia, positioning Singapore as the natural hub for the model.

A Supportive Government Framework

One of Singapore’s most powerful advantages is the role of government policy. Agencies such as Enterprise Singapore and EDB (Economic Development Board) have actively fostered venture building by co-investing in studios, providing grants, and streamlining regulatory pathways for new businesses.

For instance, in 2020, the government launched the Startup SG Founder Venture Building Program, a scheme designed specifically to support venture builders in co-developing startups with entrepreneurs. This move signaled not only recognition of the venture building model but also a willingness to bet national resources on it.

The regulatory environment also plays a role. With a reputation for clarity, efficiency, and fairness, Singapore provides a rare sense of stability in a region where startups often grapple with red tape. For deeptech or highly regulated sectors like fintech and biotech, this regulatory clarity can make the difference between stagnation and scale.

Case Studies: Successful Venture Builders

The global venture builder Antler made Singapore its launchpad in Asia, running its residency program for founders and producing startups that have since expanded globally. In just five years, Antler Singapore has backed more than 500 founders and created over 100 startups, several of which have gone on to raise significant Series A and B rounds.

Another standout is Xora Innovation, the venture building arm of Temasek, Singapore’s sovereign wealth fund. Unlike traditional venture capital, Xora works directly with scientists and entrepreneurs to transform advanced research into scalable deeptech ventures. This model reflects Singapore’s ambition not just to create more startups but to anchor globally relevant ones in high-tech, defensible fields. These examples show how Singapore is positioning venture building not as a fringe experiment but as a central pillar of its innovation economy.

Location as a Strategic Advantage

Geography has always been part of Singapore’s success story, and venture building is no different. Situated at the crossroads of Southeast Asia, the city-state offers immediate access to a consumer market of over 650 million people, a young, digital-native population hungry for innovation. At the same time, Singapore remains deeply connected to Western capital markets, making it a natural bridge for global investors seeking exposure to Asia.

This dual access - emerging market scale on one side, developed-world capital on the other - is a rare combination. For venture studios looking to create startups that can expand regionally and scale globally, Singapore offers the perfect launchpad.

Why Founders Are Choosing Singapore

It’s not only investors and policymakers driving this momentum. Founders themselves increasingly see Singapore as the best place to build. The city offers one of the most connected startup communities in Asia, access to a deep pool of talent, and a cosmopolitan culture that values experimentation.

Entrepreneurs also appreciate the reduced risk profile that venture building offers. Instead of going it alone, they join studios that provide initial capital, expert support, and access to networks, dramatically improving their odds of success. For many, especially in capital-intensive sectors like biotech or climate tech, this support is the difference between a promising idea and a real company.

Looking Ahead

As venture building matures globally, Singapore is uniquely positioned to lead its adoption in Asia. With strong government support, growing investor participation, and an ecosystem of studios producing measurable results, the city-state has built the foundations of a venture building hub that rivals the best in the world.

The next chapter will depend on whether these studios can consistently produce companies that scale to unicorn status or become regional champions. If they do, Singapore won’t just be a hub for venture building - it will be the place where Asia’s most important startups of the next decade are born.

For founders, the message is clear: if you want to test bold ideas in Asia with a higher chance of survival, Singapore is the place to start. For investors, the message is equally strong: the most interesting stories in venture building are not just being written in Silicon Valley - they are unfolding right here, at the crossroads of the East.

Investing in Artificial Intelligence: Key Trends for Funds

Methodology: A Fund-Focused View on AI Investment Dynamics

This article draws from market reports, fund manager insights, and AI ecosystem analyses to outline the main trends shaping how venture, growth, and corporate funds are investing in artificial intelligence today. We look at deal activity, sector focus, and strategic themes guiding capital allocation.

In Brief: What Funds Need to Know

• AI deal volume remains strong, with funds focusing on core infrastructure, applied AI, and ethical frameworks.

• Large funds and corporate VCs are increasingly backing AI tools that reshape entire industries.

• Geopolitics, regulation, and responsible AI principles are playing a bigger role in diligence.

• The next wave of winners may emerge from vertical AI not general-purpose models.

AI Investment Is Maturing But the Opportunity Remains Huge

Over the past decade, funds have steadily increased their exposure to artificial intelligence. From early bets on core machine learning platforms to today’s more refined focus on vertical applications (healthcare AI, legal tech AI, climate AI), the landscape has evolved.

AI deal activity remains resilient even in cautious markets, as funds seek companies offering real, scalable applications rather than AI hype.

According to PitchBook, AI and machine learning startups captured over $50 billion in venture funding globally in 2024, with enterprise AI infrastructure and applied AI solutions leading the way.

Key Trend 1: From General AI to Vertical AI

• Fund managers are shifting attention from general-purpose AI tools to sector-specific solutions. Why?

• Vertical AI startups typically show faster paths to product-market fit.

• Customers value AI embedded in their existing workflows (e.g., legal document review, clinical trial analysis).

• Regulatory clarity is stronger in narrow-use cases.

Funds investing in AI are looking for companies that deeply understand their end markets, not just ones building horizontal tools.

Key Trend 2: Responsible AI Moves Front and Center

Ethical AI isn’t just a discussion point anymore, it's a diligence priority.

LPs increasingly expect funds to assess AI safety, bias mitigation, and explainability during investment screening. Startups offering transparency features (e.g., model audits, bias dashboards) are gaining an edge in fundraising.

Funds that position themselves as champions of responsible AI will not only de-risk portfolios but also build brand credibility with partners and regulators.

Key Trend 3: Corporate Venture Capital Is Leading in AI Scaling

Corporate funds are playing a growing role in AI funding rounds especially at the growth stage. Why?

• AI solutions often require integration with large enterprise systems.

• Corporate VCs provide go-to-market pathways AI startups need to scale.

• Strategic investors are focused on AI that directly augments their core business lines.

We see funds co-investing alongside corporates in areas like AI-driven cybersecurity, supply chain optimization, and predictive analytics.

Final Thought: What’s Next for AI-Focused Funds?

The AI gold rush is shifting from model-building to real-world deployment. Funds that succeed will:

• Back founders solving specific industry problems.

• Prioritize responsible, explainable AI.

• Align with partners who can accelerate adoption at scale.

For investors, artificial intelligence isn’t just a theme, it's becoming an essential part of any modern portfolio.

Is AI Transforming Venture Capital?

Methodology: Mapping AI’s Impact Across the VC Value Chain

This analysis draws from recent VC investment trends, AI tooling adoption across fund operations, startup market behavior, and published reports from leading firms in venture and enterprise AI. We focus on identifying how artificial intelligence influences sourcing, due diligence, portfolio support, and decision-making within venture capital firms, and whether it’s enhancing efficiency or replacing core human functions.

In Brief: What’s Changing?

• AI tools are being widely adopted for deal sourcing, screening, and due diligence.

• LPs are showing increased interest in VC funds with a defined AI advantage.

• New firms are emerging with AI-built investment platforms, offering algorithmically driven portfolios.

• Portfolio support is becoming more data-informed, from hiring intelligence to pricing optimization.

• The human element of venture capital: relationships, trust, judgment, remains irreplaceable, but it’s being redefined

Rethinking Venture Capital: Why Evolution Isn’t Optional

While venture capital has long been considered a relationship-driven business, it’s also a sector rich in data, startup metrics, founder backgrounds, market dynamics, and exit multiples. As these datasets grow, VCs are increasingly turning to AI-powered platforms to extract insight, surface opportunities, and reduce operational burden.

Tools like Affinity, PitchBook’s AI modules, and custom GPT-based systems are now used to automate initial sourcing and provide predictive scoring on potential investments. Some firms, like SignalFire and Zetta, have fully integrated AI into their scouting stack.

“What used to take weeks of founder outreach and CRM updates can now be done in hours,” says one GP at a data-native early-stage fund.

AI-Driven Deal Flow: Filtering Noise with Signal

One of AI’s most impactful applications has been in the triage of inbound deal flow. Firms now deploy models that rank incoming decks and emails based on historic performance patterns, investment thesis fit, and keyword matching.

Some early-stage firms are even experimenting with LLM-powered memo generation, allowing analysts to summarize founder calls and create investment memos in minutes rather than days.

However, this is not about removing human insight; it's about freeing teams to focus on founder evaluation, industry diligence, and partnership building.

Due Diligence Gets Smarter and Faster

Diligence used to be slow, expensive, and heavily manual. With AI, venture teams now automate:

• Market sizing analysis

• Competitor landscape mapping

• Sentiment tracking across social/web

• Technical benchmarking using code or API audits

Firms like a16z and FirstMark have invested in internal tools that run structured diligence pipelines, combining data scraping with analyst review. AI makes the process leaner without compromising depth.

Still, human interpretation, especially for early-stage, pre-revenue bets, remains essential.

AI at the Portfolio Level: Coaching and Insight at Scale

Beyond the investment decision, AI is reshaping how firms support their startups. From hiring intelligence (e.g,. identifying likely candidate attrition) to churn risk detection and customer segmentation, venture teams are leveraging platforms to give founders smarter feedback, faster.

Portfolio dashboards with embedded AI modules offer near real-time insights, transforming GPs into strategic advisors supported by robust tooling.
Some emerging fund models even offer “productized venture support”, giving founders access to plug-and-play AI toolkits as a default benefit of the partnership.

What AI Won’t Replace

For all its analytical power, AI has limitations. Venture remains a trust business. Relationship building, founder empathy, and strategic thinking still matter deeply, particularly at the earliest stages, where conviction often precedes data.

The winning firms in this new landscape won’t be the ones that replace people with bots, but those that use AI to scale what humans do best: pattern recognition, intuition, and judgment.

Final Thought: AI Is Reshaping Venture Quietly and Permanently

AI is not replacing venture capital but it is changing the pace, process, and precision with which it’s practiced. Firms embracing this shift are seeing faster cycles, smarter insights, and a competitive edge in both sourcing and portfolio management. Those resisting risk falling behind not because they can’t find deals, but because they’re spending time where AI can already add value. The future of VC isn’t fully automated. It’s augmented and the transformation is already well underway.

Why Do Venture Studios Attract Investors?

Methodology: Understanding Investor Interest Through Models, Outcomes, and Market Signals

This article is based on an analysis of venture studio performance data, institutional investor trends, and commentary from founders and fund managers across Europe and the U.S. It examines why LPs and corporate partners are increasingly backing the venture studio model, and how it aligns with capital-efficient innovation and risk mitigation.

In Brief: What’s Driving Interest?

• Venture studios reduce startup risk through internal ideation, shared operations, and early product-market fit support.

• Investors are drawn to the repeatable nature of the studio model and its portfolio optionality.

• Studios often deliver higher ownership stakes, clearer paths to scale, and shorter time to value realization.

• The model aligns well with corporate innovation strategies and emerging markets.

• Studio economics are evolving to appeal to both traditional LPs and hybrid backers.

The Studio Model Offers a More Controlled Startup Building Process

Unlike traditional VCs that back external founders, venture studios originate and launch companies in-house, providing founding teams, initial capital, and operational resources. From day one, the studio has owned a significant equity position and maintains strategic oversight.

For investors, this structure reduces early-stage chaos. Ideas are pressure-tested before teams are formed. Hiring, product development, and GTM are handled with experienced operators.

This disciplined approach to entrepreneurship improves the odds of success and makes capital deployment more predictable.

Portfolio Construction: More Shots on Goal, Less Waste

Venture studios are built for portfolio logic. Instead of betting big on a single founder or product, they launch multiple companies in parallel, iterate fast, and shut down underperformers early.

For investors, this reduces downside risk. Studios can reallocate capital, reuse talent, and recycle insights across ventures. A single studio may create 10–20 startups over a few years, all from a shared knowledge base and infrastructure.

This portfolio optionality is appealing to LPs looking for high upside with downside protection.

Ownership and Exit Potential Are More Attractive

Because studios are co-founders, they often retain 25–50% equity stakes in their startups at launch, significantly higher than typical VC-backed models.

This concentrated ownership means that when a studio-backed company succeeds, the returns are larger and more direct. For investors in the studio itself, this structure translates into more meaningful exit participation per win.

Moreover, studios often guide startups to exit-readiness faster. With shared legal, hiring, and product resources, time-to-Series A (and beyond) is compressed.

Alignment with Corporate and Institutional Capital

Studios are also uniquely suited for corporate venture partnerships and family office co-building.

Corporates like the model because it offers them a front-row seat to innovation without the risk of internal R&D. For family offices, studios provide a way to co-create meaningful, values-aligned businesses without needing to incubate from scratch.

The model’s transparency, governance, and strategy-first approach make it easier to manage risk while fostering long-term engagement.

Studios Are Building in Emerging and Underserved Markets

Studios are increasingly being used to catalyze innovation in emerging markets, where capital is scarce but talent is abundant.

By controlling startup formation centrally, studios reduce the operational risk of building in fragmented or early ecosystems. They also attract LPs interested in impact investing, climate solutions, and regional development without sacrificing returns.

This makes the model a compelling vehicle for mission-aligned funds, development finance, and global innovation networks.

Final Thought: Studios Offer a New Kind of Investor Alignment

The rise of venture studios isn’t just about better startup outcomes. It’s about better alignment between capital, creators, and customers.

Studios combine the creativity of entrepreneurship with the structure of private equity. For investors, this means fewer surprises, more visibility, and a clearer path from idea to exit.

As more LPs rethink how they allocate to early-stage innovation, the venture studio model will continue to gain traction not as a trend, but as a tool for sustainable, scalable company building.

How AI is Changing the Underwriting Process in B2B Insurance

The B2B insurance landscape is experiencing a seismic transformation. Traditional underwriting, once dominated by manual processes and lengthy decision cycles, is giving way to a new era powered by artificial intelligence. This shift isn't just evolutionary, it's revolutionary, fundamentally changing how insurers assess risk, price policies, and serve their commercial clients.

The Numbers Don't Lie: A Market in Rapid Transformation

The statistics paint a compelling picture of AI's meteoric rise in insurance. The global AI in the insurance market, valued at $8.13 billion in 2024, is projected to explode to $141.44 billion by 2034, representing a staggering 33.06% compound annual growth rate. This isn't just growth; it's a complete market reimagining. What makes this transformation even more remarkable is its pace of adoption. Recent industry surveys reveal that 77% of insurance companies are now in some stage of AI adoption across their value chain, a dramatic leap from just 61% in 2023. Among life and annuity insurers, the adoption rate soars even higher, with 82% having implemented generative AI in one or more business functions.

For underwriting specifically, the impact is particularly pronounced. AI-assisted underwriting has emerged as one of the largest use case segments for AI in insurance, with insurers reporting up to 40% improvement in underwriting efficiency when deploying AI tools.

Beyond Speed: The Multifaceted Revolution

The transformation extends far beyond simple automation. Modern AI systems are reshaping every aspect of the B2B underwriting process, creating value that compounds across multiple dimensions.

Risk Assessment Precision: Traditional underwriting relied heavily on historical data and underwriter intuition. Today's AI systems analyze vast datasets from connected devices, satellite imagery, social media, and IoT sensors. With experts estimating one trillion connected devices by 2025, the data available for risk assessment is expanding exponentially. This data deluge enables insurers to understand their commercial clients more deeply than ever before, resulting in pricing accuracy that was previously impossible.

Fraud Detection and Pattern Recognition: AI's pattern recognition capabilities have revolutionized fraud detection in commercial lines. By identifying irregular patterns and reducing subjective biases, AI systems can spot potential fraud that human underwriters might miss. This enhanced detection capability translates directly to improved loss ratios, with some insurers reporting decreases of 1-3% through intelligent recommendations on optimal application approval and quoting decisions.

Real-Time Decision Making: The traditional underwriting process often stretched across weeks or months for complex commercial risks. AI has compressed this timeline dramatically, enabling real-time analysis of applications and instant decision-making for many types of coverage. This speed advantage is particularly crucial in B2B markets where businesses need coverage quickly to support their operations.

The Technology Stack Driving Change

The AI revolution in B2B insurance underwriting isn't powered by a single technology but rather by a sophisticated ecosystem of interconnected tools and platforms. Machine learning algorithms process historical claims data to identify risk patterns, while natural language processing systems extract insights from unstructured documents like financial statements and business plans.

Computer vision technology analyzes satellite imagery and drone footage to assess property risks, while predictive analytics models forecast potential claims scenarios. Integration platforms connect these AI tools with existing underwriting systems, creating seamless workflows that enhance rather than replace human expertise.

The sophistication of these systems continues to evolve rapidly. Today's AI underwriting platforms can process multiple data sources simultaneously, cross-referencing business registration information, financial health indicators, industry risk factors, and real-time market conditions to generate comprehensive risk profiles within minutes.

Industry Leaders Driving Innovation

The competitive landscape is being reshaped by companies that successfully harness AI's potential. Planck, for example, raised $71 million in funding to develop its underwriting AI product, which now operates globally. Their platform demonstrates how specialized AI solutions can transform traditional underwriting approaches.

Similarly, major data companies like Experian are developing AI-powered solutions specifically for commercial insurance. Their "Hazard Tags" system provides comprehensive profiles of five million UK businesses, enabling insurers to make more informed underwriting decisions at scale.

The Path Forward: Challenges and Opportunities

Despite the remarkable progress, the journey toward AI-driven underwriting isn't without obstacles. Data quality remains a persistent challenge, as AI systems are only as good as the information they process. Regulatory compliance adds another layer of complexity, particularly in jurisdictions with strict data protection laws.

The human element remains crucial. While AI excels at processing vast amounts of data and identifying patterns, human underwriters bring contextual understanding and relationship management skills that complement AI capabilities. The most successful implementations combine AI's analytical power with human expertise and judgment.

Looking ahead, the integration of AI in B2B insurance underwriting will likely deepen rather than simply expand. As AI systems become more sophisticated and data sources multiply, underwriters will gain unprecedented insights into commercial risks. The question isn't whether AI will transform B2B insurance underwriting; it's how quickly and comprehensively this transformation will occur.

Final Thought

The transformation of B2B insurance underwriting through AI represents more than technological advancement, it's a fundamental shift toward data-driven, precise, and efficient risk assessment. With 36% of insurance technology experts identifying AI as their top innovation priority for 2025, the momentum behind this transformation continues to build.

For B2B insurers, the choice is clear: embrace AI-driven underwriting or risk being left behind by competitors who have harnessed its power. The insurers who successfully integrate AI into their underwriting processes won't just survive this transformation, they'll thrive in the new landscape of precision, speed, and insight that defines the future of commercial insurance.

The numbers, the technology, and the market momentum all point in the same direction. AI isn't just changing B2B insurance underwriting, it's revolutionizing it, one algorithm at a time.

The Next Generation of Insurtech Founders: Trends to Watch in Europe

Europe's  landscape is experiencing a remarkable transformation. While global funding may have cooled from pandemic highs, a new generation of founders is emerging with bold visions that could reshape the continent's €1.4 trillion insurance market. These entrepreneurs aren't just digitizing old processes, they're reimagining insurance from the ground up.

The Numbers Tell a Story of Resilience

Despite broader market challenges, Europeans are showing impressive resilience. Europe captured $1.1 billion in  investment in 2024, positioning itself as the second-largest market globally after the United States. More telling is the quality over quantity approach: the median early-stage  deal size has reached a record high, increasing from $2.5M in 2023 to $4M in 2024.

This isn't just about bigger checks, it signals investor confidence in European founders' ability to build substantial businesses. The UK leads the charge, but Berlin, Paris, and Amsterdam are emerging as serious contenders, each developing distinct specializations that reflect local market needs and regulatory environments.

AI-First Founders: Beyond the Hype

The most compelling trend among Europe's new  founders is their AI-native approach. Unlike previous generations who retrofitted AI into existing processes, these entrepreneurs are building from first principles.  that raised funding in 2024 are growing headcounts faster than others, by a median of 20% over the last 12 months, with many of these high-growth companies being AI-centric.

Take Berlin-based INSRD, which raised €500k in pre-seed funding in early 2024. Founder Stefan Balg, a serial entrepreneur with over a decade of experience, isn't just digitizing business insurance, he's using AI to predict and prevent risks before they materialize. This proactive approach represents a fundamental shift from reactive claims processing to predictive risk management.

The AI trend extends beyond risk assessment. European founders are leveraging machine learning for personalized pricing, automated underwriting, and real-time policy adjustments. This isn't theoretical, it's happening now, with tangible results in customer acquisition costs and retention rates.

The Embedded Insurance Revolution

Perhaps the most significant opportunity lies in embedded insurance, where coverage becomes seamlessly integrated into other products and services. Berlin's Embea exemplifies this trend, having raised €4 million to build a pan-European embedded life insurance platform. The company's approach reflects a broader understanding that modern consumers expect insurance to be invisible until needed.

This embedded approach is particularly relevant in Europe's fragmented market, where regulatory differences across countries have historically created barriers. Smart founders are turning this challenge into an advantage, building platforms that can adapt to local requirements while maintaining operational efficiency across borders.

The embedded model also addresses a critical pain point: insurance literacy. By integrating coverage into familiar purchase journeys, whether buying a phone, booking travel, or starting a business, these founders are making insurance more accessible and relevant to younger demographics who traditionally under-insure.

Climate-Conscious Innovation

European insurtech founders are uniquely positioned to lead in climate-related insurance innovation. Extreme weather drives insured losses 70% above historical norms, creating both challenges and opportunities for innovative coverage models.

Forward-thinking founders are developing parametric insurance products that pay out automatically when specific weather conditions are met, eliminating lengthy claims processes. Others are creating new coverage categories for climate adaptation technologies, renewable energy installations, and carbon credit portfolios.

This climate focus isn't just about risk management, it's about enabling the green transition. European founders understand that insurance can be a catalyst for sustainable business practices, not just a safety net.

Regulatory Navigation as Competitive Advantage

While many view Europe's regulatory complexity as a barrier, the smartest founders see it as a moat. Those who master compliance across multiple jurisdictions create defensible positions that are difficult for later entrants to replicate.

The regulatory landscape is also evolving in founders' favor. Open banking regulations have paved the way for open insurance initiatives, creating opportunities for data-driven underwriting and seamless policy management. Forward-thinking founders are building compliance-by-design approaches that will position them well as regulations continue to evolve.

The Funding Reality Check

The funding environment requires founders to be more capital-efficient than their predecessors. Investments are down, both in the number of deals inked (-32%) and euros invested (-54%) compared to peak years. However, this constraint is breeding innovation.

Today's European insurtech founders are focusing on faster paths to profitability, often through partnerships with traditional insurers rather than trying to replace them entirely. This collaborative approach is proving more sustainable than the disruption-focused strategies of earlier insurtech waves.

The successful founders are also more sophisticated about timing their fundraising, often achieving significant milestones with smaller initial rounds before pursuing larger growth capital. This approach builds stronger businesses and more attractive investment cases.

Demographic Shifts Drive Innovation

Europe's aging population and changing work patterns create unique opportunities for innovative insurance products. Gig economy workers, remote professionals, and portfolio careers all require flexible insurance solutions that traditional products can't address.

Smart founders are building usage-based models that align cost with actual risk exposure. Whether it's pay-per-mile car insurance for occasional drivers or project-based professional indemnity for freelancers, these products reflect how people actually live and work.

The generational shift is equally important. Digital natives expect insurance to be as intuitive as their banking or shopping apps. Founders who nail the user experience have significant advantages in customer acquisition and retention.

Looking Ahead: The Platform Play

The most ambitious European founders are building platforms rather than products. They understand that the real opportunity lies in becoming the infrastructure layer for insurance across multiple verticals and geographies.

This platform approach leverages Europe's strengths: regulatory expertise, technical talent, and market diversity. By building once and deploying many times across different markets and use cases, these founders can achieve the scale needed to compete globally.

The Next Chapter

Europe's next generation of founders operates in a more mature but still rapidly evolving market. They combine the technical sophistication of their predecessors with a deeper understanding of regulatory realities and customer needs. The most successful won't just build better insurance companies, they'll create entirely new categories of risk management that we can't yet imagine. In a continent where innovation meets regulation, where tradition confronts disruption, these founders are writing the next chapter of European.

The trends are clear: AI-native thinking, embedded experiences, climate consciousness, regulatory savvy, and platform approaches. The founders who master these elements while maintaining capital discipline will define European insurtech's next decade.

For investors, partners, and industry observers, the message is equally clear: the most interesting European stories are still being written.

AI in Insurance: From Claims Automation to Risk Prediction

The insurance industry stands at the precipice of a technological revolution. What once required weeks of manual processing, stacks of paperwork, and armies of adjusters can now be accomplished in hours through artificial intelligence. The transformation isn't just impressive, it's reshaping the entire economic landscape of risk management.

The Numbers Tell the Story

The statistics are staggering. The global artificial intelligence (AI) in insurance market size is projected to hit around USD 141.44 billion by 2034 from USD 8.13 billion in 2024 with a CAGR of 33.06%. This exponential growth reflects more than just technological adoption, it represents a fundamental shift in how insurers operate, compete, and serve customers.

By 2024, 80% of insurance executives believe that AI-driven automation will be a key factor in improving efficiency and customer engagement. This isn't wishful thinking; it's a strategic necessity in an increasingly competitive marketplace where customer expectations for speed and service continue to rise.

 Claims Processing: The Speed Revolution

Perhaps nowhere is AI's impact more dramatic than in claims processing. Traditional claims handling, with its lengthy investigations and manual reviews, is being transformed into streamlined, automated workflows. AI automates the traditionally slow claims processing, reducing the time from weeks to just a few days or even hours.

Consider the practical implications: a fender-bender that once required multiple phone calls, adjuster visits, and weeks of processing can now be handled through a smartphone app that uses computer vision to assess damage, cross-references repair costs, and approve payment, all within minutes of the incident.

Claims processing in 2030 remains a primary function of carriers, but more than half of claims activities have been replaced by automation. McKinsey's research suggests we're already well on our way to this future, with advanced algorithms handling initial claims routing and IoT sensors providing real-time data capture through technologies like drones.

The customer experience transformation is equally significant. AI-powered chatbots and virtual assistants are used to provide 24/7 support to customers, helping them file claims and answer queries. This means policyholders no longer need to wait for business hours or navigate complex phone trees; assistance is available instantly, whenever disaster strikes.

 The Fraud Detection Arms Race

Insurance fraud represents a massive financial drain on the industry, with insurance fraud costs $6 billion annually, and insurers lose at least 10% of their premium collection to insurance fraud. But AI is leveling the playing field in unprecedented ways.

• The potential savings are enormous. Deloitte predicts that, by implementing AI-driven technologies across the claims life cycle and integrating real-time analysis from multiple modalities, P&C insurers could reduce fraudulent claims and save between US$80 billion and US$160 billion by 2032.

• However, the challenge is evolving rapidly. Insurance fraud increased by 19% from synthetic voice attacks in 2024, with sophisticated AI-generated deep fakes and voice cloning creating new categories of fraud that traditional detection methods simply cannot identify.

• The response from insurers has been equally sophisticated. AI systems now analyze patterns across vast datasets, identifying subtle anomalies that human investigators might miss. These systems can detect everything from staged accidents to inflated medical claims by analyzing behavioral patterns, cross-referencing databases, and identifying inconsistencies in real-time.

 Risk Prediction: The Crystal Ball Effect

• Beyond processing existing claims, AI is revolutionizing how insurers predict and price risk. Machine learning algorithms analyze millions of data points, from satellite imagery showing property conditions to IoT sensors monitoring driving behavior, to create highly accurate risk profiles.

• This granular risk assessment enables dynamic pricing models that adjust premiums based on real-time risk factors. A homeowner who installs smart security systems might see immediate premium reductions, while a driver who demonstrates consistently safe behavior through telematics could earn ongoing discounts.

• The implications extend beyond individual policies. Insurers can now predict natural disaster impacts with greater accuracy, optimize their risk portfolios, and even provide early warning systems to policyholders to prevent losses before they occur.

Investment Priorities and Market Focus

• AI garnered the largest share of experts, about 36%, who weighed in on what the top tech innovation priority for the coming year was. Big data and analytics were the second highest with 28%, followed closely by cloud and digital infrastructure with 26% of respondents.

• This investment pattern reveals a clear strategy: insurers are building comprehensive AI ecosystems rather than implementing isolated solutions. The combination of AI, big data analytics, and cloud infrastructure creates a powerful platform for innovation across all aspects of insurance operations.

• While AI monetization lags, embedded insurance is set to grow by 30%, especially in personal lines. This suggests that while the technology is maturing rapidly, the industry is still learning how to fully capitalize on its potential.

Real-World Applications

The theoretical benefits of AI in insurance are compelling, but the real-world applications demonstrate its transformative power:

• Auto Insurance: Computer vision analyzes accident photos to assess damage severity and estimate repair costs instantly. Telematics devices monitor driving behavior to adjust premiums dynamically and even predict potential accidents before they occur.

• Property Insurance: Satellite imagery and weather data help insurers assess property risks and predict natural disaster impacts. Drones inspect hard-to-reach areas for damage assessment, reducing both time and safety risks for human inspectors.

• Health Insurance: AI analyzes medical records to identify potential fraud, predict health outcomes, and optimize treatment recommendations. Machine learning algorithms can even identify patients at risk for specific conditions, enabling preventive interventions.

• Life Insurance: Underwriting processes that once took weeks now occur in minutes through AI analysis of medical records, lifestyle data, and risk factors. This dramatically improves the customer experience while maintaining rigorous risk assessment standards.

The Road Ahead

• The integration of AI in insurance represents more than technological upgrade, it's a fundamental reimagining of how risk is assessed, managed, and transferred. As we move forward, the insurers who successfully leverage AI will enjoy significant competitive advantages through improved efficiency, better risk selection, enhanced customer experiences, and reduced fraud losses.

• The transformation is accelerating, driven by technological advancement, competitive pressure, and changing customer expectations. For insurance professionals, understanding and adapting to this AI-driven future isn't just an opportunity, it's an imperative for survival in an increasingly digital marketplace.

• The question isn't whether AI will transform insurance, it's how quickly insurers can adapt to harness its full potential while maintaining the trust and reliability that remain the foundation of the industry.

Final Thought

As we stand at this technological crossroads, the insurance industry faces a defining moment. The companies that embrace AI today aren't just adopting new tools, they're positioning themselves to lead tomorrow's market. The convergence of artificial intelligence with traditional insurance principles creates unprecedented opportunities to serve customers better, operate more efficiently, and build more resilient businesses. In this rapidly evolving landscape, the winners won't be those who resist change, but those who thoughtfully integrate AI while preserving the human elements that make insurance truly valuable: empathy, trust, and the promise of protection when it matters most.

From Payment Rails to Embedded Finance: What VCs Are Betting on in Fintech

The fintech revolution has evolved far beyond simple payment apps and digital wallets. As we advance through 2025, venture capitalists are recalibrating their strategies, moving away from traditional fintech plays toward sophisticated infrastructure and embedded financial services that promise to reshape how businesses and consumers interact with money.

The Great Fintech Reset: Where the Smart Money Is Going

The numbers tell a compelling story of transformation. While overall VC investment in fintech remains near six-year lows, strategic investors are doubling down on specific segments that demonstrate exceptional growth potential. The embedded finance market, valued at $104.8 billion in 2024, is projected to explode to $690.39 billion by 2030, a staggering 36.4% compound annual growth rate that has captured the attention of sophisticated investors worldwide.

This isn't just another tech trend. It represents a fundamental shift in how financial services are delivered, consumed, and integrated into daily life. Smart VCs recognize that the future belongs to companies that can seamlessly weave financial functionality into existing platforms rather than building standalone financial products

Payment Rails: The Infrastructure Play That's Paying Off

The backbone of modern finance is undergoing a radical transformation, and investors are taking notice. FedNow, the Federal Reserve's instant payment system, is processing $190 million in payments daily, while Real-Time Payments (RTP) networks reported a remarkable 94% increase in transaction volume throughout 2024. This explosive growth has tripled participation in instant payment rails over the past year, with over 1,200 financial institutions now connected to these systems.

For VCs, this represents more than just impressive statistics, it signals a massive opportunity in payment infrastructure. Companies building the pipes that enable instant, seamless transactions are attracting significant investment because they're positioned to capture value from every transaction flowing through their systems. The shift from traditional payment processing to instant settlement creates entirely new revenue streams and business models that savvy investors are eager to fund.

Embedded Finance: The Trillion-Dollar Opportunity

The embedded finance sector is where VCs are placing their biggest bets, and the data supports their enthusiasm. Multiple market research firms project the sector will reach between $570.9 billion and $1.73 trillion by 2033, depending on adoption rates and regulatory environments. These aren't just optimistic projections, they're backed by real market momentum.

Consider the rapid expansion beyond traditional sectors. Healthcare, construction, and hospitality, industries previously slow to adopt financial technology, are now integrating tailored financial services directly into their platforms. This expansion is driving what investors call the "invisible finance" trend, where financial services become so seamlessly integrated that users barely notice they're engaging with sophisticated financial products.

The retail sector alone demonstrates the power of this shift. Fintech companies have grown from handling 22% of personal loan originations in 2019 to approximately 39% in 2024. This isn't just market share displacement, it's evidence of a fundamental change in how consumers prefer to access financial services: embedded within the platforms and services they already use.

The AI Wild Card: Intelligent Financial Services

Artificial intelligence has emerged as a bright spot in an otherwise cautious investment environment. VCs are particularly excited about AI applications that enhance embedded finance platforms, enabling real-time credit decisions, personalized financial products, and predictive analytics that can anticipate user needs before they're explicitly expressed.

The convergence of AI and embedded finance is creating opportunities for companies to offer hyper-personalized financial services at scale. For investors, this represents the holy grail of fintech: technology that can increase conversion rates, reduce risk, and create sticky customer relationships simultaneously.

Geographic Hotspots: Where the Action Is

The global nature of fintech investment is creating interesting regional dynamics. China's embedded finance market is expected to grow at a remarkable 32.8% CAGR through 2030, driven by tech giants like Alibaba and Tencent integrating financial services into their ecosystems. Meanwhile, India is witnessing significant growth with a 19.5% CAGR, fueled by a massive underbanked population and supportive regulatory environment.

These geographic variations are creating opportunities for VCs to invest in region-specific solutions that can later be adapted for global markets. The most successful fintech companies are those that can navigate diverse regulatory environments while maintaining their core value propositions.

The Regulatory Reality Check

Smart investors are also paying close attention to the regulatory landscape. Increased regulation, predicted as one of the top fintech trends for 2025, isn't necessarily a headwind, it's an opportunity for well-positioned companies to create competitive moats. Firms that can navigate complex compliance requirements while maintaining user experience advantages are attracting premium valuations.

The regulatory environment is actually accelerating the embedded finance trend, as companies seek to partner with established financial institutions rather than navigate licensing requirements independently. This creates opportunities for B2B fintech companies that can serve as bridges between traditional financial institutions and technology platforms.

The Investment Thesis: Infrastructure Over Apps

The most successful fintech VCs are shifting their focus from consumer-facing applications to the infrastructure that powers them. The companies receiving the largest funding rounds are those building the rails, APIs, and platforms that enable other businesses to offer financial services seamlessly.

This infrastructure-first approach reflects a mature understanding of the fintech ecosystem. While consumer apps can achieve viral growth, infrastructure companies build sustainable, defensible businesses with predictable revenue streams and strong network effects.

Looking Forward: The Next Wave

As we move deeper into 2025, the fintech landscape is being reshaped by three key forces: the maturation of instant payment rails, the explosive growth of embedded finance, and the intelligent application of AI to financial services. VCs who understand these dynamics and invest accordingly are positioning themselves to capture outsized returns in what promises to be the most transformative period in financial services history.

The message is clear: the future of fintech isn't about building better banking apps, it's about making finance invisible, instant, and intelligent. The companies and investors who embrace this reality will define the next decade of financial innovation.

Final Thoughts

The fintech evolution we're witnessing today represents more than just technological advancement, it's a fundamental reimagining of how financial services integrate into human and business experiences. For venture capitalists, this moment presents both unprecedented opportunity and significant risk. 

The data overwhelmingly supports one conclusion: the age of standalone fintech products is ending, and the era of invisible, embedded financial services has begun. The question isn't whether this transformation will happen, it's whether investors will have the vision to back the companies that make it reality.

Venture Studio vs. Incubator vs. VC Fund: What Are the Differences?

In the startup world, founders have more pathways than ever to launch and grow their businesses. Venture studios, incubators, and VC funds are some of the most common models, but they’re often confused. Each plays a different role in a startup’s journey, and understanding how they work can help you choose the right support at the right time.

After reviewing real-world examples, startup reports, and founder experiences, this article breaks down how each model works, how they differ, and when they are most useful.

Venture Studios Create Startups From Scratch

Venture studios don’t wait for external founders to pitch them ideas. Instead, they come up with startup concepts internally and build them in-house. The studio handles early research, product development, branding, and even hires founding team members.

The goal is to create multiple startups each year, test them quickly, and scale the most promising ones. Studios usually retain a large share of equity in the companies they build and stay involved long term. This model offers strong support but less ownership for incoming founders.

Example: Atomic is a top venture studio that co-founded companies like Hims and Bungalow. It provides full support, from engineering to legal, giving startups a strong foundation.

Venture studios are still relatively new compared to incubators and VC funds. Globally, there are estimated to be 500–700 venture studios, while there are thousands of VC funds and incubators. This model shows how investors are moving earlier into the startup lifecycle, often building startups from scratch so that investment and company creation happen simultaneously. Venture studios also reflect a growing trend of investors getting involved earlier in the innovation process, from the ideation phase onward. Unlike traditional VC funds that invest after a product or business model is validated, venture studios combine capital and company creation at the same time. This trend shows how the line between ‘builder’ and ‘investor’ is increasingly blurred.

Incubators Help Early-Stage Founders Shape Their Ideas

Incubators are designed for individuals or teams that already have a startup idea and need help turning it into a viable business. They typically offer mentorship, training sessions, office space, and sometimes small amounts of seed funding.

Most incubators run structured programs that last a few months. Founders join a cohort, attend workshops, get access to experienced mentors, and leave with a more developed product and pitch. The equity taken is usually minimal, and the focus is more on growth than ownership.

Example: The Founder Institute helps first-time founders get started by providing a step-by-step curriculum, access to a network of mentors, and feedback from experienced entrepreneurs.

VC Funds Invest in Startups That Are Ready to Grow

Venture capital funds work differently. They invest money into startups that already have a product, some traction, or a proven business model. VC funds are made up of pooled capital from outside investors called Limited Partners (LPs), and they typically take minority ownership in startups.

VCs don't build startups or run structured programs. Instead, they provide funding, advice, and connections to help companies grow faster. Founders usually seek out VC funding when they need to scale operations, expand into new markets, or hire aggressively.

Example: Andreessen Horowitz is a leading VC firm that has invested in companies like Airbnb and Coinbase. It provides both capital and high-level strategic support.

Key Differences Between Venture Studios, Incubators, and VC Funds

When they get involved:

• Venture studios come in at the idea stage. They build startups from zero, often without an external founder involved at first.

• Incubators support startups that are just beginning and need help shaping their ideas.

• VC funds invest in startups that are already operating and need capital to grow.

How they operate:

• Venture studios act like co-founders. They are deeply involved in building the company and typically stay long term.

• Incubators act as mentors and program hosts. They guide founders through the early stages but usually step back after the program ends.

• VC funds act as investors. They fund startups, join boards, and provide access to additional resources.

What they offer:

• Venture studios provide internal resources, team members, capital, and strategic direction.

• Incubators offer mentorship, training, and sometimes small funding or services.

• VC funds offer larger amounts of capital and help with scaling strategies, fundraising, and hiring.

Equity expectations:

• Venture studios usually take a significant equity stake, often ranging from 30 to 80 percent depending on how much they contribute.

• Incubators take a small equity stake, often around 5 to 10 percent.

• VC funds typically take between 10 to 30 percent, depending on the round and valuation.

Which Model Is Right for You?

The right model depends on where you are in your startup journey.

If you want to build a company but don't yet have an idea or team, a venture studio could be your best option. You’ll get full support, but you’ll share more equity.

If you have a startup idea but need help turning it into something real, an incubator is a great choice. You'll learn, build, and grow with peers, while keeping most of your ownership.

If your product is live and you're looking for funding to expand, a VC fund is the natural next step. You’ll raise larger sums in exchange for equity and get access to high-level strategic support.

Final Thoughts

Venture studios, incubators, and VC funds all aim to build successful startups, but they approach that goal in very different ways. Choosing the right one depends on your stage, goals, and how much ownership or involvement you’re willing to trade for support.

For founders who understand these differences, the startup journey becomes clearer and more strategic, and the chances of building something meaningful increase significantly. As more investors move upstream, the choice of partner; whether studio, incubator, or VC, is more strategic than ever.

Où vont les investissements VC en 2025 ?

L’année 2025 marque un tournant pour le capital-risque. Après une période de correction marquée par la prudence post-2021, les investisseurs reviennent sur le marché avec une vision plus sélective, plus stratégique, mais toujours ambitieuse. Certaines tendances se confirment, d’autres émergent, dessinant une nouvelle cartographie des secteurs les plus prometteurs.

Alors, où va l’argent du capital-risque cette année ? Voici un panorama des secteurs qui attirent le plus l’attention (et les fonds) des VC en 2025.

Le climat et la transition énergétique restent en tête des priorités

Le climate tech continue de séduire les investisseurs, porté par l’urgence climatique, les politiques européennes ambitieuses, et l’engagement des nouvelles générations.
En 2025, les fonds se tournent vers des solutions plus matures : stockage d’énergie, électrification industrielle, infrastructures vertes, et technologies de capture du carbone.

Les startups capables de combiner impact environnemental mesurable et viabilité économique deviennent les stars des portefeuilles VC. Les fonds créent même des équipes spécialisées pour capter les meilleurs dossiers du secteur.

L’intelligence artificielle passe du battage médiatique à l’adoption concrète

L’IA reste incontournable, mais l’approche évolue. Après l’explosion des modèles de langage et des outils génératifs en 2023–2024, les investisseurs misent désormais sur les applications sectorielles de l’IA : santé, logistique, cybersécurité, finance, éducation.

Les startups qui se contentent de “surfer sur l’IA” sans preuve d’utilité sont écartées. En revanche, celles qui intègrent l’IA pour résoudre des problèmes précis avec efficacité reçoivent un accueil très favorable.

La santé digitale et la biotechnologie reviennent au cœur des portefeuilles

Le secteur de la santé retrouve un second souffle en 2025. Les investisseurs ciblent des startups en healthtech, biotech et medtech, surtout celles qui allient innovation technologique et compréhension fine des besoins des patients.

On observe un fort intérêt pour les solutions liées à la santé mentale, la longévité, la médecine préventive, et la personnalisation des traitements via la donnée. La convergence entre technologie et biologie attire des tickets plus importants qu’auparavant.

La fintech se transforme, mais reste attractive

La fintech traverse une phase de consolidation, mais les projets solides continuent de lever. En 2025, les VC préfèrent des modèles plus résilients : infrastructure financière, outils B2B, sécurité des paiements, gestion d’actifs numériques.

Les néobanques et les solutions de paiement grand public ont moins la cote, sauf si elles affichent une rentabilité réelle et une différenciation claire. L’heure est à la maturité dans ce secteur autrefois surchauffé.

L’éducation et la formation professionnelle attirent un intérêt renouvelé

Le monde post-pandémie a changé la perception de l’éducation. En 2025, les investissements VC se dirigent vers des plateformes d’apprentissage continu, formation technique, et outils de requalification.

L’essor de l’IA et de l’automatisation crée une pression sur les compétences : les startups capables de proposer des formats flexibles, accessibles et certifiants rencontrent une forte demande — aussi bien du côté des particuliers que des entreprises.

L’agritech et la foodtech s’imposent comme des verticales stratégiques

La sécurité alimentaire et la durabilité deviennent des enjeux géopolitiques majeurs. En réponse, les VC s’intéressent aux innovations en agriculture régénérative, production locale, biotechnologie alimentaire, et logistique intelligente.

Des startups développant des alternatives aux pesticides, des capteurs intelligents pour les sols, ou des solutions d’agriculture verticale lèvent des fonds dans toute l’Europe. Ces technologies sont vues comme des leviers essentiels pour un futur résilient.

Moins de hype, plus de preuves

Ce qui caractérise les investissements VC en 2025, c’est une exigence renforcée de traction, de viabilité et d’impact concret. Les investisseurs recherchent des preuves : chiffre d’affaires, rétention, adoption, partenariats, réglementation maîtrisée.

L’époque des levées à neuf zéros sans produit fini est révolue. Désormais, l’équilibre entre vision ambitieuse et rigueur opérationnelle est la clé.

Conclusion : une année d’innovation responsable

En 2025, le capital-risque ne ralentit pas, il se réinvente. Les investissements se concentrent sur des secteurs à fort impact, où l’innovation technologique rencontre des besoins réels, sociétaux, et environnementaux. Cette évolution marque une nouvelle maturité de l’écosystème européen.

Pour les fondateurs, cela signifie qu’il faut allier audace, exécution, et alignement avec les grandes transitions du monde. Pour les investisseurs, 2025 est l’année où le capital-risque devient plus stratégique que jamais.

Pourquoi les insurtechs attirent autant les investisseurs ?

L’assurance n’a jamais été un secteur synonyme d’innovation rapide. Pourtant, depuis quelques années, les startups de l’insurtech bouleversent ce paysage traditionnel avec des approches digitales, agiles et centrées sur l’expérience utilisateur. Résultat : elles attirent des milliards d’euros d’investissement à travers le monde, et l’Europe n’est pas en reste.

Mais qu’est-ce qui rend les insurtechs si séduisantes aux yeux des investisseurs ? Voici les raisons clés.

Un marché colossal en attente de disruption

Le secteur de l’assurance représente des milliers de milliards d’euros de primes chaque année, avec une forte concentration d’acteurs historiques. C’est un marché immense, mais souvent lent, opaque et peu centré sur le client. Pourtant, l’insurtech connaît une croissance rapide : en 2023, les investissements mondiaux dans ce secteur ont dépassé les 4 milliards de dollars, malgré un contexte macroéconomique difficile. 

Cette dynamique s’est poursuivie en 2024, avec plus de 1,4 milliard de dollars levés au premier semestre, signe d’un intérêt soutenu des investisseurs pour des acteurs capables de digitaliser et transformer un marché encore largement traditionnel. Comme la fintech avant elle, l’insurtech promet d’ouvrir un secteur longtemps verrouillé à l’innovation, attirant ainsi des capitaux à la recherche de nouvelles opportunités de croissance.

Une transformation digitale enfin lancée

Les consommateurs veulent désormais souscrire, gérer et résilier leurs contrats d’assurance en ligne, en quelques clics. Les insurtechs répondent à cette attente avec des interfaces intuitives, des tarifs transparents, et parfois même une personnalisation en temps réel.

En automatisant les processus, en utilisant l’intelligence artificielle pour l’évaluation des risques ou le traitement des sinistres, ces startups réduisent drastiquement les coûts d’exploitation. Un levier très attractif pour les investisseurs en quête de rentabilité.

Des modèles hybrides et scalables

Les insurtechs n’ont pas toutes le même modèle. Certaines créent leurs propres produits d’assurance en tant que porteurs de risque, d’autres s’associent à des assureurs traditionnels pour distribuer des offres sous marque blanche, ou encore proposent des infrastructures tech en marque grise (B2B).

Ce niveau de flexibilité permet d’adapter le modèle économique à chaque marché local, tout en gardant une ambition d’expansion rapide à l’international. Les investisseurs apprécient ces modèles scalables, capables de croître sans exploser les coûts.

Un alignement avec les nouvelles attentes sociétales

Les jeunes consommateurs veulent des services simples, accessibles, et plus transparents, mais aussi des entreprises qui partagent leurs valeurs. De nombreuses insurtechs proposent des assurances à impact : mobilité douce, assurance santé mentale, couverture pour freelances, micro-assurance pour les populations exclues…

Ces approches rendent l’assurance plus inclusive et plus moderne, ce qui séduit non seulement les clients finaux mais aussi les fonds à impact ou les family offices sensibles aux enjeux sociétaux.

Des exemples de succès qui rassurent le marché

Des startups comme Alan (France), Wefox (Allemagne) ou Zego (Royaume-Uni) ont levé des centaines de millions d’euros ces dernières années. Elles prouvent que le modèle fonctionne, et qu’il est possible de combiner croissance rapide et innovation réglementée.

Ces success stories créent un effet d’entraînement : en voyant d’autres fonds entrer au capital, de nouveaux investisseurs veulent aussi prendre position tôt dans les prochaines pépites du secteur.

Une réglementation de plus en plus ouverte à l’innovation

Les régulateurs européens sont de plus en plus ouverts à l’expérimentation, notamment via des "sandboxes réglementaires" qui permettent aux insurtechs de tester de nouveaux produits en conditions réelles tout en restant encadrées.

Cela réduit le risque juridique pour les investisseurs et accélère la mise sur le marché des nouvelles offres. Un cadre qui rend l’investissement plus sûr et plus prévisible.

Conclusion : une vague structurelle, pas un effet de mode

L’insurtech n’est pas une simple tendance. C’est une réponse stratégique à un besoin profond de transformation dans un secteur clé de l’économie. Elle combine les ingrédients que les investisseurs recherchent : taille de marché, inefficience à corriger, technologies différenciantes, scalabilité, impact social, et exemples concrets de croissance.

Dans les années à venir, les insurtechs les plus solides pourraient bien devenir les nouveaux géants de l’assurance. Et pour les investisseurs, c’est maintenant qu’il faut être à bord.

Les KPIs clés pour mesurer la performance d’un venture studio

Les venture studios gagnent du terrain dans l’écosystème entrepreneurial, en créant des startups de manière itérative et structurée. Contrairement aux fonds d’investissement ou aux incubateurs, leur modèle repose sur la création interne d’entreprises. Un studio n’est pas qu’une machine à startups, c’est aussi un acteur de transformation. Mais comment mesurer leur réussite ? Quels indicateurs permettent d’évaluer leur performance au-delà des simples sorties financières ?

Dans cet article, nous explorons les principaux KPIs (indicateurs clés de performance) qui permettent de suivre et d’analyser l’efficacité d’un venture studio.

Le taux de création de startups est un indicateur fondamental

Un premier KPI essentiel est le nombre de startups créées sur une période donnée (souvent annuelle). Ce chiffre reflète la capacité du studio à générer, valider et transformer des idées en projets réels.

Il ne s’agit pas seulement de quantité. Le ratio entre idées explorées et startups réellement lancées permet de mesurer l'efficacité du processus de validation en amont.

Le taux de survie des startups montre la solidité du modèle

Créer une startup, c’est bien. Mais assurer sa survie dans les 12 à 36 mois, c’est mieux. Le taux de survie mesure le pourcentage de startups du studio toujours actives après une période définie. Il témoigne de la qualité de l’accompagnement, de la pertinence du produit, et de l’adéquation au marché.

Un bon venture studio ne se contente pas de lancer des projets : il les structure pour qu’ils tiennent la route.

La vitesse de mise sur le marché reflète l’agilité du studio

L’un des grands atouts des venture studios est leur capacité à aller vite. Le time-to-market — soit le temps entre l’idéation et le lancement public du produit — est un KPI clé.

Un cycle de développement court indique que le studio sait mobiliser ses ressources (design, produit, développement, juridique) pour accélérer la croissance des projets.

Les levées de fonds externes mesurent l’attractivité des projets

Lorsque les startups issues d’un studio réussissent à lever des fonds externes, cela valide non seulement leur potentiel, mais aussi la crédibilité du studio aux yeux des investisseurs.

Le montant levé, le nombre de tours de financement réussis, et la qualité des investisseurs impliqués sont autant d’indicateurs de la valeur créée par le studio.

Le retour sur investissement global reste un KPI incontournable

Même si les studios ne fonctionnent pas comme des fonds VC classiques, ils doivent générer un retour sur investissement (ROI) à long terme. Cela peut inclure les exits (reventes), les dividendes perçus, ou encore l’augmentation de la valorisation du portefeuille global.

Ce KPI est souvent analysé sur un horizon de 5 à 10 ans, le temps que les startups atteignent leur maturité.

L’efficacité opérationnelle interne fait aussi la différence

Au-delà des performances des startups, la productivité de l’équipe du studio est aussi un KPI à suivre. Combien de projets un chef de produit ou un développeur peut-il gérer par an ? Le coût moyen par startup créée est-il optimisé ? Ces données permettent de piloter le modèle comme une entreprise à part entière.

Le réseau d’experts et de talents est un levier stratégique

Enfin, un KPI souvent sous-estimé concerne le réseau activé par le studio. Cela inclut les fondateurs recrutés, les experts impliqués, les partenariats industriels ou commerciaux. La richesse et la diversité de cet écosystème renforcent l’effet de levier du studio.

Un studio performant attire des talents de qualité, mobilise des mentors engagés et crée des synergies entre les startups.

L’impact sectoriel ou thématique : un KPI à considérer

Certains venture studios choisissent de se spécialiser dans des secteurs clés comme la santé, le climat, ou la tech sociale. Dans ce cas, il peut être pertinent de mesurer leur influence spécifique sur ces écosystèmes, par exemple à travers le nombre de brevets déposés, les partenariats noués avec des grands groupes industriels, ou encore leur contribution à la transition numérique ou écologique. 

Conclusion : mesurer, c’est piloter

La performance d’un venture studio ne se mesure pas uniquement à travers les succès visibles. Derrière chaque startup lancée, il y a des processus, des paris, des ajustements. En suivant des KPIs adaptés, à la fois quantitatifs et qualitatifs — les studios peuvent affiner leur stratégie, prouver leur impact, et construire un modèle durable.

Dans un écosystème en constante évolution, les venture studios qui savent se mesurer sont ceux qui savent durer.

Major Insurtech Trends: AI, Personalization, Automation

The global insurance sector is undergoing a seismic shift. As customer expectations evolve and digital technologies mature, insurtech companies are leading the charge in transforming how insurance is designed, delivered, and experienced.

At the heart of this revolution are three powerful forces: Artificial Intelligence (AI), hyper-personalization, and automation. These trends are not just buzzwords, they are redefining the insurance landscape in 2025 and beyond.

AI takes over risk assessment and claims processing

Artificial intelligence is becoming a core enabler for smarter, faster, and more scalable insurance operations. Insurtechs are using AI to:

• Analyze real-time customer data to generate more accurate risk profiles

• Detect fraudulent claims through pattern recognition and anomaly detection

• Automate underwriting with machine learning models trained on massive datasets

• Power chatbots that handle routine claims and customer service with minimal human intervention

By 2025, AI will no longer be a “nice-to-have”, it will be a competitive necessity for both startups and incumbents.

Hyper-personalization is the new standard

The age of one-size-fits-all insurance products is over. Today’s consumers expect coverage tailored to their lifestyle, behavior, and needs - and insurtechs are delivering.

Using data from connected devices, social platforms, wearables, and spending habits, insurtech platforms can:

• Offer usage-based insurance (e.g., pay-as-you-drive car insurance)

• Tailor recommendations in real time, such as micro-policies for short-term travel or freelance work

• Adapt coverage dynamically as a customer’s circumstances evolve

This level of personalization leads to higher customer retention, lower churn, and better alignment between risk and premium.

Automation streamlines the entire insurance lifecycle

Insurtechs are pushing automation across the board, from customer onboarding to claims disbursement. Key developments include:

• Instant quotes generated by digital platforms using AI-powered rules engines

• Self-service portals where users can buy, manage, and renew policies online

• Automated claims payouts, sometimes settled within minutes using smart contracts or pre-validated data

Automation reduces operational costs, eliminates friction, and frees up human agents to focus on high-value interactions.

Embedded insurance gains ground

Closely tied to automation is the rise of embedded insurance; coverage seamlessly offered at the point of need, integrated into platforms like e-commerce checkouts, car rental apps, or fintech services.

This trend is set to reshape distribution models, enabling insurtechs to reach customers who may never have actively sought out a policy.

Data-driven innovation fuels inclusive growth

With AI and automation unlocking new types of data, insurtechs can serve previously “uninsurable” populations, especially in emerging markets. Behavioral data and alternative credit scoring models are helping design inclusive insurance products for gig workers, rural communities, or informal sectors.

This shift represents not only a business opportunity but also a social innovation frontier.

Conclusion: Insurtech is redefining the rules of the game

As we move further into 2025, the most successful insurtechs will be those that blend AI intelligence, customer-centric personalization, and end-to-end automation into a seamless experience.

Traditional insurers that fail to adapt will struggle to stay relevant, while agile, tech-savvy players will set the standard for what modern insurance looks like: proactive, digital-first, and deeply human in impact.

Predictive Insurance Through AI: Myth or Reality?

Methodology: Exploring AI’s Role in Insurance Forecasting

This article draws on industry reports, case studies, and current use cases from insurers applying artificial intelligence to predictive modeling. It examines how AI is reshaping underwriting, claims management, and customer engagement and where the promise may be ahead of the current reality.

In Brief: Where We Stand Today

• AI is already delivering predictive insights in claims detection, risk scoring, and fraud prevention.

• Adoption remains uneven, with most impact in large carriers and insurtech startups.

• Challenges include data privacy concerns, regulatory hurdles, and model transparency.

• The future of predictive insurance lies in combining AI with human judgment and ethical frameworks.

How AI Is Changing Insurance Predictions

The idea of predictive insurance is no longer science fiction. With vast amounts of customer data, real-time IoT inputs (such as from vehicles or smart homes), and advanced machine learning models, insurers can now:

• Identify high-risk customers or properties proactively

• Anticipate claim likelihood based on behavioral and environmental factors

• Tailor pricing more accurately for individual policyholders

• Detect fraud before payouts are made

AI models can process data at a scale and speed that human teams simply can’t match, making predictive insurance a growing reality in modern underwriting.

The Challenges That Make It Feel Like a Myth

Despite these advancements, predictive insurance powered by AI isn’t universal yet. Key challenges include:

Data Quality and Access

Insurers need clean, consistent, and ethically sourced data. Many legacy systems were not built for this level of data integration, slowing adoption.

Regulatory Landscape

Predictive pricing and claims forecasting raise complex compliance questions. Regulators demand transparency on how models make decisions, particularly in sensitive areas like health or auto insurance.

Trust and Transparency

Consumers and sometimes underwriters want to understand why a price or decision was made. AI models can feel like a “black box,” making it harder to build trust without proper explainability measures.

Where AI Predictive Models Are Already Delivering

Despite these challenges, AI-driven prediction is already reshaping certain insurance segments: 

• Auto insurance: Predictive telematics models score driver safety in real time, impacting pricing.

• Property insurance: Climate and weather models anticipate loss patterns to adjust coverage proactively.

• Health insurance: Behavioral data informs wellness incentives and early intervention programs.

• Fraud detection: AI flags anomalies faster than traditional methods, cutting loss ratios.

These are no longer pilot projects; they're live tools helping insurers reduce costs, improve customer experience, and drive smarter decisions.

Final Thought: Myth or Reality? A Bit of Both For Now

Predictive insurance through AI is very real but it’s not evenly applied across the industry. For many carriers, true AI-driven prediction is still aspirational, hampered by legacy infrastructure, governance complexity, and talent gaps.

However, where AI is deployed well, it’s transforming how risk is assessed, priced, and managed. The future will belong to insurers who combine AI’s predictive power with human insight, transparency, and a focus on ethical impact.

Comment l’IA personnalise l’expérience bancaire ?

Les attentes des clients envers leur banque ont profondément changé. Ils recherchent aujourd’hui simplicité, rapidité et services sur mesure. L’intelligence artificielle permet désormais aux banques d’offrir une expérience client personnalisée, comparable à celle des géants du numérique.

Mais comment cette transformation se concrétise-t-elle ? Voici un tour d’horizon de l’impact de l’IA sur l’expérience bancaire.

Des conseils financiers adaptés à chaque profil

L’IA peut analyser en temps réel les habitudes de dépenses, les revenus et les comportements financiers pour proposer des recommandations personnalisées : conseils d’épargne, alertes sur les dépenses, suggestions de budget, ou encore anticipation des découverts.

La banque devient ainsi un véritable assistant personnel, disponible à toute heure pour aider les clients à mieux gérer leur argent.

Une segmentation plus fine et plus pertinente

Grâce à l’IA, les banques dépassent les segmentations traditionnelles (âge, revenu, statut) et s’appuient sur des données comportementales. Elles peuvent ainsi proposer des offres adaptées au style de vie de chaque utilisateur, qu’il s’agisse de produits de crédit, d’assurance ou d’investissement.

Cette personnalisation améliore la pertinence des services et renforce la fidélité des clients.

Un service client plus fluide avec des assistants virtuels

Les chatbots intelligents permettent aux clients de poser des questions, consulter leurs comptes ou effectuer des opérations simples, sans passer par un conseiller. Ces assistants virtuels évoluent avec l’usage, comprennent les préférences des utilisateurs, et savent transférer la demande à un humain si nécessaire.

Le résultat : un service plus rapide et moins contraignant.

Une anticipation proactive des besoins

L’intelligence artificielle peut détecter de nouvelles habitudes (comme un changement de statut professionnel) et proposer des solutions financières adaptées : compte professionnel, assurance dédiée, options d’épargne ou d’investissement.

Cette capacité à anticiper renforce la position de la banque comme partenaire de confiance, au-delà de son rôle traditionnel.

Une sécurité renforcée, personnalisée pour chaque client

L’IA apprend à connaître les comportements habituels des utilisateurs et peut détecter immédiatement une activité suspecte. Ce niveau de vigilance personnalisé réduit les risques de fraude tout en évitant les alertes inutiles.

Les clients bénéficient ainsi d’une sécurité renforcée, sans perte de fluidité dans leur expérience.

Vers une relation bancaire plus empathique

Certaines banques testent des technologies d’analyse d’émotions dans les interactions client, pour adapter leur ton et mieux répondre aux situations sensibles. Même si ces approches sont encore en développement, elles ouvrent la voie à une relation plus humaine, même à distance.

Conclusion

L’intelligence artificielle transforme en profondeur la manière dont les banques interagissent avec leurs clients. Elle rend les services plus personnalisés, plus efficaces et plus sûrs.

Pour les établissements bancaires, cette transformation est une opportunité stratégique. Pour les clients, c’est la promesse d’une expérience plus fluide, plus utile, et centrée sur leurs besoins réels. 

Les tendances Insurtech à suivre en 2025

Le secteur de l’assurance vit une transformation profonde portée par la technologie. En 2025, les insurtechs ne se contenteront plus de numériser les processus existants : elles réinventeront l’ensemble de la chaîne de valeur, de la souscription à la gestion des sinistres.

Voici les 6 grandes tendances à surveiller pour comprendre où va l’innovation dans l’assurance.

1. L’intelligence artificielle devient le moteur principal de l’automatisation

L’IA est désormais au cœur des modèles insurtech. En 2025, elle sera utilisée à toutes les étapes : évaluation des risques, détection de fraude, gestion des sinistres, tarification dynamique.

Par exemple, AXA France a développé, avec Microsoft, une plateforme interne baptisée AXA Secure GPT. Basée sur l’IA générative, elle permet d’ajuster les offres aux antécédents médicaux ou au mode de vie : services de prévention personnalisés ou offres santé ciblées.

De leur côté, des startups comme Shift Technology utilisent l’IA pour détecter des fraudes en analysant des millions de transactions.

Les assistants conversationnels intelligents réduisent aussi les délais de traitement, offrent un support 24h/24, et améliorent l’expérience client de bout en bout.

2. L’assurance embarquée s’impose comme nouveau standard

L’assurance ne se vend plus, elle s’intègre. En 2025, le modèle de l’assurance embarquée ("embedded insurance") devient la norme, proposée automatiquement au bon moment — lors de l’achat d’un téléphone, d’un voyage ou d’un service.

Exemples notables :

• AppleCare propose une couverture dès l’achat d’un appareil Apple.

• Booking.com intègre des options d’assurance voyage au moment du paiement.

• Stripe propose aux commerçants d’offrir une assurance à leurs clients via son API.

Cette intégration contextuelle permet d’atteindre des clients qui n’auraient pas souscrit à une assurance classique.

3. Des modèles d’abonnement plus flexibles pour répondre aux nouveaux usages

Avec l’évolution des modes de vie (freelance, mobilité, économie à la demande), les clients attendent plus de flexibilité. En 2025, les insurtechs proposent des formules à la carte ou par abonnement, facilement activables ou désactivables via une app.

La startup française Luko permet par exemple de suspendre son assurance habitation quand on est en déplacement prolongé.

Ces offres s’inspirent des standards de consommation modernes (Netflix, Spotify), et séduisent particulièrement les générations Z et milléniales.

4. Une assurance plus inclusive, portée par la donnée alternative

Les données alternatives issues des objets connectés, réseaux sociaux ou plateformes de mobilité ouvrent de nouvelles perspectives.

La startup Pula, active en Afrique, utilise les données météo et agricoles satellitaires pour assurer les petits agriculteurs, jusque-là exclus des produits classiques.

Autre exemple : Zego, au Royaume-Uni, propose des assurances flexibles pour les livreurs ou chauffeurs VTC, en s’appuyant sur des données d’usage en temps réel (heures de conduite, distance parcourue).

Ces modèles permettent une inclusion assurantielle plus large, notamment dans les économies émergentes.

5. Un écosystème de partenariats plus stratégique

Les insurtechs ne visent plus à remplacer les assureurs traditionnels, mais à collaborer avec eux. En 2025, les partenariats stratégiques deviennent un levier clé : startups agiles + acteurs établis + géants technologiques.

Par exemple :

• Swiss Re collabore avec des insurtechs pour co-développer des produits.

• Generali noue des alliances avec des acteurs de la healthtech pour enrichir ses offres santé.

• Des acteurs cloud comme AWS ou Azure fournissent l’infrastructure sécurisée des nouvelles plateformes insurtech.

Ces synergies favorisent l’innovation tout en garantissant la solidité réglementaire et financière.

6. La blockchain gagne du terrain dans la gestion des sinistres

En matière de transparence et d’automatisation, la blockchain apporte des solutions puissantes.

Des startups comme Etherisc ou Chainlink expérimentent les smart contracts pour des assurances paramétriques : retard de vol, aléa météo, hospitalisation… L’indemnisation est automatique dès qu’un événement validé est détecté.

Bien que cette technologie reste marginale, elle se développe notamment dans les micro-assurances et les marchés émergents, où la rapidité et la confiance sont essentielles.

Conclusion : une assurance plus intégrée, intelligente et centrée sur l’utilisateur

En 2025, les insurtechs redéfinissent les règles du jeu. IA, personnalisation, intégration fluide, inclusion… l’assurance devient proactive, flexible et contextuelle.

Les compagnies traditionnelles devront s’adapter à ces standards ou risquer de perdre en compétitivité. Car plus que la technologie elle-même, c’est l’expérience utilisateur qui devient le nouvel avantage concurrentiel.

AI in WealthTech: Where the Next Wave of Innovation Lies

Artificial intelligence is not just a feature in WealthTech—it’s the foundation of the next generation of solutions. 

Our methodology involved gathering numerous venture maps from around the world to identify recurring categories and sources of innovation in AI. From this extensive research, we developed the Mandalore AI in WealthTech Venture Map 2025, which captures the current state of the art in AI technology and innovation. Using these insights, we analyzed how innovation is driven across different sectors and crafted this article to highlight the key trends and opportunities shaping the future of AI.

AI enables dynamic portfolio optimization

AI is redefining portfolio construction through hyper-personalization and continuous optimization. Algorithms can ingest investor goals, risk tolerance, and real-time market data to dynamically rebalance portfolios. This enables scalable, advisor-like services delivered automatically, with less human intervention and greater adaptability.

While unlocking private markets through automated sourcing and valuation

Access to private assets is being democratized and de-risked through AI-powered deal sourcing, valuation modeling, and scenario simulation. Machine learning models uncover hidden opportunities and automate diligence processes, creating a competitive edge in an opaque and fragmented landscape.

And turning financial planning into adaptive guidance

AI transforms static financial plans into living, breathing systems that adjust to life changes in real time. By integrating behavioral data and predictive analytics, platforms can guide users proactively—recommending decisions, anticipating shortfalls, and making planning feel less like a spreadsheet and more like a conversation.

As well as modernizing compliance with intelligent monitoring

Legacy compliance processes are being replaced by intelligent monitoring systems that learn from data and flag risks before they materialize. AI enhances transparency and reduces manual workloads, making it possible for firms to scale governance and stay ahead of evolving regulations with minimal friction.

While also enhancing market insight through unstructured data analysis

AI mines unstructured data—from news to social feeds—to generate real-time insights and sentiment indicators. This empowers investors to make faster, more informed decisions and unlocks new alpha from sources that traditional models overlook.

And finally personalizing client experience with predictive interfaces

AI personalizes the advisor-client relationship at scale. From conversational interfaces to predictive nudges, AI enables firms to deliver tailored advice, anticipate needs, and build trust—making digital wealth platforms feel human, even when no one is on the other end.