Venture Building

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.

The Most VC-Funded Sectors in Europe

The Most VC-Funded Sectors in Europe

Europe’s startup ecosystem has grown rapidly over the past decade, attracting billions in venture capital (VC) from both local and global investors. While overall funding levels fluctuate with macroeconomic conditions, certain sectors consistently draw strong VC attention. From climate tech and deep tech to fintech, health innovations, and enterprise software, the continent’s innovation landscape is increasingly diverse and resilient.

Climate Tech Leads the Pack

Climate tech and energy transition startups are now Europe’s single largest VC-funded sector, accounting for approximately 27–30% of total venture capital investment in 2023 (Dealroom/Sifted). This surge reflects the EU’s ambitious carbon neutrality targets, supportive policy frameworks, and the growing appetite among investors for climate-positive solutions.

Startups tackling renewable energy, sustainable mobility, carbon capture, and circular economy solutions are driving the trend. Countries like the Netherlands, Germany, and the Nordics are at the forefront, combining strong cleantech ecosystems with dedicated climate funds.

AI & Deep Tech Keep Rising

AI and deep tech (which includes frontier technologies like advanced hardware, quantum computing, and automation) accounted for about 17% of Europe’s VC funding in 2023. The rise of generative AI and automation tools is accelerating investor interest, with large rounds for companies like Mistral AI, DeepL, and Aleph Alpha showing the strength of the ecosystem.

Key hubs for AI and deep tech include Berlin, Paris, and London, all benefiting from talent density and supportive research institutions.

Fintech Remains a Pillar

Fintech remains a major draw, attracting roughly 15–19% of total VC investment, down slightly from its peak but still firmly in the top three sectors. From digital banks to blockchain platforms and payments solutions, European fintech leaders like Revolut (UK), N26 (Germany), and Lydia (France) continue to scale, supported by consumers’ shift away from traditional banking.

London remains Europe’s fintech capital, thanks to its mature regulatory environment and deep investor pools.

Healthtech & Enterprise Software Stay Solid

While harder to split precisely, healthtech and enterprise software together continue to be pillars of European VC activity. Over the last 20 years, they have consistently accounted for a combined ~40% of total VC funding (Dealroom). Healthtech startups in telemedicine, AI diagnostics, and mental health are still seeing healthy long-term growth, while B2B SaaS and cloud solutions remain attractive bets for their scalability and recurring revenues.

Companies like Doctolib (France), Kry (Sweden), and Celonis (Germany) show how Europe’s healthtech and enterprise software scenes remain globally competitive.

Emerging Sectors to Watch

Beyond these leading sectors, several emerging areas are gaining momentum:

  • AgriTech: With food security and regenerative farming in focus, AgriTech is steadily attracting more funding.

  • Cybersecurity: Increasing digital threats are driving larger rounds for European security startups.

  • Edtech: While post-pandemic growth slowed, niches like corporate training and AI-driven learning are evolving.

  • Space Tech: Once US-dominated, Europe’s space tech sector is quietly expanding, supported by national programs and private capital.

How Does Europe Compare Globally?

According to Dealroom’s 2023 and early 2024 data, Europe’s top-funded sectors now mirror global trends in the US and East Asia. In the US, the top sectors by VC investment are:

  1. Health & Biotech

  2. Enterprise Software / AI

  3. Fintech

East Asia follows a similar pattern, with deep tech, fintech, and industrial tech attracting the biggest rounds. Notably, Europe’s climate tech stands out: its share of total VC funding is higher than in North America or Asia, thanks to EU policy incentives and investor demand for sustainable growth.

Final Thoughts

The European VC landscape is dynamic, but certain sectors continue to stand out for their scale, impact, and resilience. Climate tech, deep tech, fintech, healthtech, and enterprise software together account for the lion’s share of VC investment, while emerging verticals like AgriTech and space tech hint at the next wave of innovation.

For founders, understanding which sectors attract capital and why can shape how you position your startup. For investors, the current trends reflect where both opportunity and responsibility intersect in the next era of European innovation.

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.

How is AI reshaping InsurTech ?

AI unlocks unprecedented underwriting value through non-traditional data processing, while simultaneously enabling substantial margin improvements via automated claims handling and fraud detection. Furthermore, behavioral prediction engines dramatically reduce acquisition costs, just as sector-specific applications improve loss ratios and create new premium pools. Finally, dynamic pricing optimization delivers defensible advantages through improved ratios and conversion rates.

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 InsurTech 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 unlocks unprecedented underwriting value through non-traditional data processing

The most promising AI investments in underwriting target the opportunity in reducing mispriced risk. Algorithms now process thousands of non-traditional variables that traditional actuarial models miss completely. The emerging gold rush is in proprietary data acquisition strategies that feed these models with unique signals beyond standard industry datasets. We're particularly bullish on computer vision applications that can extract property characteristics remotely, eliminating the need for costly physical inspections while dramatically improving accuracy of risk assessment.

While enabling margin improvements via automated claims handling and fraud detection

Claims processing represents perhaps the largest near-term ROI opportunity in insurtech, with potential margin improvements through AI automation. The value creation formula is straightforward: each percentage point of fraud detection improvement could translate to annual savings industry-wide. We see immediate traction for solutions combining computer vision for damage assessment with natural language processing for claims documentation analysis. The most investable opportunities are emerging at the intersection of these technologies, where end-to-end claims automation platforms can deliver increasing processing rates.

Behavioral prediction engines dramatically reduce acquisition costs

With customer acquisition costs in insurance being high, AI-powered distribution efficiency represents a massive opportunity. The most compelling investment cases are platforms that leverage behavioral prediction engines to identify high-conversion prospects before competitors. The next frontier will be conversational AI that can handle complex insurance consultations with human-like understanding of coverage nuances, effectively democratizing expert-level insurance guidance.

Just as sector-specific applications improve loss ratios and create new premium pools

Sector-specific AI applications are producing the fastest path to market leadership. In auto insurance, companies deploying telematics with behavioral analysis algorithms are decreasing loss ratios below industry averages. Life insurers leveraging continuous underwriting models through wearable data are expanding their addressable market by making coverage accessible to previously uninsurable populations. The cyber insurance sector presents the most asymmetric return profile, where AI that can quantify previously unmodeled risks creates entirely new premium pools..

Finally, dynamic pricing optimization delivers defensible advantages

AI-driven pricing represents the most defensible competitive advantage in insurance. The investment opportunity lies in platforms that balance pricing optimization with regulatory compliance through explainable AI. Dynamic pricing engines that can continuously adjust to market conditions without human intervention are a big opportunity. The next wave of innovation will come from causal inference algorithms that simulate customer responses to price changes, allowing insurers to optimize elasticity at the individual level.

The Future of AI: Key Technologies and Breakthrough Opportunities Transforming Industries

This article explores the major AI technology categories reshaping industries today. From foundational language models to generative content creation, computer vision, robotics, and cybersecurity, it highlights the core innovations driving new use cases and efficiencies. It also emphasizes the growing importance of ethical AI governance to ensure responsible adoption across sectors.

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 Techno 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.

Foundation models and LLMs are transforming language understanding

Foundation models and large language models (LLMs) are revolutionizing machine understanding and generation of natural language. These models serve as the backbone of modern AI, capable of performing a wide range of tasks with minimal supervision. Innovation is happening at multiple levels: from developing new, more efficient architectures, to fine-tuning models for domain-specific applications. Open-source ecosystems and infrastructure tools are expanding access, while autonomous agents and AI copilots are beginning to act independently across productivity tools and enterprise workflows.

Meanwhile, generative AI powers content creation

Generative AI enables machines to create original content across text, images, video, code, audio, and even 3D models. In creative industries, this means automated content production, real-time media editing, and synthetic design. For developers, new AI coding assistants accelerate software development and testing. Audio and music generation platforms provide personalized media experiences, while generative 3D tools transform asset creation in gaming, digital twins, and immersive environments.

At the same time, computer vision interprets visual data

Computer vision allows machines to interpret and act on visual information, unlocking a broad range of applications. In industrial contexts, AI can detect manufacturing defects, monitor quality, and optimize production lines. In healthcare, it assists in analyzing medical imaging to support diagnostics. Vision-based surveillance systems are transforming security operations, while autonomous driving relies on real-time image processing to navigate dynamic environments. Facial recognition and biometrics further extend vision’s reach into authentication and identity verification.

While NLP drives language recognition

NLP technologies extract meaning from unstructured language data. Machine translation tools bridge language barriers across global organizations. Text summarization and information extraction streamline document processing, legal analysis, and research. Augmented search capabilities combine retrieval and generation to provide accurate, context-aware responses in enterprise knowledge systems. In voice, real-time transcription and synthetic voice cloning enable more natural and scalable human-machine interaction.

Additionally, robotics and automation enhance efficiency

AI-driven robotics is reshaping physical work across sectors. Humanoid and task-specific robots are being deployed in manufacturing, retail, and service industries. Warehouses are increasingly automated through intelligent systems that move, sort, and package goods with minimal human input. Edge computing enables real-time decision-making in low-latency environments like vehicles or sensors. Smart city infrastructure leverages AI to manage traffic flow, safety, and urban logistics.

Also, AI in science speeds up drug discovery and materials innovation.

AI is fast becoming a core tool in scientific discovery. In life sciences, it accelerates drug discovery by modeling molecule interactions and predicting treatment outcomes. In material science and chemistry, AI models generate new compounds with specific properties, drastically reducing the time required for R&D. These technologies not only enhance research productivity but also open new possibilities across medicine, energy, and sustainability.

Meanwhile, AI for cybersecurity improves threat detection and protection

Cybersecurity is evolving with AI on both sides of the threat landscape. Security operations are becoming more autonomous, with AI systems detecting and responding to incidents in real time. Deepfake detection and malicious content identification help combat new forms of digital fraud. AI-specific guardrails are emerging to monitor prompt injection, data leakage, and model misuse—ensuring safer deployment of large-scale AI systems.

Still promoting AI Ethics & Governance

As AI becomes more powerful and pervasive, governance frameworks are essential to ensure transparency, fairness, and accountability. Tools that audit model behavior, track data provenance, and enforce compliance standards are being embedded across industries. AI monitoring systems detect drift, bias, and anomalies, while governance platforms help organizations align model development with ethical principles and regulatory requirements.

Corporate Venture Building : un levier stratégique pour les conseils d’administration

À l’ère du digital, la survie des grandes entreprises dépend de leur capacité à innover rapidement. Alors que l'espérance de vie moyenne d'une entreprise est passée de 90 ans en 1935 à un peu plus de 10 ans aujourd’hui, les conseils d’administration doivent désormais jouer un rôle actif dans la transformation de leurs organisations.

Le Corporate Venture Building : une réponse stratégique

Le Corporate Venture Building (CVB) s’impose comme un levier stratégique puissant pour créer de nouvelles sources de revenus tout en renforçant la résilience de l’entreprise. Ce modèle hybride permet de :

  • Tirer parti des actifs internes (clients, données, expertise sectorielle…)

  • Reproduire l’agilité des start-ups

  • Réduire les risques tout en accélérant l’innovation

Selon les experts, les entreprises qui adoptent ce modèle peuvent multiplier par 14 leurs chances de bâtir un business à forte croissance par rapport aux start-ups classiques.

🎯 4 leviers clés pour réussir un programme de Corporate Venture Building

Fixer des objectifs clairs et ambitieux

Définir une vision long terme, des axes de développement prioritaires, et des indicateurs de performance (OKR) est essentiel. Le conseil d’administration doit aussi statuer tôt sur la stratégie : spin-in (intégration au cœur de l’entreprise) ou spin-out (filiale autonome).

Adopter une logique de portefeuille et de financement progressif

Plutôt que de miser sur un seul projet, les entreprises les plus performantes adoptent une approche portefeuille, avec des décisions d’investissement basées sur des étapes clés (stage-gates). Cela permet d'optimiser le capital investi tout en réduisant les risques.

Mettre en place une gouvernance agile

L’un des freins majeurs à l’innovation est la lenteur des processus décisionnels. Pour réussir, il faut donner aux équipes une réelle autonomie, instaurer un cadre clair, et s’inspirer des meilleures pratiques des fonds de capital-risque.

Attirer et fidéliser les meilleurs talents entrepreneuriaux

Le succès d’un corporate venture repose sur ses fondateurs. Il faut savoir attirer des profils entrepreneurs/intrapreneurs et mettre en place des systèmes d’incentives inspirés des start-ups (participations, phantom shares, autonomie stratégique…).

📌 Leçons du terrain : le cas Axiata Digital

Le groupe télécom Axiata a lancé son programme de CVB en 2014. Résultat : des filiales comme Boost (wallet), ADA (data & marketing) ou Aspirasi (micro-financement) ont levé plus de 100 millions de dollars et généré des relais de croissance majeurs.

Leur recette du succès ?
👉 Une gouvernance claire, un capital dédié, des équipes autonomes, et une approche rigoureuse du portefeuille.

✅Pourquoi les conseils d’administration doivent s’impliquer dès aujourd’hui

Dans un monde où l’innovation est une question de survie, les conseils d’administration doivent :

  • Challenger la vision long terme

  • Soutenir l’investissement dans des projets disruptifs

  • Créer un environnement favorable à l’expérimentation et à la prise de risque contrôlée

Le Corporate Venture Building est bien plus qu’un buzzword. C’est une stratégie d’innovation structurée, mesurable et scalable, capable de transformer en profondeur les modèles économiques.

February 2025 : Venture Studios: Driving Innovation and Facing Strategic Challenges

As the venture studio model continues to gain traction worldwide, new initiatives are emerging across industries, focusing on innovation in energy storage, healthtech, and pet care, while some face financial and strategic challenges. This article explores the latest developments shaping the venture studio ecosystem.

GenLab Launches Silicon Valley Venture Studio for Energy Storage Innovation

On February 11, 2025, GenLab Venture Studios announced the launch of a new venture studio in Silicon Valley aimed at driving innovation in energy storage and AI infrastructure. With artificial intelligence increasingly demanding energy-intensive processing, this initiative seeks to alleviate pressure on national power grids by developing next-generation storage solutions.

The studio, led by CTO Sarah Novotny, will focus on creating advanced grid resilience technologies that ensure energy efficiency and sustainability. Leveraging cutting-edge agentic AI, GenLab aims to enhance energy storage capabilities for data centers and industrial applications, positioning itself as a key player in the clean energy transition.

Company Ventures Unveils Terrarium Venture Studio to Support Healthtech Startups

On February 18, 2025, Company Ventures, in collaboration with innovation consultancy Cactus and Wellstar Health System, launched Terrarium, a new venture studio focused on incubating startups in the health technology sector.

Terrarium plans to support up to ten startups over the next three years, with an emphasis on market validation through research-driven development. The first startup emerging from this initiative, Rota Health, is dedicated to solving healthcare data interoperability issues by leveraging artificial intelligence to streamline medical data integration.

By providing mentorship, funding, and strategic partnerships, Terrarium aims to bridge gaps in healthcare innovation and accelerate the adoption of transformative digital health solutions.

Leap Venture Studio Announces Ninth Cohort for Pet Care Startups

Leap Venture Studio & Academy, a leading accelerator program for pet care startups, has announced its ninth cohort, providing six innovative companies with funding, mentorship, and business development support.

The program, running from February to May 2025, will conclude with a Demo Day in London. Participating startups, including BistroCat, Buddy Bites, Happy Howl, James & Ella, Oh Norman!, and Otis, are pioneering new approaches in pet wellness, nutrition, and AI-driven pet care solutions.

With increasing consumer demand for premium pet products and services, Leap Venture Studio continues to foster high-growth companies that redefine the pet industry.

Avandra Raises $17.75 Million to Advance Real-World Medical Data Utilization

Avandra, a federated network specializing in medical imaging and clinical data, has successfully secured $17.75 million in funding to expand its data-sharing platform. The round, co-led by Aegis Ventures and SpringRock Ventures, will enable Avandra to enhance its data infrastructure and form new partnerships with leading healthcare providers.

The company’s mission is to improve real-world data accessibility for medical researchers and biopharmaceutical companies, accelerating drug development and personalized medicine. By leveraging AI and machine learning, Avandra aims to bridge the gap between raw medical data and actionable insights, ultimately improving patient outcomes.

54 Collective to Shut Down African Venture Studio Operations

Despite the growing global momentum of venture studios, not all initiatives thrive. 54 Collective, formerly known as Founders Factory Africa, has announced the closure of its venture studio operations on the continent, citing strategic shifts and funding challenges.

The decision comes as the organization’s partnership with the Mastercard Foundation is set to end in April 2025. This shift marks a significant change in the African startup ecosystem, raising concerns about the sustainability of venture-backed innovation models in emerging markets.

As Africa continues to develop its entrepreneurial landscape, the closure of 54 Collective highlights the ongoing funding constraints that many venture studios face, emphasizing the need for sustainable financing models to support long-term startup growth.

NEC X Partners with Carbide Ventures to Accelerate Early-Stage Startups

Silicon Valley-based NEC X has announced a strategic partnership with Carbide Ventures to boost early-stage startups. This collaboration aims to provide emerging companies with crucial resources, industry expertise, and mentorship to help transform promising ideas into scalable businesses.

By leveraging NEC X’s technical expertise and Carbide Ventures’ experience in startup acceleration, the partnership seeks to drive innovation across multiple sectors, including AI, robotics, and deep tech. This initiative underscores the growing role of venture studios in bridging the gap between cutting-edge research and commercial success.

Exploring the Link Between Venture Building and VC-as-a-Service

In the ever-evolving startup ecosystem, two models have emerged as key players in fostering innovation and entrepreneurship: venture building and VC-as-a-Service (Venture Capital-as-a-Service). While their approaches differ significantly, they are interconnected in ways that create synergies and drive value for startups, investors, and corporations alike. This article explores the definitions, differences, and the link between these two models.

What is Venture Building?

Venture building refers to the process of systematically creating startups from scratch within a structured environment, often led by venture studios or startup studios. These studios act as co-founders, providing resources, expertise, and funding to build and launch startups.

Key characteristics of venture building include:

  • Idea Generation: Studios identify market gaps and develop startup ideas.

  • Operational Involvement: They take an active role in building the team, developing products, and managing operations.

  • Shared Resources: Startups benefit from shared infrastructure, such as legal, marketing, and technical support.

  • Equity Ownership: Studios typically hold equity in the startups they create.

Venture building minimizes the risk of failure by providing startups with a strong foundation and access to expertise, making it an attractive model for entrepreneurs and investors alike.

What is VC-as-a-Service?

VC-as-a-Service is a model where a venture capital firm offers its expertise and services to manage investments on behalf of external entities, such as corporations, family offices, and institutional investors. Instead of raising a traditional VC fund, these firms act as strategic partners, deploying capital into startups that align with the client’s goals.

Key characteristics of VC-as-a-Service include:

  • Customized Investment Strategies: Investments are tailored to the client’s objectives, whether financial returns, strategic innovation, or market access.

  • Outsourced Expertise: Clients leverage the VC firm’s network, deal flow, and knowledge without building an internal team.

  • Focus on Innovation: Corporations often use VC-as-a-Service to invest in disruptive startups that align with their long-term vision.

This model is particularly appealing to organizations looking to innovate through external investments while mitigating the risks and complexities of direct startup engagement.

How Venture Building and VC-as-a-Service are Linked

Though venture building and VC-as-a-Service serve different purposes, they intersect in several ways, creating opportunities for collaboration and mutual benefit:

1. Complementary Roles in the Startup Ecosystem

  • Venture builders focus on creating startups from the ground up, often in the pre-seed or seed stage.

  • VC-as-a-Service providers focus on funding and scaling startups, often at later stages.

This complementary relationship allows venture studios to collaborate with VC-as-a-Service firms to secure funding for their portfolio startups, while VC-as-a-Service firms gain access to high-quality, de-risked investment opportunities.

2. Partnerships for Strategic Investment

Venture studios often partner with VC-as-a-Service providers to attract external capital for their startups. For instance:

  • A corporation using a VC-as-a-Service model might invest in startups created by a venture studio as part of its innovation strategy.

  • Venture studios benefit from these partnerships by securing funding and strategic support for their startups.

3. Integrated Models

Some organizations combine both models under one roof. For example:

  • A venture studio may offer VC-as-a-Service to external partners, allowing them to co-invest in the startups the studio creates.

  • This hybrid approach aligns the interests of venture builders and investors, creating a streamlined pipeline from startup creation to scaling.

4. Focus on Innovation and Risk Mitigation

Both models aim to foster innovation while reducing risks:

  • Venture building reduces the risk of startup failure by providing operational support and expertise.

  • VC-as-a-Service diversifies investment risks by spreading capital across multiple startups.

Together, they create a robust ecosystem where startups are not only built but also funded and scaled efficiently.

Key Differences Between Venture Building and VC-as-a-Service :

Conclusion

Venture building and VC-as-a-Service are two distinct yet interconnected models that play vital roles in the startup ecosystem. Venture studios focus on the creation of startups, while VC-as-a-Service enables the funding and scaling of these ventures. Together, they form a powerful combination that drives innovation, reduces risks, and creates value for all stakeholders involved.

As the startup ecosystem continues to evolve, the collaboration between venture builders and VC-as-a-Service providers is likely to grow, creating new opportunities for entrepreneurs, investors, and corporations to thrive.