Scouting for Growth

The App Era Is Over: Wallet-Native Insurance & the Agentic Frontier — Marc Lampe × Ernesto Suarez In this episode of Scouting for Growth, Sabine VanderLinden sits down with Ernesto Suarez and Marc Lampe to explore why the future of insurance is moving beyond apps and into wallet-native, AI-ready experiences. The conversation begins with a powerful reminder of why customer experience matters: a traveler stranded abroad, unable to prove they had insurance in an emergency. From there, the discussion unpacks the hidden friction embedded across the insurance journey — especially in claims, servicing, and customer engagement. Ernesto shares how Gigasure was designed as a digital-native travel MGA focused on mobile-first engagement, instant gratification, and removing the traditional “handoffs” that frustrate policyholders. Marc explains how Wallet Studio, developed by Miss Moneypenny Technologies after nearly a decade of experimentation, enables insurers to create dynamic wallet-based insurance experiences that sit directly alongside boarding passes, payments, and loyalty cards. Together, they reveal how the partnership rapidly launched over 50,000 digital wallet cards in just a few months, achieving remarkable customer engagement and demonstrating that insurance can become proactive, contextual, and genuinely useful. The episode also dives into parametric claims, embedded insurance, MGA innovation, AI-enabled customer journeys, and why ecosystem collaboration — not disruption alone — is shaping the next era of InsurTech.   KEY TAKEAWAYS What struck me most in this conversation is how both Ernesto and Marc are solving an issue the industry has talked about for years but rarely fixed: making insurance truly accessible and useful at the exact moment customers need it most. We often talk about “customer experience” in insurance, yet too many journeys still rely on PDFs buried in inboxes, disconnected claims processes, and handoffs between providers. This discussion showed what happens when founders design around real human behavior instead of legacy systems. I was particularly fascinated by the simplicity and power of wallet-native insurance. Consumers already use wallet technology every day for boarding passes, payments, loyalty cards, and transport tickets. Integrating insurance directly into that ecosystem feels obvious once you see it in action. The results speak volumes: more than 50,000 wallet cards issued within months and exceptionally high customer engagement rates. That tells us customers are ready for insurance experiences that are frictionless, visible, and mobile-first. Another important insight is how the MGA model is evolving. Ernesto highlighted how modern MGAs are increasingly powered by specialist InsurTech enablers rather than trying to build every capability themselves. The future is less about disruption in isolation and more about intelligent collaboration, integration, and speed to market. This partnership demonstrates how insurers, MGAs, and technology providers can create far more value together than separately. Finally, I loved the honesty around AI and the “agentic frontier.” Both guests acknowledged that technology alone is not enough. The real challenge is guiding customers through increasingly complex ecosystems in ways that remain trustworthy, intuitive, and human-centered. The winners in this next phase of insurance innovation will be the companies that combine intelligent automation with seamless customer trust.   BEST MOMENTS “The era of the app, as we have known it, is over.” — Marc Lampe “88% said they have trouble finding their documents.” — Ernesto Suarez “Insurance has never been tangible. And I feel like this is a little piece that we can give customers for what they’ve purchased.” — Ernesto Suarez “The solution is not to build the perfect AI-driven functionality, but to deliver that actually to the customer.” — Marc Lampe “We’re all very good at selling, but it’s the post-sale se

Transcribed - Published: 28 May 2026

Insurance did not fail the mobility economy because it lacked technology. It failed because it misunderstood behavior. That is the core insight behind this conversation with David Daiches, COO & Co-Founder of INSHUR — the embedded insurance company powering protection for some of the world’s largest on-demand platforms, including Uber, Amazon, and DoorDash. The breakthrough started in Manhattan in 2016. David and his co-founder spent weeks taking short Uber rides across the city asking drivers one question: how do you buy insurance? The answer exposed a major gap. Traditional taxi drivers were comfortable visiting brokers and navigating legacy processes. But Uber drivers lived through their smartphones. Insurance had become a real-time operational dependency — not an annual transaction. That insight became the foundation for INSHUR’s growth into one of the fastest-growing mobility insurers globally, issuing more than one million policies and covering over 25 million Amazon Flex driving hours through its wallet technology. In this episode, David shares the blueprint behind scaling a global insurtech in one of the industry’s most difficult categories: commercial mobility risk. The conversation explores: * Why “fluency over features” became INSHUR’s competitive advantage * How embedded insurance removes friction from platform ecosystems * Why wallet technology transformed pay-as-you-go coverage for gig economy drivers * The operational lessons learned moving from outsourced to in-house claims * Why financial discipline became critical after the “growth at all costs” era * How EVs are reshaping frequency-versus-severity risk models * Why autonomous vehicles represent the hardest liability challenge insurance has ever faced One of the most powerful moments comes when David reframes insurance through the eyes of a driver finishing a 12-hour shift at 2am on a rainy Tuesday night. An accident happens. Airbags deploy. The driver sits silently wondering how they will pay rent next week. That is when David realized: “Claims is the product.” Not the app. Not the onboarding flow. Not the API. The claims experience defines trust. The conversation then moves into the next frontier: autonomous mobility. David explains why AV insurance fundamentally changes the industry’s understanding of liability: * Was it the software? * The sensor? * Connectivity failure? * Human override? * Machine decision-making? Traditional “who-hit-who” frameworks no longer work in a world where vehicles become intelligent systems operating inside digital ecosystems. To solve that challenge, INSHUR is building the Autonomous Insurance Exchange (AIX) — a framework designed to translate sensor telemetry, platform integrations, and machine-generated data into real-time underwriting and claims decisions. The implications extend far beyond mobility. This is about building the next insurance intelligence layer — where embedded ecosystems, AI-native underwriting, and intelligent orchestration converge. Three principles define that future: * Fluency over features * Partnership as the new distribution * Respect the claim This episode is essential listening for: * Insurance and mobility executives * Embedded finance leaders * Commercial fleet and auto insurers * Autonomous vehicle innovators * Claims and underwriting teams * Insurtech founders and investors * AI and mobility infrastructure strategists Because the future of insurance will not be defined by policies alone. It will be defined by who can orchestrate trust, resilience, and risk intelligence in real time.

Transcribed - Published: 21 May 2026

What if the biggest opportunity in insurance isn’t pricing risk—but transforming it? Alan Martin brings a bold, necessary reframe to the life and health insurance industry: the future belongs to insurers who move beyond actuarial prediction and into active health orchestration. At the center of this shift is his concept of modifiable risk—the idea that many health outcomes are not fixed, but can be influenced through timely, personalized, and scalable interventions. For decades, insurers have operated within a reactive model: Assess risk at underwriting Pay claims when events occur Offer limited, often disconnected support But this model is breaking down under the weight of rising chronic disease, mental health challenges, and post-pandemic shifts in customer expectations. Alan exposes a critical flaw: most health propositions fail because they don’t engage. Low engagement → high cost per use High cost → reduced investment Reduced investment → poor customer experience This “engagement-cost doom loop” is reinforced by outdated service models—like generic nurse helplines—that lack personalization, digital access, and effective triage. Instead, Alan argues for a fundamentally different approach: 1. Intervene at the moment that matters most The point of diagnosis or claim is where behavior can change. Yet insurers are often absent. This is where personalized pathways, digital triage, and embedded services must come into play. 2. Redesign wellness to include everyone—not just the healthy Today’s programmes often reward those already fit. True innovation targets high-risk populations with affordable, scalable interventions that deliver measurable outcomes. 3. Build economic models around health improvement Modifiable risk enables: Dynamic pricing linked to behavior change New product innovation Reduced claims through prevention This is not philanthropy—it’s commercially viable prevention. 4. Embrace embedded health ecosystems Through platforms like CareVoice, insurers can orchestrate care journeys—connecting policyholders to the right services at the right time, seamlessly. 5. Rethink risk appetite for a new world Post-pandemic realities demand new assumptions: AI-driven insights Rising chronic disease burdens Increased focus on mental health Risk is no longer static. It’s dynamic, behavioral, and deeply human. This episode challenges insurers, startups, and policymakers alike to rethink their role—not as payers of claims, but as partners in health outcomes. Because the real question is no longer: How do we price risk more accurately? It’s: How do we reduce it—at scale, sustainably, and profitably? This episode is essential listening for: Insurance executives redefining product and risk strategy Healthtech founders building engagement and care platforms Policymakers shaping preventive health systems Innovation leaders designing embedded ecosystems Investors seeking scalable models in health and insurance So here’s the challenge: If you could influence risk before it becomes a claim… why wouldn’t you build your entire business model around it?

Transcribed - Published: 14 May 2026

The future of health insurance will not be defined by faster claims processing—but by relevance in everyday life. In this episode, Xavier Lestrade, Managing Director of AXA Health International at AXA Global Healthcare, explores how insurers must evolve beyond the traditional payer model toward personalized, outcome-driven healthcare ecosystems. The shift is clear: from claims management to care orchestration, from reactive reimbursement to proactive health engagement. At the core is a new operating model—the frontier healthcare insurer. This is not incremental innovation. It is a structural transformation where insurers redesign value creation through personalized care pathways, integrated data, and intelligent systems that support members before, during, and after health events. Three stages of AI and operational maturity define this evolution: * AI-assisted workflows that enhance productivity, enabling faster decision-making and automation of routine tasks. * Human and AI collaboration, where digital agents triage, coordinate care, and support members while humans focus on complex interventions. * Autonomous care pathways, where AI-powered systems manage real-time workflows under human-defined governance and outcomes. However, technology alone is not the strategy—execution is the differentiator. To successfully transition to this model, five critical enablers emerge: * Data governance in healthcare: Clean, consent-driven, and auditable data is essential to enable personalization, ensure compliance, and build trust. * Ecosystem partnerships: Leading insurers orchestrate networks of healthtech partners, providers, and platforms to deliver seamless, end-to-end member experiences. * Organizational change management: Cultural alignment, incentives, and operating models must evolve to support a new definition of value focused on outcomes, not transactions. * AI integration and intelligent orchestration: Embedding AI into real workflows—not pilots—is key to scaling impact across member journeys. * Leadership alignment and governance: CEO and board-level commitment, funding discipline, and accountability are critical to avoid fragmented transformation efforts. A key insight from this discussion is the changing expectation of health insurance customers. Members increasingly demand preventive care, wellness support, and personalized guidance—not just coverage when something goes wrong. This creates an opportunity for insurers to enhance customer engagement, retention, and lifetime value through continuous, meaningful interactions. For stakeholders across the ecosystem: * Health insurers must rethink growth strategies beyond claims and focus on proactive care models. * Corporates and enterprise leaders should prioritize data-driven health engagement to better manage risk and employee wellbeing. * Healthtech startups need to build scalable, integration-ready solutions that fit into complex insurer ecosystems. * Regulators and governance leaders must ensure transparency, accountability, and trust in AI-enabled healthcare systems. Delivering a unified, global health experience remains operationally complex—spanning legacy systems, multiple geographies, and diverse partners. Yet this complexity is where competitive advantage is built: in the integration of digital capability, clinical relevance, and trusted member relationships. This episode is essential for: * Health insurers transforming toward value-based care and personalized insurance models * CEOs, COOs, and Chief Data Officers leading digital health and AI transformation * Healthtech founders building scalable, partnership-driven platforms * Ecosystem leaders designing connected healthcare experiences * Risk, compliance, and governance professionals shaping responsible AI in healthcare The defining question remains: Will future health insurers simply pay claims—or become trusted platforms that help people live healthier, longer, and more informed lives?

Transcribed - Published: 7 May 2026

AI isn’t disrupting your business because it’s intelligent. It’s disrupting it because it orchestrates. In this solo episode of Scouting for Growth, Sabine VanderLinden explores why MIT CISR’s Business Models in the AI Era is a must-read for leaders in insurance, finance, and risk. The real shift? Moving from static, function-led organisations to adaptive, outcome-driven firms. MIT’s data tells a clear story. In 2013, only 12% of companies operated as Ecosystem Drivers. By 2025, that number reached 58%—and these firms consistently outperformed peers on growth. Orchestration isn’t a future idea. It’s already a competitive edge. Now, with agentic AI, four new models emerge: * Existing+ — AI-enhanced incumbents * Customer Proxy — acting on behalf of customers * Modular Creator — assembling capabilities dynamically * Orchestrator — coordinating ecosystems around outcomes For regulated industries, Sabine introduces the Frontier Insurer Matrix: Legacy Carrier → Agile Innovator → Empathetic Advisor → Frontier Insurer The leap is profound. Imagine a burst pipe. Legacy insurers react after damage. Frontier insurers prevent, respond, and recover in real time—detecting the issue, stopping the leak, dispatching help, and settling payments automatically. This is the shift: from paying claims to shaping outcomes. Sabine outlines the Frontier Firm stack: * Headless core systems (API-accessible) * Agentic AI platforms (reasoning + guardrails) * Specialist connectors (insurtech, fintech, healthtech, cyber) Here, the venture-client model becomes a strategic weapon—plugging best-in-class innovation into your value chain without owning it all. The impact goes beyond insurance. CFOs move from reporting to real-time decision support. Wealth managers orchestrate portfolios, tax, and protection as one outcome. Risk leaders face a dual reality: AI as mitigation tool—and new risk frontier. Which brings us to the critical piece: guardrails. In an agentic world, governance must be designed upfront: ethical boundaries, escalation paths, override mechanisms, decision rights—and the right Human–Agent Ratio for each workflow. Because not every decision should be automated. Sabine closes with five imperatives: know your position, make systems headless, build your ecosystem, redesign governance, and train “Agent Bosses.” The question isn’t whether AI will reshape your industry. It already is. The real question: will you automate the past— or orchestrate a better future?

Transcribed - Published: 30 April 2026

The future of property underwriting will not be won by carriers with the most models. It will be won by those with the most decision-grade intelligence. In this episode of Scouting for Growth, Sabine VanderLinden speaks with Anthony Peake, CEO of Intelligent AI, about a problem hiding in plain sight across commercial property insurance: the risk intelligence gap. The conversation is built around one uncomfortable truth. Underwriters are being asked to make portfolio-defining decisions using exposure data that is often incomplete, unverified, outdated, and disconnected from the workflows where decisions actually happen. That matters because the scale is hard to ignore: In the UK, only 7% of properties are adequately characterized in underwriting files, while 93% are insured for the wrong amount. In the US, 90% of commercial buildings carry inadequate coverage, with 68% falling short by 25% or more. Underwriters rate their access to decision-time risk intelligence at just 3-5 out of 10 and spend 50–55% of their working day chasing, checking, and rekeying data rather than applying judgment. Meanwhile, the US P&C industry posted underwriting losses exceeding $20 billion in both 2022 and 2023, even as carriers continued to invest heavily in AI and automation. This is the automation paradox Anthony unpacks so clearly. Better engines. Worse fuel. Massive investment in AI pricing, triage, and catastrophe models — but weak building-level inputs at the very moment of decision. The conversation then shifts from diagnosis to design. Anthony explains Intelligent AI’s three-part framework for modern property underwriting infrastructure: API-first risk intelligence, where a property address is enriched with structured data across construction, occupancy, protection, hazard, human-made risk, and climate signals in seconds. Intelligent rebuild cost modeling, especially critical in the US, where inflation, labor shortages, tariffs, and code drift have made historical valuations increasingly unreliable. Living digital twins of risk, continuously updated virtual representations of buildings and their exposure context, enabling a shift from assumption-based underwriting to evidence-driven orchestration at scale. Why does that matter strategically? Because the implications go far beyond underwriting productivity. For corporates, it means better portfolio steering, more defensible pricing, and a clearer line of sight on accumulation risk. For brokers, it means richer submissions and stronger quote-to-bind outcomes. For MGAs, it creates a path to providing underwriting precision to capacity providers. For regulators and boards, it creates the provenance, explainability, and auditability increasingly required under emerging AI governance expectations. Anthony also highlights what happens when exposure intelligence improves. A major UK mutual moved from manually surveying 10% of its commercial portfolio to achieving real-time oversight across 100% of addresses. In wildfire-prone zones, verified property-level mitigation data helped drive a 60% reduction in loss frequency. And frontier carriers are already compressing quote cycles from days to under 30 minutes when structured risk intelligence is properly embedded in workflow design. This episode is essential listening for: - Chief Underwriting Officers - Heads of Property and Specialty Lines - Chief Data and Analytics Officers - Broking and placement leaders - MGA founders and portfolio builders - Insurtech product and infrastructure leaders - Reinsurance and capital strategy executives The real question is no longer whether the industry has enough data. It is whether leaders are ready to build the intelligent orchestration layer that turns fragmented signals into trusted underwriting action. And as catastrophe volatility, climate drift, and capital pressure intensify, one question remains: who will close the risk intelligence gap first — and own the best risks because they did?

Transcribed - Published: 23 April 2026

Trust is not a feature. It’s the foundation. And yet, most organizations are still treating it as an afterthought—something to audit, regulate, or retrofit once AI is already in motion. That mindset is breaking. Fast. In this episode, Steven Abel and Franklin Manchester introduce a critical shift: from managing AI risk to engineering trust into the system itself. This is the essence of Trust by Design—a framework that redefines how enterprises build, deploy, and scale AI in an agentic world. Because we are no longer deploying tools. We are deploying decision-makers. And that changes everything. Here’s what becomes clear: The industry’s false start Organizations are over-investing in models and under-investing in decision architecture. More LLMs ≠ more trust More data ≠ better decisions More pilots ≠ real transformation The breaking point of autonomy As AI systems evolve from copilots to agents, the risk profile shifts dramatically: Decisions are made faster—and at scale Human oversight becomes impractical Errors compound across interconnected systems The idea of “human in the loop” quickly collapses when one human is expected to validate thousands of machine-generated decisions daily. What Trust by Design actually requires Trust must be embedded across the full lifecycle of decision-making: Governance: Clear ownership and accountability structures Explainability: Every decision must be traceable and interpretable Monitoring: Continuous oversight, not periodic review Testing: Backtesting decisions—not just models Documentation: Transparent and auditable processes This is not compliance overhead. It is an operational infrastructure. A critical shift in metrics Leaders must move beyond accuracy as the gold standard. Instead, they must ask: Is the decision fit for purpose? Does it perform consistently in real-world conditions? Can we challenge and improve it over time? This is the move from model performance to decision fidelity. The leadership mandate This transformation cannot be delegated. It requires: CEO-level ownership Board-level oversight A clear, enterprise-wide doctrine on trust Without this, AI remains experimentation—not execution. For different stakeholders, the implications are profound: For corporates: Trust becomes the enabler of scalable automation and competitive advantage For startups: Trustworthiness becomes a differentiator—not just capability For regulators: The focus shifts from static compliance to dynamic system accountability This episode is essential listening for: CEOs and board members defining AI strategy Chief Risk, Data, and Technology Officers building governance frameworks Transformation leaders moving from pilots to scaled AI systems Founders building enterprise-grade AI solutions Because the real question is no longer: Do we trust AI? It’s this: Have we built systems that deserve that trust?

Transcribed - Published: 9 April 2026

Execution is the new strategy. Yet most organizations still treat it as an afterthought. In this solo episode, Sabine VanderLinden introduces a critical leadership lens: the Capacity Gap—the structural mismatch between strategic ambition and an organization’s ability to deliver at scale. In a world shaped by generative AI, climate pressure, cyber risk, and rising customer expectations, this gap is no longer occasional. It is systemic—and it is widening. Too often, a failed transformation is blamed on talent, technology, or strategy. Sabine challenges that assumption. The real issue is more fundamental: organizations continue to stack priorities without redesigning how work gets executed. The result? Friction, overload, and stalled value creation. The numbers are hard to ignore: * Up to 80% of strategy execution failures link back to the ambition–capacity gap * $1.85 trillion spent on digital transformation in 2022, yet 70% underperforming * In insurance, only 7% of firms have scaled AI enterprise-wide, with most stuck in “pilot purgatory.” * 70% of scaling barriers are organizational—not technological So what does it take to close the gap? Sabine introduces the concept of the Frontier Firm—organizations that treat capacity not as fixed, but as something to be designed, orchestrated, and multiplied. These firms shift the question from “How do we build this?” to “How do we deliver outcomes faster and smarter?” Two powerful examples bring this to life. Ping An has evolved from a traditional insurer into a technology-driven ecosystem. With over 53,000 patents, 3,000 scientists, and 21,000 developers, it has built an intelligent operating core that delivers real performance gains—7.4-minute claims processing, 93% automated underwriting, and 95% AI accuracy in damage assessment. More importantly, it transformed internal capabilities into external value through OneConnect, which now serves nearly the entire Chinese banking ecosystem. Nestlé, facing constraints on innovation speed, deployed generative AI to compress product development cycles from 3 months to just 3 weeks—generating over 1,300 concepts in minutes. This is not just efficiency. It is intelligent orchestration at scale. To move from insight to action, Sabine outlines a practical five-step playbook: * Audit true delivery capacity against strategic ambition * Increase innovation throughput by focusing on completion, not volume * Leverage ecosystems and venture-client models as force multipliers * Build operational elasticity through modular tech and flexible talent models * Embed capacity as a core leadership and governance metric This shift matters across the ecosystem. Corporations must reduce execution drag to make transformation investable. Startups must position themselves as execution partners, not just solution providers. Boards and regulators must rethink governance in a world where capability evolves faster than control frameworks. This episode is essential listening for: * CEOs and board leaders driving transformation * Chief operating, digital, and innovation officers * Insurance and financial services executives scaling AI * Founders building enterprise-grade solutions * Leaders turning ecosystems into execution advantage The question is no longer whether your strategy is bold enough. The real question is: do you have the capacity to deliver it?

Transcribed - Published: 26 March 2026

Risk is no longer something we predict. It’s something we design for. In this episode of Scouting for Growth, Sabine VanderLinden sits down with Florian Graillot, Founding Partner at Astorya VC, to explore how artificial intelligence, venture capital, and new business models are reshaping the future of insurance and risk management. At the heart of the conversation is a fundamental shift: from static, backward-looking risk models to adaptive, forward-looking systems built for uncertainty. As emerging risks—from climate volatility to cyber threats and AI-driven fraud—accelerate beyond historical data, insurers and financial institutions must rethink how they create value. Florian shares insights from over 15 years of investing in insurtech and risk innovation, highlighting why the most successful organizations are no longer optimizing silos, but redesigning the entire risk value chain—from prevention and risk assessment to capital efficiency and claims. These “frontier firms” don’t just digitize—they continuously learn, evolve, and act in real time. A central theme is the rise of “intelligence on tap.” AI is no longer an experiment sitting at the edge of the organization; it is becoming embedded infrastructure. But technology alone is not the differentiator. The real advantage lies in how organizations combine AI agents with human expertise to create faster, smarter, and more trusted decision-making systems. The discussion also challenges conventional thinking around regulation. While often perceived as a barrier, Europe’s regulatory environment may provide a strategic edge—enabling the development of trust-by-design AI models that are explainable, ethical, and aligned with long-term customer value. Yet, transformation is not without friction. Sabine and Florian unpack the real constraints facing incumbents: talent gaps, cost pressures, and the tension between short-term performance and long-term innovation. Their message is clear—layering AI onto legacy systems is not transformation. Meaningful change requires intention, ecosystem collaboration, and a willingness to rethink operating models from the ground up. For founders and investors, the bar is equally high. The most compelling ventures combine deep industry expertise with strong technical capability—bridging the gap between understanding the problem and building scalable solutions. Ultimately, this episode reframes risk itself. Emerging threats are not just challenges to manage—they are opportunities to build resilience. And resilience, in today’s environment, is fast becoming the ultimate competitive advantage. As Florian puts it, technology doesn’t remove risk—it reveals our choices. For leaders in insurance, finance, and risk, the question is no longer whether to transform, but how fast—and how boldly—you are willing to act.

Transcribed - Published: 12 March 2026

Financial services aren’t being digitized. It’s being re-architected. In this episode of Scouting for Growth, Sabine VanderLinden sits down with Karl Grandl (Miss Moneypenny Technologies) to unpack one of the most critical shifts facing insurance, banking, and capital markets: the rise of the Intelligent Experience Layer—a customer-centric orchestration fabric that connects data, AI, governance, and distribution in real time. Because here’s the uncomfortable truth: most “digital transformation” efforts are still layering automation onto legacy systems. And that doesn’t create intelligence—it creates fragmentation. What’s emerging instead is a new operating model. Karl introduces the concept of a Customer Experience Fabric—an intelligent orchestration layer that embeds compliance, risk, and customer engagement directly into workflows. The result? Financial services that feel seamless, adaptive, and increasingly invisible. We’re entering the era of the Frontier Firm—where competitive advantage is no longer defined by products alone, but by how intelligently organizations integrate: * Agentic AI and human expertise * Real-time data and decisioning * Embedded governance and compliance * Ecosystem-driven distribution models This shift has profound implications. Compliance moves from retrospective reporting to real-time intervention. Underwriting evolves into a living, adaptive system. Distribution becomes intelligence-augmented—not disintermediated. And customer experience transforms from fragmented journeys into continuous, orchestrated engagement. For European insurers and financial institutions, regulation (think EU AI Act and digital identity wallets) isn’t friction—it’s fuel. It’s creating the infrastructure for trusted, scalable, and compliant innovation across 450 million citizens. Looking ahead, the industry is moving fast: * Up to 60–80% of low- to mid-complexity processes could become autonomous * Claims may evolve into “service recovery moments.” * Insurance and protection could become embedded, invisible infrastructure * Brokers and advisors will shift toward higher-value, strategic roles The real battleground? Not AI adoption. AI orchestration. This episode is essential listening for: * Insurance executives (CROs, COOs, Chief Digital Officers) * Banking and capital markets leaders navigating AI transformation * MGAs and InsurTech founders building next-gen distribution models * Strategy and innovation leaders redesigning operating models for scale Because the question is no longer whether transformation is happening. It’s whether you’re optimizing yesterday’s model—or architecting tomorrow’s intelligence layer.

Transcribed - Published: 5 March 2026

AI isn’t transforming insurance from the outside. It’s quietly rewriting it from the core—and exposing who’s ready, and who’s not. Insurance leaders talk about innovation, but many are still constrained by legacy systems that dictate how decisions are made, how fast change happens, and how much risk leaders are willing to take. In a world where customer expectations evolve in real time, that hesitation has become a liability. In this episode of Scouting for Growth, Sabine VanderLinden is joined by Manish Shah, President and Chief Product Officer at Majesco, to unpack what happens when intelligence is embedded directly into the core of insurance operations. Manish challenges a dangerous assumption: that being “cautious” with AI is safer than moving forward decisively. In reality, the greatest risk facing insurers today isn’t automation—it’s irrelevance. As AI evolves from copilots to agentic systems capable of autonomous action, insurers must decide where technology ends and human accountability begins. This conversation tackles the hard questions leaders are wrestling with—but rarely say out loud. Which decisions should never be fully delegated to machines? How do insurers earn trust operationally, across underwriting, claims, and service, rather than promising it in marketing decks? And how do you modernise without breaking the very promise insurance was built on? Manish shares why the future isn’t about efficiency alone. The real opportunity lies in redesigning insurance to feel more relevant, more responsive, and more human—using AI to augment judgment, not replace it. Looking three to five years ahead, this episode paints a credible vision of insurance powered by intelligent cores, guided by humans, and built around participation, prevention, and peace of mind. This is a must-listen for CEOs, CIOs, CPOs, and innovation leaders who know that AI is no longer a future conversation—it’s a leadership test. Because the real question isn’t whether AI will reshape insurance. It’s who will have the courage to redesign it responsibly—and first.

Transcribed - Published: 26 February 2026

Insurance doesn’t have a technology problem. It has a prevention problem—and a leadership one. For decades, the industry has mastered the art of paying claims after losses occur. But in a world defined by climate volatility, cyber threats, and real-time data, that model is cracking fast. Rising loss ratios aren’t just a financial warning—they’re a strategic one. In this episode of Scouting for Growth, Sabine VanderLinden is joined by Gil Arazi, Founder of The Spark and Managing Partner at FinTLV Venture Capital, to challenge one of insurance’s most sacred assumptions: that risk can only be managed after the fact. Gil argues that the next era of insurance will be built on prevention as a growth engine, not a cost center. And that shift isn’t theoretical—it’s already underway. Together, they unpack why many insurers are still trapped in innovation theatre, mistaking pilots for progress, while the real opportunity lies in bending the loss curve through data, collaboration, and trust. Gil explains why prevention fundamentally reshapes underwriting, pricing, and customer relationships—and why that makes many executives deeply uncomfortable. This conversation goes beyond technology. It tackles the emotional and cultural transformation leaders must embrace: moving from fear to conviction, from silos to ecosystems, and from control to collaboration—even with competitors. You’ll hear why AI won’t replace underwriters, but will radically elevate the human skills that matter most. Why trust—not algorithms—will define the winners. And why insurers who fail to act risk becoming irrelevant to the very customers they were built to protect. This episode is for CEOs, innovation leaders, and founders who know the model is broken—but are ready to rebuild it intelligently. Because the future of insurance won’t belong to the fastest claim payers. It will belong to the protection architects.

Transcribed - Published: 19 February 2026

The world isn’t becoming uninsurable. Leaders are choosing not to redesign it. Climate risk is accelerating. Cyber threats are multiplying. The protection gap is widening. And yet, “uninsurability” has quietly become a convenient excuse for inaction. In this solo episode of Scouting for Growth, Sabine VanderLinden challenges that narrative head-on—and introduces The Frontier Firm: organizations that are rewriting the rules by becoming human-led, agent-operated enterprises. Drawing on firsthand insights from global boardrooms, Microsoft Ignite, and real-world transformations, Sabine explains why incremental improvement is no longer enough. The capacity gap facing enterprises cannot be solved by working harder—it requires a leap. That leap is agentic AI. Frontier Firms are not experimenting at the edges. They are redesigning their operating models so humans set direction, judgment, and purpose—while AI agents handle execution at scale. This shift moves organizations from AI assistance to human–agent teams, and ultimately to fully agent-operated workflows with human oversight. Sabine then lays out the Five Levers of Frontier Firm success: Data governance and ethics as the non-negotiable foundation Ecosystem partnerships as the only viable path forward Cultural and change enablement as the true bottleneck Deep AI integration into core workflows Leadership alignment and organizational agility This isn’t theory. Applying this framework to global insurance leaders reveals the Agentic Five—Ping An, Allianz, Chubb, Zurich, and Aviva—each proving that agentic enterprises can be built through different strategies: building, partnering, or platforming. From Ping An’s autonomous AI workforce at scale, to Allianz’s venture-client mastery, to Aviva’s disciplined, human-centric deployment, these firms aren’t waiting for certainty. They are creating it. The episode closes with a direct call to action—for incumbents fearing irrelevance, founders seeking traction, and leaders stuck between vision and execution. The message is clear: the playbook exists, the tools are ready, and the examples are visible. The only real question left is this: Who will have the courage to execute? ------------ Frontier Firm Agentic Enterprise AI Agents Insurance Innovation AgentIQ 5 Ping An Allianz Chubb Zurich Insurance Aviva Microsoft Ignite Digital Transformation Venture Client Corporate Innovation Scouting for Growth Sabine VanderLinden Alchemy Crew Data Governance AI Leadership Human-Agent Teams InsurTech World Economic Forum

Transcribed - Published: 12 February 2026

On this episode of Scouting For Growth, Sabine VdL sits down with Sangha Penesetti, Founder & CEO of goZeal—a leader who didn’t just break the glass ceiling… she redesigned the entire building (with better lighting and significantly better policies). Sangha shares the deeply personal story that sparked goZeal: early in her career, every client meeting felt the same—rooms filled with men, with Sangha often the only woman and the only woman of colour in the room. When she became a mother in 2010, the lack of flexibility in the industry became impossible to ignore. There was little empathy, no real system support for working mothers, and certainly no workplace designed for parents navigating both ambition and responsibility. Then came Covid—and with it, a painful revelation. Sangha saw brilliant, highly educated women (especially Indian and Asian mothers) quietly step out of the workforce to raise families—and never return. Not because they lacked capability or drive, but because the system simply wasn’t built for them. That moment made everything click: this wasn’t an individual problem. It was a systemic design flaw. And that’s when goZeal was born. Together, Sabine and Sangha explore what “empowerment” really means. It’s not a buzzword, it’s economic mobility—financial freedom, autonomy, and the ability for women to shape their own lives, careers, and futures. As Sangha puts it, being included isn’t the same as being empowered. True inclusion is about access to meaningful work, decision-making authority, and direct pathways to opportunity. This episode goes beyond surface-level DEI conversations and into the hard economics of equity. The message is clear: when women—especially women of colour—advance, companies don’t just look better on paper. They become more innovative, more resilient, and stronger financially. A major focus of the conversation is flexible work—and why the insurance industry must stop treating it like a perk. Sangha challenges the myth that remote work automatically equals flexibility. Real flexibility means flexibility of time, not just location. goZeal’s approach is bold: hire women directly, offer true autonomy, and build roles that enable peak performance without forcing people into outdated models of productivity based on proximity. Sangha makes a compelling case for insurers: flexibility is a performance driver. When people can work at their best, companies gain higher-quality outcomes, reduced burnout, stronger retention, and lower attrition. In short: better work, better talent, better results. If you’re an insurer thinking about workforce strategy, talent gaps, operational modernization, or how to build a future-ready organization—this episode is your wake-up call (served with data, leadership, and just the right amount of disruption). Because the future of insurance isn’t just digital. It’s inclusive by design.

Transcribed - Published: 25 December 2025

On this episode of Scouting For Growth, Sabine VdL welcomes Marinela Profi, Global Market Strategy Lead for AI, GenAI, and Agentic AI at SAS, for a sharp, grounded conversation on what’s actually happening in enterprise AI right now—and what leaders need to prepare for next. Together, they cut through the noise surrounding generative AI and focus on what comes after the chatbot era: agentic AI. If generative AI is the talented communicator in the room, agentic AI is the one who not only speaks—but takes action, executes workflows, and delivers outcomes. Marinela puts it simply: Generative AI talks. Agentic AI does. The episode begins by reframing a major misconception: LLMs alone don’t solve business problems. While generative AI chatbots are excellent at answering questions, summarizing content, and producing text, they typically stop at conversation. Business transformation, however, requires systems that can reason, make decisions, interact with data, follow rules, coordinate across tools, and carry tasks through to completion. That’s where agentic AI steps in—combining large language models with analytics, policies, data pipelines, governance frameworks, and real operational logic. Marinela explains that AI agents aren’t a futuristic fantasy—they’re a practical evolution of automation, made smarter through contextual understanding and orchestrated decision-making. To help business leaders and technical teams understand what “agent behavior” looks like in real life, she shares her 5-step lifecycle framework—a clear model for how agents operate end-to-end: Perception – sensing signals from users, systems, or environments Cognition – reasoning, interpreting context, and forming intent Decisioning – selecting the best course of action based on goals and constraints Action – executing tasks across workflows and tools Learning – improving over time through feedback and outcomes But the most important message in this episode isn’t just that agents are powerful—it’s that autonomy must be designed responsibly. Marinela emphasizes that the real leap forward for enterprises won’t come from more impressive demos. It will come from governance, because trust is becoming the true competitive advantage in AI. She forecasts that by 2026, governance boards will increasingly resemble digital oversight committees—not just approving AI deployments, but ensuring agents are safe, accountable, explainable, auditable, and continuously monitored. A critical insight: governance doesn’t end when an agent is launched. Performance and behavior must be monitored continuously, particularly as agents learn from human feedback loops. Marinela warns that learning mechanisms can’t be left unchecked—because allowing an agent to “self-update” in uncontrolled ways is not innovation, it’s operational risk wearing a futuristic costume. The conversation also tackles one of the biggest leadership questions emerging right now: How autonomous should an AI agent be? Marinela’s answer is refreshingly practical: most of the time, it depends on the risk and impact of the task. Low-risk activities may allow higher autonomy, while high-impact decisions demand constraints, oversight, and transparency. As she highlights throughout the episode, autonomy without accountability is a risk multiplier. Ultimately, this episode is a strategic guide for leaders who want to move beyond AI experimentation into reliable execution. The future isn’t just about faster answers—it’s about autonomous, governed intelligence that can explain what it’s doing, why it’s doing it, and who is responsible when it does. If your organization is wondering what comes after GenAI pilots, how to build AI trust at scale, or what enterprise AI will look like by 2026—this is the conversation to listen to. Because the winners in AI won’t be the ones with the flashi

Transcribed - Published: 18 December 2025

On this episode of Scouting For Growth, Sabine VdL sits down with Andrei Craciunescu, Founder and CEO of RiskCube, to explore why the next generation of insurance must be built like software: fast, adaptive, transparent—and embedded directly into how modern businesses operate. Andrei shares what startups really want from insurance today: speed. Especially for venture-backed companies, the old model of waiting weeks (or months) for underwriting decisions simply doesn’t match the pace of business. Founders don’t want endless conversations and back-and-forth emails—they want a quote in minutes, not a process that feels like it belongs in a filing cabinet era. That market gap is exactly why RiskCube exists. Andrei explains how traditional insurance shopping is fragmented and exhausting: founders often have to approach multiple carriers individually, requesting separate quotes that can vary dramatically—sometimes by 40%. Comparing those quotes becomes time-consuming, expensive, and difficult to understand, especially for operators focused on growth. RiskCube changes the experience by acting as an AI-powered insurance agency for startups, allowing customers to buy and manage insurance online through a streamlined, modern interface. The mission isn’t to make insurance “cool”—it’s to make it clear, fast, and trustworthy. Andrei notes that most founders don’t care which carrier is behind the policy; what they care about is having someone (or something) that truly understands their business risk and delivers an experience that works at startup speed. Sabine and Andrei also discuss how AI is reshaping the role of brokers—from a traditional middleman into an intelligent orchestrator. RiskCube is mapping the full agency workflow (applications, renewals, cancellations, claims) and identifying where AI agents can drive real value today. While Andrei is realistic that AI won’t automate the entire insurance value chain overnight, he sees major adoption already happening in applications and claims, where automation can significantly improve speed and efficiency. A key strategic advantage RiskCube is building is defensibility through data. Instead of layering AI onto an existing model, they’ve built the agency foundation first—then embedded technology into it—so they can own the customer relationship, generate proprietary data, and train their own models over time. The conversation also highlights a growing concern in the AI era: many people use AI daily without fully knowing where their data is going or how it’s hosted—making transparency and trust non-negotiable. Looking ahead to 2030, this episode paints a clear future: insurance becoming embedded and invisible, protection built into the platforms businesses already use, and trust emerging as the most valuable asset. Because in the future of insurance, the best experience won’t be the one with the most paperwork—it’ll be the one you barely notice.

Transcribed - Published: 4 December 2025

On this episode of Scouting For Growth, Sabine VdL sits down with Rob Schimek, Group CEO at bolttech, to unpack how the company’s connector model is reshaping global insurance distribution — not through more paperwork, but through smarter ecosystems that meet customers where they already are. If you’ve ever wondered what happens when insurance stops being a product you buy and starts becoming protection that’s simply… there, this conversation is your preview. Insurance distribution is being rebuilt (and it’s not starting with carriers) Rob explains bolttech’s mission in one powerful phrase: closing the multi-billion-dollar global protection gap — a gap that isn’t shrinking, it’s widening. The reason? Too many people and businesses still lack the right coverage because protection remains too complex, too expensive, too fragmented, or too hard to access. bolttech’s answer is to create a seamless connection between: Insurance providers (who build protection products), and Distribution partners (who already have customers — think telcos, retailers, auto makers and platforms) This is B2B2C distribution at scale: tailored, affordable, accessible coverage — delivered with convenience, not friction. Rob makes the point that the more you remove friction from connections, the more protection becomes adoptable… and the faster the protection gap closes. The real differentiator: trust, data, and design This episode goes beyond business models into something more strategic: what makes protection work in the real world. Rob is clear — the future of insurance won’t be won by premium tables and policy wordings. It will be won by: Trust (because adoption depends on it) Data (because personalization depends on it) Design (because customers won’t tolerate clunky experiences anymore) And data is the unlock. Rob highlights how real-time information — like vehicle telematics — enables insurers to move away from “paint everything with one brush” pricing and instead reflect the actual risk of the individual in front of you. For enterprise leaders, the implication is huge: the winners will be those who can turn data into relevance, and relevance into trust. Leadership: stay obsessed with the problem One of the most memorable leadership lessons from Rob is this: If you have an hour to solve a problem, spend 55 minutes understanding the problem and 5 minutes designing the solution. He’s spent his career deep in the “problem,” and bolttech represents the path he’s chosen to bring solutions to market at global scale. That focus matters, because when the mission is crystal clear, distractions don’t stand a chance — even when markets get noisy. AI only works where trust exists Rob also delivers a critical reminder for every executive racing toward automation: If customers don’t trust how AI is used in their experience, AI won’t be accepted — and therefore won’t succeed. Trust isn’t a tagline. It’s a prerequisite. Why this matters now For insurers, brokers, and platform partners alike, this episode is a blueprint for the next era of distribution: embedded, frictionless, data-driven protection, delivered through ecosystems customers already rely on. Because by 2030, the most successful insurance brands won’t just sell protection. They’ll make it effortless to access — and impossible to ignore.

Transcribed - Published: 27 November 2025

On this episode of Scouting For Growth, Sabine VdL flips the mic inward. After dozens of conversations with AI builders, insurance innovators, and enterprise leaders navigating transformation at full speed, she shares the real pattern she’s seen across the industry: AI isn’t just changing our tools. It’s changing our temperament. From founders simplifying chaotic insurance back offices to Fortune 500 teams wrestling with governance, regulation, and talent shortages, this episode is Sabine’s sharp, human (and very actionable) reflection on what actually drives successful AI adoption—and what quietly kills it. The hidden truth: resistance isn’t where you think Sabine opens with a story that stops most leaders in their tracks. When Branch Insurance introduced AI into claims, the pushback didn’t come from customers. It came from the adjusters. Not because the AI made mistakes… but because it didn’t. That moment reveals a leadership challenge many underestimate: AI doesn’t just automate tasks. It reshapes identity, confidence, and control. And if you don’t manage the human side, the tech side won’t matter. Governance isn’t the brake. It’s the steering wheel. Another standout lesson comes from Lisa Bechtold, formerly leading AI governance at Zurich Insurance (now at Nestlé). Her team faced the classic dilemma: move fast or move right. Her answer reframes the whole debate: Governance doesn’t slow innovation—it enables trust at speed. In the AI era, the best-run organizations won’t be the ones with the biggest models. They’ll be the ones with the clearest accountability. The real pilot-to-production gap is human Sabine also revisits the collaboration between ERGO Group and CamCom, an Indian startup using computer vision to assess vehicle damage from photos or drones. The technology worked. The real challenge was everything around it: integration, compliance, workflow change, validation, and risk. What made it succeed wasn’t a handoff—it was proximity. Engineers, adjusters, compliance teams, even lawyers worked side by side. It took nearly a year to go from pilot to production, but the outcome was bigger than faster claims. It created a new operating model: startups learned how corporates think corporates learned how startups move That’s where transformation becomes real. The shift no one can delegate: talent evolution Across all these conversations, one conclusion keeps rising to the top: AI won’t replace people. But people who know how to use AI will replace people who don’t. Not as a threat—but as an invitation. Claims adjusters now need to interpret AI outputs. Underwriters must question model logic. Leaders must learn to manage digital teammates. And success will belong to those who can blend automation with judgment—because intelligent tools don’t remove human decision-making… they reveal it in higher resolution. Sabine’s five principles for successful AI adoption This episode is a guide for enterprise executives and builders navigating the new age of intelligence, grounded in five leadership truths: Trust is the new currency Governance is acceleration, not friction Every AI dream dies in the shadow of bad data Pilots don’t fail because of tech—they fail because humans aren’t brought along The more intelligent systems become, the more human leadership must be Because the future of insurance won’t be won by who deploys AI first. It will be won by the leaders who can deploy it responsibly, scale it operationally, and guide people through it empathetically. And that’s the real edge.

Transcribed - Published: 20 November 2025

On this episode of Scouting For Growth, Sabine VdL sits down with Stephen Brittain, Co-Founder of InsurTech Gateway — the world’s first authorised venture builder and fund dedicated to insurtech — to explore what it really takes to build startups inside one of the most regulated, risk-averse industries on the planet. And yes… that industry is still insurance. (The land where “move fast and break things” gets politely escorted out by compliance.) Stephen has spent the last decade doing something most people talk about but few actually pull off: bringing early-stage innovation into the heart of large insurers — without killing the startup spirit in the process. He’s been a catalyst for corporate innovation leaders and a strategic guide for founders trying to navigate the labyrinth of regulation, procurement, and distribution at scale. From product design to mastering risk Stephen’s journey starts in product and service design, where he saw risk as the ultimate constraint. But instead of avoiding it, he leaned in. His curiosity became a turning point: what if understanding risk wasn’t a blocker… but the unlock for doing bigger and bolder work? That insight is what led him into insurance — not because it was “sexy,” but because it holds powerful, often underestimated capabilities: creating trust, enabling lending, and building mutual models that scale across ecosystems. The real job of a venture builder: keep the idea alive long enough to evolve InsurTech Gateway was born with a mission: find exceptional founders and help fast-track them into market with enough momentum (and resilience) to survive an environment where early ideas are too often treated as fixed commitments. But Stephen makes a critical point for every founder and innovation leader: no one gets it right on day one. Innovation is a learning journey, and the ventures that win are the ones that have the room—and the support—to adapt as reality hits. One of the biggest challenges in insurtech isn’t starting strong. It’s ensuring something that looked brilliant at launch actually evolves into the opportunity it promised. The missing link: connectivity between insurers and venture capital Stephen shares a blunt truth: the entrepreneurial excitement gets everyone moving, but on hard days, the question becomes sustainability. Because innovation doesn’t scale on enthusiasm alone — it scales when incentives align, capital supports the long game, and distribution becomes real. And historically, that alignment has been rare. Stephen highlights a structural disconnect: VCs and insurers haven’t traditionally sat at the same table, even though the future demands they build together. The good news? Pattern recognition has never been higher, and the cost of experimentation has never been lower. We can spot what works faster than ever before. The challenge is still the same: can you validate it with an insurer and get them truly onside? That’s where venture builders like InsurTech Gateway play a pivotal role — acting as the bridge between speed and scrutiny, ambition and regulation, creativity and sustainability. Why this matters for leaders right now For Fortune 500 executives, this episode is a reminder that innovation doesn’t fail because people lack ideas — it fails because they don’t understand risk well enough to scale them responsibly. For founders, it’s a roadmap for navigating the insurance operating system: if you can work with innovators, understand risk, and unlock sustainable adoption, you don’t just build a startup… You build something that lasts. Because the future of insurance won’t be shaped by the loudest demo. It will be shaped by the ventures that can earn trust, survive regulation, and scale in the real world.

Transcribed - Published: 13 November 2025

On this episode of Scouting For Growth, Sabine VdL sits down with Sebastien Denef, CEO and Co-Founder of AGENTS.inc, a company building intelligent agent platforms for enterprises—and helping leaders move from “AI curiosity” to AI capability at scale. This is not another ChatGPT-is-cool conversation. This is the episode for executives and founders who want to understand what’s really coming next: agentic AI architectures that don’t just generate answers… they execute outcomes. From automation to autonomy: the real upgrade Sebastien breaks it down in plain language: an AI agent is software you can assign a task to—and it will handle that task autonomously. That’s the step change. Compared to older automation layers, we’re now able to increase autonomy dramatically because we finally have two things we didn’t have before: powerful AI models oceans of usable data RPA helped move documents from point A to point B. AI agents do something far more valuable: they understand what’s inside the document, extract what matters, evaluate it, and push the right actions into the right systems. That wasn’t realistically possible before. Now, it is. Why “AI-ready” is a myth (and what real readiness looks like) One of Sebastien’s most important messages is a reality check for enterprises: using ChatGPT or Microsoft Copilot doesn’t make you AI-ready. It makes you AI-aware. Real readiness means building the infrastructure, workflows, and operating model that allows AI agents to deliver business value across silos—without breaking governance, security, or human accountability. Because once you deploy agents at scale, you don’t want to “chat” with them all day. You’d drown in messages. What you need is a control interface—a way to steer, supervise, and direct these tireless digital employees. “Computers that work while you sleep” Sebastien offers a powerful mental model: think of AI agents as computers that keep working after you log off. A tireless workforce running tasks in the background—processing, interpreting, executing—while humans focus on judgment, creativity, and decision-making. And he’s not shy about the scale of change. He estimates that more than 70% of the work people do today can be automated, and that this will reshape entire industries—especially those with large workforces built around repetitive knowledge tasks. Underhyped, not overhyped While the world debates whether AI is hype, Sebastien takes the opposite stance: agentic AI is underhyped. The real impact won’t just show up in corporate operations. It will touch everyday life too—education, job hunting, buying a home, grocery shopping, and even how we plan our weekends. In his view, we’re only seeing the first chapter of what’s possible. The winners: technology + collaboration Sabine and Sebastien explore why the winners in this new era won’t simply be the companies with the best model. They’ll be the ones who master: scalable architectures across silos collaboration between teams and functions and the ability to operationalize AI responsibly Because agentic AI doesn’t live in a lab. It lives inside workflows, systems, and people. And that’s where transformation becomes real. If you’re a leader wondering what comes after copilots, dashboards, and experiments—this episode is your blueprint for the next era of enterprise AI: autonomous execution, orchestrated at scale, led with intent.

Transcribed - Published: 6 November 2025

On this episode of Scouting For Growth, Sabine VdL is joined by two powerhouse voices shaping the future of enterprise transformation: Ulrich (Uli) Homann, Corporate Vice President at Microsoft, and Mark Luquire, EY Global Microsoft Alliance Co-innovation Leader. Together, they unpack a question every insurance and financial services executive is quietly asking right now: How do you build an agentic AI enterprise that doesn’t just move faster… but gets smarter — and works for everyone? From rigid automation to outcome-driven intelligence Uli and Mark draw a clear line between yesterday’s automation and today’s agentic AI reality. Traditional automation was task-driven and brittle: workflows had to follow a fixed sequence, and you needed to know that sequence in advance. If anything changed, the whole process broke or required manual intervention. Agentic AI flips that model. Instead of obsessing over steps, leaders can now focus on the outcome — and allow intelligent systems to help figure out how to get there, even when conditions shift mid-process. In other words, enterprises can begin to rethink not only how processes run… but which processes even need to exist. That’s not incremental change. That’s operational reinvention. What happens when everyone gets access? Mark shares a critical EY lesson: when EY gave broad access to generative AI across the organization early on, people didn’t just use it to speed up tasks. They used it as a thought-partner — a way to sharpen ideas, improve deliverables, and accelerate the quality of work. Productivity moved up. Confidence moved up. Curiosity moved up. And then the tech evolved again. Mark reflects on the rapid shift from early GenAI tools to today’s emerging agent capabilities — systems that can now write code, build applications, and take action with very little prompting. That evolution opens the door to a new enterprise reality: AI that doesn’t just assist… it executes. Or as the conversation makes crystal clear: It’s not just providing information anymore — it’s taking on work, processing decisions, and driving momentum. The leadership mindset shift: “start with where you want to be” One of the biggest takeaways from this episode is refreshingly simple—and extremely hard to do in practice: Focus on where you want to be… then rethink how you’re going to get there. That’s the key to unlocking agentic AI at scale. Because most organizations try to bolt AI onto existing workflows, legacy systems, and operating models. But agentic AI forces a different question: What if the old workflow is the problem? What if your best path forward is not optimization — but redesign? Why this matters for enterprise leaders (especially in insurance) For C-suite leaders, this episode is a strategic blueprint for what’s coming next: an enterprise where AI becomes a true digital workforce, operating alongside humans — amplifying expertise, reducing friction, and accelerating execution. But the goal isn’t speed for speed’s sake. It’s building intelligence that creates measurable business value and earns adoption across the organization — from the boardroom to the front line. Because the future won’t belong to companies that deploy the most AI tools. It will belong to the ones that build an agentic enterprise that’s trusted, scalable, and designed to work for people — not around them.

Transcribed - Published: 30 October 2025

On this episode of Scouting For Growth, Sabine VdL sits down with Laurna Castillo, Senior Vice President of Product at CSAA Insurance Group (a AAA insurer serving millions across the western United States), for a timely conversation on one of the most urgent challenges in insurance today: How do we build real resilience as wildfire risk escalates—and keep insurance accessible for everyday families? This isn’t just a climate conversation. It’s a community, affordability, and future-of-protection conversation. Wildfire resilience is becoming an insurance survival strategy Laurna shares a powerful reminder: AAA didn’t start as an insurance company. It began as an automobile association working to make driving safer—advocating for things like seatbelts. And that safety work mattered because it reduced losses, improved outcomes, and helped keep car insurance affordable. Now, Laurna says, wildfire is the modern equivalent. With homes being lost in massive numbers each year, the stakes are rising fast. Without scalable solutions that reduce wildfire damage, living in high-risk regions—like parts of California—could become financially out of reach for the average consumer. In other words: resilience is no longer a “nice-to-have.” It’s becoming a prerequisite for insurability. The hardest part? Knowing where to start. Laurna is candid about the biggest challenge CSAA faced: deciding where to begin. Wildfire mitigation is complex, multi-dimensional, and emotionally charged. But her lesson is one every leader needs to hear: Pick a direction. Stick with it. Progress compounds. Because waiting for the perfect strategy delays the only thing that matters—action. People are overwhelmed… and trust matters more than ever One of the most insightful parts of this episode comes from Laurna’s community engagement work. She explains that homeowners are flooded with information, and often receive conflicting advice—from neighbors, local leaders, online sources, and agencies. The result is decision paralysis. And it reinforces a hard truth for insurers: trusted voices matter. People are more likely to believe the motivations of someone they know than an institution they assume is profit-driven. That’s why community partnerships aren’t optional—they’re essential. As Laurna puts it: partnerships extend reach. And in wildfire resilience, reach saves homes. The 0–5 foot zone: the simplest action with the biggest impact If you only take one practical takeaway from this episode, it’s this: The single most important factor for wildfire mitigation is the 0–5 foot ignition zone around the home. Clearing flammable materials—like fencing, bushes, or overhanging vegetation—from that immediate perimeter can dramatically reduce risk. It’s not glamorous, but it’s powerful. And it’s actionable today. From there, the next challenge is scalability: creating consistent standards and repeatable guidance so homeowners aren’t left guessing what “safe” actually looks like. Build resilience into the system — not just the retrofit Laurna also highlights something the industry doesn’t say loudly enough: the easiest way to have a wildfire-resilient home is to build one that way from the start. Retrofitting is possible, but harder, slower, and often less effective. That’s where long-term change really lives: in codes, design choices, and ecosystem alignment. A leadership principle worth stealing Laurna’s most memorable line is also a leadership strategy: Do the next, best, right thing in front of you. Repeat it long enough, and it becomes a system of change. For insurers, this episode is a blueprint for moving from risk transfer to risk reduction. For communities, it’s a path to resilience. And for leaders, it’s proof that meaningful transformation doesn’t start with a grand plan… It starts with the next right step.

Transcribed - Published: 22 October 2025

On this episode of Scouting For Growth, Sabine VdL sits down with Yo Kwon, CEO of Voltaire.Claims, to shine a spotlight on one of the most underestimated pain points in insurance operations — and why fixing it can unlock serious financial and regulatory upside. Because while the industry loves talking about AI in underwriting, fraud, and customer experience… the real bottleneck is often buried in the back office. And yes — it’s the humble claims letter. The problem hiding in plain sight Yo shares how Voltaire.Claims started almost by accident. While testing AI applications for broader enterprise use, he noticed someone using their tool to write claims correspondence. That became the “wait… THIS is the problem?” moment. Claims adjusters don’t enjoy writing letters — especially denial letters. And when productivity is measured (as it always is), speed often wins over compliance. Adjusters rely on templates, cheat sheets, and copy-paste workflows, which makes it dangerously easy for small mistakes… and big ones… to slip through. The catch? In claims, correspondence isn’t admin. It’s evidence. It can determine whether a carrier stays compliant, avoids disputes, and prevents lawsuits. What Voltaire does differently: no shortcuts, no sloppy language Voltaire doesn’t just populate a template. It generates each claims letter from scratch, based on the actual claim context and policy language — reducing the risk of errors and misapplied clauses. But the real breakthrough is the guardrails. If an adjuster requests a denial letter and no valid policy exclusion exists to support it, the system stops the process and returns a message like: “No relevant policy language was found.” That one moment of friction can prevent: wrongful denials compliance violations reputational damage and the kind of disputes that turn into litigation This is what Yo means when he says: compliance is a product feature, not an afterthought. The economics are hard to ignore The financial case is as sharp as the operational one. Yo highlights that litigation alone adds an average of $10,718 per claim in loss adjustment expense. Voltaire estimates it can reduce litigated claims by 10% or more simply by producing clearer, more defensible correspondence. Even a conservative 5% improvement in leakage through better letters can translate into meaningful recovered value — not by working harder, but by communicating smarter. AI that improves the workforce, not just the workflow One of the most unexpected outcomes? Claims managers and adjusters told Voltaire that the AI was teaching them policy details they’d never known before. That’s the hidden advantage of well-designed enterprise AI: it doesn’t just automate tasks. It upgrades capability. It creates consistency. It protects the business from avoidable mistakes—at scale. Yo’s big insight is also Sabine’s warning to every leader: if you assume this problem should already be solved in 2025… you’re not alone. But claims complexity has grown faster than operational tools. And that’s exactly why this category is now ripe for reinvention. Why this matters for enterprise leaders If you’re a claims leader, COO, transformation exec, or innovation sponsor inside an insurer, this episode is a practical reminder that the next wave of competitive advantage won’t only come from shiny AI pilots. It will come from fixing the high-volume, high-risk workflows that quietly drive: compliance exposure loss costs customer trust and operational drag Because in insurance, trust isn’t built in slogans. It’s built one letter at a time.

Transcribed - Published: 16 October 2025

On this episode of Scouting For Growth, Sabine VdL speaks with Bobbie Shrivastav, Co-Founder and CEO of Solvrays, about the real transformation opportunity hiding in plain sight: insurance operations. Not the flashy front-end innovation. The messy, manual, high-volume back office work that quietly drives cost, delay, burnout—and operational risk. Bobbie’s mission is bold and refreshingly practical: use AI-driven workflows to eliminate up to 70% of manual work, without sacrificing what matters most in enterprise insurance—governance, auditability, and human-in-the-loop control. The reality: work still arrives in non-digital form Bobbie highlights a truth most transformation programs underestimate: not everything entering an insurer is digital. Documents still arrive by mail. Emails still carry unstructured attachments. Teams still manually extract information and route it to the right place. Solvrays starts there—capturing and extracting data from manual sources and pushing it into case management systems. That single shift can eliminate 5–7 touchpoints immediately, reducing handoffs, errors, and time lost to “administrivia.” From “assistants” to agents that move work forward A standout example: when a new business application arrives via email, Solvrays can detect it, extract the right data, classify it correctly, and integrate it directly into the new business workflow. What used to take a person checking inboxes, keying data, and nudging systems forward becomes an automated, governed flow—freeing teams to focus on decisions, not data entry. Legacy is everywhere (and customers don’t care) Bobbie notes that 74% of the industry is still tackling legacy systems—and yet customers expect seamless service regardless of what’s running behind the curtain. Solvrays uses agentic AI as a connector across environments: legacy systems database-to-database integrations modern platforms via APIs The message to enterprise leaders is clear: modernization doesn’t always require ripping everything out. Sometimes the fastest path is orchestration that works with reality. Speed matters — but only when risk is respected Bobbie tackles the biggest anxiety point in transformation: implementation. It can drain IT and ops teams and stall momentum. Solvrays’ promise is confident: after signing, their goal is to deliver one workflow in two weeks, not months. Fast value creation—without cutting corners on compliance, change management, or control. Why this matters now This episode is essential for insurers facing: operational overload rising cost pressure retiring talent and knowledge gaps slow transformation cycles that don’t match business urgency Bobbie’s message is a hopeful one: AI doesn’t have to create fear in operations. Done right, it becomes an engine for stability, scalability, and relief. Because the future of insurance isn’t just digital. It’s governed automation that actually works in the real world.

Transcribed - Published: 8 October 2025

On this episode of Scouting For Growth, Sabine VdL speaks with Amit Santhirasenan, Co-Founder and CEO of hyperexponential (hx) — an actuary, software engineer, and one of the sharpest minds shaping the future of specialty insurance. If you lead underwriting, pricing, or portfolio performance, this episode is your wake-up call: agentic underwriting is no longer theoretical. It’s operational — right now. The underwriting problem nobody wants to admit Specialty carriers sit at the heart of global commerce — yet underwriting still runs on messy submissions, fragmented data, and spreadsheet-heavy workflows. Amit captures the shift perfectly: early in his career, getting submissions by email felt like a luxury. Today, the real challenge isn’t access to information… It’s making that information usable, trustworthy, and fast. Because a pricing model is only as good as the data you feed it. And “garbage in” still produces “garbage out” — just at machine speed. From messy inputs to structured signals (without hiring an army) Amit explains how hx helps turn unstructured submissions into structured signals underwriting teams can actually trust — without adding headcount. This is where agentic AI becomes game-changing: instead of expecting humans to manually pull, clean, and interpret data across sources, you can deploy digital agents to do the heavy lifting at scale — consistently, quickly, and audibly. Amit’s point is blunt (and brilliant): why shouldn’t every underwriter have deep risk research on every single risk? Why should differentiation be reserved only for the biggest accounts? No human team can justify that cost-benefit tradeoff. But AI can. With the right architecture, you can run deep risk analysis on every submission, extracting key exposures and producing insights that elevate underwriting quality across the board. Multi-agent architecture: the “agentic mesh” Sabine and Amit dig into what’s powering this shift: multi-agent systems and the agentic AI mesh — specialized agents working together across tasks like extraction, enrichment, evaluation, and decision support. But this episode isn’t “automation for automation’s sake.” Amit is clear that executives need two things to scale safely: human-in-the-loop controls auditability you can defend Speed only matters if you can explain why you moved fast. Where agentic underwriting is ready (and where it isn’t) Amit offers a practical view: agentic workflows are already strong at accelerating early triage and decisioning — including rapid red/amber/green risk status at a scale humans could never match. But he also highlights the importance of knowing where autonomy should stop, and where expert judgment still must lead. The future is not “AI replaces underwriters.” It’s: great underwriters + an army of digital partners. What executives should track: three metrics that matter To move from AI pilots to measurable performance, Amit points leaders to clear outcomes: Cycle time (submission to bind) Hit ratio (wins vs quotes) Loss ratio uplift (better selection & pricing discipline) hx’s results are hard to ignore: faster submission-to-bind, dramatically faster model deployment, and real-world scale supporting tens of billions in premium. The bigger message AI capabilities are moving so quickly that what felt like a full product six months ago is now embedded inside foundation models. That’s why the question isn’t “should we adopt agentic underwriting?” It’s: how fast can we operationalize it — safely and competitively? Because in specialty insurance, speed is a weapon… but disciplined intelligence is the advantage.

Transcribed - Published: 1 October 2025

On this episode of Scouting For Growth, Sabine VdL sits down with Will Ross, Co-Founder & CEO of Federato, for a straight-talking conversation every underwriting transformation leader needs right now. If you’re drowning in Excel sprawl, stalled “innovation pilots,” and disconnected data sources, this episode delivers what most AI conversations don’t: clarity, practicality, and measurable outcomes. Will isn’t here to sell hype. He’s here to explain what AI looks like when it actually works—helping carriers quote faster, decide smarter, and give underwriters their time (and sanity) back. From AI “Wild West” to enterprise reality Will reflects on the early days of AI—when Alexa first launched and curious tech minds took devices apart just to understand what was inside. Back then, AI felt like the Wild West. Today, it’s mainstream. Any computer science student has exposure to it, and AI capabilities that used to require heavy resources are now accessible at scale. That shift matters because it’s changed what’s possible for insurers—not someday, now. What “AI” actually means (and why definitions matter) One of the most useful parts of this episode is Will’s breakdown of AI in plain English: Artificial = doing something in place of a human Intelligence = grasping knowledge or concepts Then you have different “modes” of AI: Predictive AI (predicting outcomes) Generative AI (creating content) Agentic AI (taking action and completing tasks) For enterprise leaders, this matters because too many initiatives fail at the starting line: teams buy tools before they’ve defined what type of AI they actually need. Underwriting isn’t broken — it’s bottlenecked Will reframes underwriting work in a way executives will recognize instantly. Across most commercial lines, underwriters follow a repeatable process: assess exposures, loss history, and controls, then arrive at a rate perspective. The real question isn’t whether underwriters know how to underwrite. It’s: what could they do if they had unlimited time? This is where AI becomes a force multiplier—supporting risk analysis, surfacing signals faster, and removing manual grind so underwriters can focus on judgment and deal quality. The mindset shift leaders must drive Will addresses the uncomfortable truth: jobs will change. But the real risk isn’t “AI replacing people.” It’s people using AI replacing people who don’t. That’s not fearmongering—it’s competitive reality. And Will makes an equally important point: most people are already using these tools at work, whether leadership has sanctioned them or not. The most effective move? Bring AI into the room. Let teams interact with it. Build awareness and confidence through real use—not policy documents. The caution: speed without discernment creates risk Will also flags a growing concern: AI can accelerate misinformation and amplify news cycles faster than ever. That’s a warning for insurers where trust, accuracy, and decision accountability are non-negotiable. Why this episode matters This episode is a call to action for underwriting and transformation leaders: stop chasing AI theater and start building underwriting advantage. Because the future carrier winner won’t be the one with the biggest tech stack. It will be the one that helps underwriters make better decisions, faster—with proof on the scoreboard before the next board meeting.

Transcribed - Published: 24 September 2025

On this episode of Scouting For Growth, Sabine VdL sits down with Sara Mikulski, CTO at Kingstone Insurance, to unpack a transformation story every insurer needs to hear right now: how to rebuild the claims ecosystem around one trusted data spine—and why that foundation matters more than any AI tool you buy next quarter. This is a masterclass in modern insurance tech leadership: pragmatic, human-centered, and relentlessly focused on long-term scalability. The starting point: stabilize first, transform second Sara opens with a refreshingly honest truth: when she began, “success” didn’t mean ripping everything out and launching something shiny. It meant stabilisation—understanding which systems did what, where the data lived, and how to make it work without blowing up the organization. She spent the first 18 months learning what was working, what wasn’t, and what the business was actually ready for. Not because she lacked ambition—because she understood something many transformation programs forget: Disruption without readiness creates resistance, not results. One platform. Clean data. Happier adjusters. From that baseline, Kingstone made a major shift: upgrading the platform and putting processes and data discipline at the center. The goal wasn’t “more technology.” It was better operations: clean, reliable data in the right place processes that people actually understand systems that are easier to maintain and administer And the payoff was immediate and human: adjusters were happier, and IT could finally support the business without constant workarounds. Because when data is trusted and accessible, automation becomes possible—and AI becomes realistic. The AI lesson: don’t run before you can walk Sara delivers one of the most valuable takeaways in the episode: big AI initiatives tied to core systems don’t always go as planned. And sometimes what looks like an “AI problem” is actually a workflow problem. She explains how, by slowing down and dissecting processes, her team often discovered they didn’t need a moonshot. They needed a smart tweak—something that improved usability, reduced friction, and made life easier for the people doing the work. That approach also led to better decisions with less emotion attached—because they were grounded in clarity, not urgency. Efficiency is the driver — but fundamentals are the multiplier Sara acknowledges why AI is surging: efficiency is king. Every insurer wants to take tasks that consume hours and compress them into seconds. But her warning is sharp: if your foundation is weak, AI becomes a band-aid, not a solution. AI will absolutely shape insurance operations— but only if the basics are right first. That’s why the “single trusted place” matters. Build the spine. Make the data clean and true. Identify what adjusters still need to leave the system to find—and fix it. Why enterprise leaders should listen For COOs, CIOs, CTOs, and claims leaders, this episode is a blueprint for sustainable transformation: stabilize before you accelerate standardize data before you automate earn trust before you introduce AI at scale Because the future of claims isn’t just faster workflows. It’s a trusted system of record that lets people—and AI—make better decisions with confidence.

Transcribed - Published: 17 September 2025

On this episode of Scouting For Growth, Sabine VdL sits down with Arvind Sontha, Co-Founder (and CEO) of Kyber, an AI startup redefining one of the most overlooked levers of claims performance: correspondence. Because while the industry loves to talk about AI in underwriting and fraud… the moment of truth for customers often comes down to something far simpler: The letter. The wording. The timing. The clarity. And right now, carriers are under mounting pressure to deliver communications that are not only faster and more transparent—but also compliant across 50 states. That’s why claims transformation isn’t optional anymore. It’s survival. From “cool AI” to real insurance execution Arvind’s journey is a classic founder moment: he knew he could build complex AI systems to quantify risk. The bigger question was whether he could operate inside the real-world machine of insurance. So he did what few founders do: he got his broker’s licence. Not for optics—because credibility in insurance isn’t earned through demos. It’s earned through fluency in regulation, workflow, and distribution. The pain point hiding in calendars One of the most powerful insights in this episode has nothing to do with technology—and everything to do with time. Arvind explains the real cost of claims letters: if an adjuster needs an hour to draft a document, they don’t need an hour. They need a 1.5-hour calendar block—because context switching is real, interruptions are constant, and the work keeps getting pushed. Multiply that across adjusters, managers, reviews, approvals… and the result is slow communication, higher cycle times, and frustrated policyholders. Kyber changes the game by taking that process from 1.5 hours to 30 seconds: high-quality letter generation one-click approval faster delivery to the customer And that “slip it into any part of your day” advantage? It’s underrated—and massively impactful. Kyber’s model: AI-native document generation for claims Kyber is built as an AI-native document generation and delivery platform made for claims teams. It automates drafting, standardizes language, and reduces the chaos of template sprawl—especially in large, multi-state operations. Arvind shares results that make enterprise leaders lean in: 65% faster drafting times 80% template consolidation across a 50-state operation 5x reduction in letter cycle times That’s not incremental efficiency. That’s operational lift you feel immediately—in cost, speed, and customer trust. The future: compliance as a shared advantage Kyber’s next frontier is just as strategic: managed parameters for statutory and fraud language. Arvind’s point is simple: it’s inefficient for every carrier to reinvent compliance wording repeatedly. If platforms can manage standard language updates intelligently, insurers reduce risk, increase consistency, and improve governance without adding friction. In a world where regulation is complex and scrutiny is rising, this approach turns compliance into a scalable asset—not a bottleneck. Why this matters now This episode is a must-listen for claims leaders, COOs, and transformation executives who want real AI impact without turning operations upside down. Because speed matters. Compliance matters. Trust matters. And in claims, trust is built in the moments customers actually experience: What you say. How fast you say it. And whether it holds up when it matters most.

Transcribed - Published: 10 September 2025

On this episode of Scouting For Growth, Sabine VdL sits down with Charlie Wendland, Chief Claims Officer at Branch Insurance, to explore what happens when claims transformation is driven by the people closest to the work — and powered by AI without losing the one thing insurance can’t afford to break: trust. Claims is in the middle of a seismic shift. Insurers leveraging AI are seeing dramatic improvements—faster handling times, stronger fraud detection, and lower operational drag. But Charlie makes it clear: technology is only part of the story. The real future of claims is about continuous transformation, balancing innovation with compliance, and keeping empathy at the center of the customer experience. Why claims matters (and why Charlie stayed) Charlie shares what drew him into claims in the first place: it’s the combination of investigation, problem solving, and being there for people in their worst moments. It’s intellectually engaging—and deeply meaningful. That human truth becomes the anchor for everything Branch is building. Automate the admin… elevate the adjuster Branch is small, so Charlie and his team couldn’t afford to build a massive, traditional claims organization. Instead, they made strategic investments to remove the work that slows adjusters down the most: administrative tasks that drain time, drive expense, and delay outcomes. But here’s the difference: they didn’t guess. They listened to adjusters. They ran time studies. They identified exactly what was bogging teams down—and then targeted those inefficiencies with technology. Charlie’s takeaway is simple and powerful: Free adjusters from admin, and they’ll spend more time on complex decisions and customer care. Iteration is the operating model Branch has taken an iterative approach to everything: launch, learn, refine. Charlie doesn’t chase perfection on day one—he chases improvement fast, while staying hyper-aware of what isn’t working and fixing it. That’s startup discipline applied to an enterprise-grade responsibility: people’s lives and losses. Real AI adoption in action Branch’s progress shows what practical AI adoption looks like in claims operations. Charlie shares a standout metric: 70% of Branch’s first notice of loss is now handled electronically or through voice AI. That’s not innovation theater—that’s real operational shift that reduces friction for customers and gives claims professionals more time for high-value work. Change is constant — communication is everything Charlie also offers a leadership truth that resonates far beyond claims: in a startup environment, change is ever-present. The biggest obstacles aren’t always external—they’re often self-inflicted. If communication isn’t clear, adoption slows. If people aren’t brought along, transformation stalls. That’s why Branch involves adjusters in most decisions. It may sound inefficient, but Charlie frames it as the opposite: done thoughtfully, it accelerates buy-in, improves outcomes, and reduces downstream resistance. Why this episode matters For insurance leaders, this conversation is a blueprint for modern claims transformation: target admin drag first use AI to compress time, not cut empathy iterate relentlessly keep compliance and trust non-negotiable build with adjusters, not around them Because the future of claims isn’t just faster. It’s smarter, more human, and designed to help people when it matters most.

Transcribed - Published: 3 September 2025

On this episode of Scouting For Growth, Sabine VdL speaks with Barbara Schonhofer and Carmen Powell — two influential voices who have not only survived the insurance industry’s evolution, but helped shape it. This is a conversation about resilience, reinvention, and relationships—and why the future of work in insurance will reward the people who keep learning, keep connecting, and keep showing up with courage (and a little humour). Breaking in when the room wasn’t built for you Barbara reflects on starting her career in 1972, at a time when women stepping into frontline business roles were still an unfamiliar sight. Her experience wasn’t defined by constant hostility—more by men who simply didn’t know how to behave when women began taking space in business. Her strategy? Be sharper, stay composed, and use humour as a shield and a tool. She navigated the awkwardness, sidestepped the banter, and built credibility through performance. Carmen adds her own perspective on what it takes to thrive inside complex organisations: she learned early to celebrate being different. As a Spaniard in international markets, she turned her “idiosyncrasies” into an advantage—giving herself permission not to follow outdated norms. And when faced with the kind of question too many women still recognise—how to handle men crossing boundaries—her response was direct: she came to work, and she knew how to deal with anyone who crossed the line. A leadership lesson with bite: “keep your enemies closer” One of the most memorable insights in this episode is Barbara’s reframing of mentorship and career growth: The men who were kindest didn’t necessarily help her. The ones who challenged her often did business with her. It’s a sharp reminder that comfort doesn’t always equal opportunity. Growth often comes from friction—handled with intelligence and boundaries. Carmen echoes the theme: some of her toughest bosses pushed her limits, but that pressure became proof of her resilience. Progress, as she puts it, is rarely linear. Two steps forward. One step back. Repeat. The future of work: networks will be your career infrastructure Beyond personal stories, this episode is a masterclass in what builds longevity in insurance: relationships, reputation, and continuous development. Barbara’s work as a business leader and later an executive search consultant gave her a front-row seat to culture change in the London Market. She spotted early what many underestimated: women needed trusted spaces to connect, learn, and build power through community. That instinct led her to help create and support networks that drive real inclusion and progress across the market, including initiatives focused on female leadership and neurodiversity. Carmen brings the commercial lens: navigating complex matrices, establishing new markets, reversing declining revenue—and doing it with a strong ethical compass. Her message is clear: results matter, but how you achieve them matters too. Why this episode matters now For enterprise leaders and rising talent alike, this episode is a timely reminder that insurance is changing—but some success principles remain timeless: resilience is built through experience, not titles humour can be a strategy, not a distraction ethics are a differentiator networks create opportunity before you “need” them and career growth is still a contact sport In a sector reinventing itself through technology, regulation, and workforce shifts, Barbara and Carmen show what enduring leadership looks like: Stay sharp, stay human, and keep building the relationships that will outlast the change.

Transcribed - Published: 2 September 2025

On this episode of Scouting For Growth, Sabine VdL sits down with Yandy Plasencia, Founder and CEO of DataHaven Software, to tackle a challenge that quietly keeps CFOs awake at night: How do you run a modern insurance business when your financial truth is trapped across systems, spreadsheets, and “only Susan knows how this works” dashboards? This episode is a must-listen for mid-sized carriers, finance leaders, and transformation teams who want faster close cycles, cleaner reporting, and real-time visibility—without ripping out core systems. The problem: the ledger vs sub-ledger reality Yandy breaks down the root issue with sharp clarity: most insurance core systems are transactional. They capture everything—claims, payments, coverage decisions, timing, policy rules. But just because the data exists doesn’t mean it’s usable. If it can’t be extracted and made digestible for the right audience (especially finance), reconciliation becomes slow, painful, and error-prone. That’s where the classic insurance tension emerges: technology teams can move data around… but it often doesn’t arrive in a form that finance teams can actually trust and act on. The hidden friction in mid-sized carriers In smaller and mid-sized insurers, Yandy observes a common pattern: highly technical teams running infrastructure, and business teams trying to manage results. That gap creates constant friction—especially between IT and finance. And the CFO is stuck in the middle, expected to deliver fast insight with slow tools. The fix: an insurance-specific intelligence layer Yandy’s solution is not “another spreadsheet.” It’s building an intelligence layer that defines clear relationships across every data point that touches financials. He emphasizes the importance of an ontology—meaning the system understands how pieces connect: If it affects financials, it must have a relationship model behind it. Without that framework, you’re not solving the problem. You’re just postponing the next crisis. Why spreadsheets and dashboards stop scaling Yandy doesn’t attack spreadsheets because they’re useless. He attacks them because they’re dangerous at scale. Visualisation tools often solve the problem—until they don’t. As datasets grow and organizations expand, they become: bottlenecks change-management nightmares and a huge personnel risk (when only 1–2 people understand the logic) That’s not “agile.” That’s operational debt with a prettier interface. The CFO advantage: traceability and real-time clarity One of the strongest takeaways from the episode is the power of traceability: being able to trace an expense back to the source system and see full transactional detail is the most reliable way to reconcile and act. This is where automation and AI become a strategic edge. Yandy makes the point: reconciliation is only labour-intensive if you do it manually—or without a defined framework. With the right structure, AI can automate the grunt work and unlock real-time insight. And his closing line is as bold as it is true: It’s not rocket science. It’s just data science. Why this episode matters now For insurance executives, this conversation is a roadmap for building finance agility without destabilizing operations. Because in insurance, “the devil is in the details”—and the companies that win won’t be the ones with the loudest dashboards. They’ll be the ones with the cleanest financial truth, fastest reconciliation, and the ability to explain performance in real time—before the board asks twice.

Transcribed - Published: 21 August 2025

On this episode of Scouting For Growth, Sabine VdL sits down with Mike Gulla, CEO and Co-Founder of Adaptive Insurance, to explore what resilience really means when climate risk is rising, systems are strained, and business disruption is no longer a “rare event.” Mike founded Adaptive in early 2024 with a clear mission: help businesses build financial resilience against climate uncertainty using parametric and adaptive insurance, powered by unique data assets and modern technology. Why parametric, why now? Traditional insurance was built for a world that moved slower. But climate volatility doesn’t wait for claims adjusters, inspections, or long settlement cycles. Mike makes the case that speed is becoming the defining advantage in protection. Parametric insurance is designed for exactly that: fast decision-making after an event occurs. Instead of lengthy claims processes, payouts can be triggered by predefined conditions—helping business owners respond quickly when it matters most. As Mike puts it: when you combine knowledge with speed, you help leaders make better decisions. The real problem isn’t just risk — it’s visibility One of the strongest takeaways is that many business owners don’t fully understand what environmental risks will impact them over time. Starting and running a business already comes with enough complexity: revenue planning, product selection, hiring, operations. Insurance is often an afterthought—until it’s not. Adaptive’s focus is helping owners see how factors like extreme weather, outages, and business interruption can affect them long before the next disruption hits. Operational disruption is the new normal Mike highlights how power outages reveal the fragility of business infrastructure. Even with backup systems, grid failures ripple into real-world impact: darker streets, reduced foot traffic, disrupted services, and lost revenue. That’s the kind of disruption that doesn’t just hurt operations—it changes customer behavior. A shifting climate is shifting populations (and exposure) As climate patterns evolve, people and businesses are moving into areas with new or unfamiliar weather risks. Mike sees this as both a challenge and an opportunity: to design products that match reality, close protection gaps, and create positive outcomes for communities. Parametric as “insurance on demand” Mike offers a useful analogy: parametric coverage is like a streaming service—opening the door to a new way of accessing protection that’s more targeted, flexible, and aligned with what actually threatens a business. Not more paperwork. More relevance. Why this episode matters For insurers, brokers, and enterprise leaders, this conversation is a glimpse into where the market is heading: faster protection, data-driven product design, and resilience as the core value proposition. Because the question is no longer whether disruption will happen. It’s whether your business can absorb it—and keep moving.

Transcribed - Published: 13 August 2025

On this episode of Scouting For Growth, Sabine VdL speaks with Sterling Parker, SVP of Global Solutions & Services at Ivanti, to unpack a leadership challenge that’s quietly reshaping every enterprise operating model: Flexibility is now a talent requirement… but most workplaces still treat it like a perk. Sterling brings insights from Ivanti’s latest Technology at Work report, revealing why the future-ready workplace won’t be built by chasing productivity alone — it will be built by designing work that’s efficient, human, and sustainable. The flexibility gap leaders can’t ignore The report uncovers a striking disconnect: 73% of office workers and 83% of IT professionals say flexible working is high value or essential but only 23% of employees describe their current job as highly flexible That gap isn’t just a culture issue — it’s a competitive one. Because when flexibility expectations rise and workplace reality doesn’t, talent doesn’t “wait it out.” They leave. And when top talent exits (or never joins), innovation slows. Sterling calls it out clearly: losing talent creates innovation stagnation—and the cost compounds fast. Flexibility isn’t free — but inflexibility is expensive Sterling highlights something leaders often underestimate: employees calculate flexibility in real-life terms. There’s a cost in commuting. A cost in time away from family. A cost in burnout. Post-COVID, people are simply more willing to switch employers to regain control over their time. Refusing to adapt doesn’t preserve performance — it increases attrition risk. Listening is the strategy A key message in this episode: don’t design flexibility from the boardroom. Sterling stresses that leaders must hear directly from teams what’s blocking flexibility — whether it’s perception, policy, or workflow reality. Without that feedback loop, it becomes almost impossible to align employee demand with business objectives. Flexibility is not “one-size-fits-all.” It’s negotiated at the team level, shaped by goals, responsibilities, and trust. Define success or you can’t scale flexibility Sterling also offers a practical leadership test: if you haven’t defined what success looks like for an individual, how will you measure whether flexible work is producing outcomes worth continuing to invest in? This is where flexibility becomes operational — not ideological. Clear expectations + measurable outcomes = flexibility that works for both the business and the employee. The shadow AI warning The report also points to the rise of shadow AI—tools employees adopt without formal governance, often to move faster and work smarter in environments that aren’t meeting their needs. That’s both an opportunity and a risk: opportunity, because teams are hungry for efficiency risk, because unmanaged AI introduces security and compliance exposure Why this episode matters For enterprise leaders — especially in highly regulated sectors like insurance and financial services — this episode is a wake-up call: The workplace isn’t just competing on salary anymore. It’s competing on time, autonomy, and trust. Because the future of work won’t be won by the companies that demand presence. It will be won by the ones that build workplaces people don’t want to escape from.

Transcribed - Published: 6 August 2025

On this episode of Scouting For Growth, Sabine VdL sits down with Sam White, CEO of Stella Insurance — a founder who’s not just building a business, but challenging the culture of an industry that still too often feels like it was designed by men, for men. Sam is a trailblazer with a sharp commercial edge and a big mission: create a fairer, more inclusive version of insurance — one that actually reflects the needs, risks, and realities of women. Stella didn’t set out to be “revolutionary”… and then it was Sam reflects on the early days of building Stella: an entirely female management team, mostly in their 20s and 30s, stepping into a marketplace dominated by older male incumbents. At the time, they didn’t realise how radical that would seem. But the impact was real. Sam speaks candidly about gender differences in business — not as stereotypes, but as lived reality. Women often approach relationships, risk, and decision-making differently. And insurance, by definition, is about vulnerability, protection, and trust — areas where women’s experiences and needs are too often underrepresented. Insurance is a community model — and that matters One of the most powerful parts of the episode is Sam’s lens on the purpose of insurance itself: A group of people contribute to a shared pot, so that when one person is vulnerable, they’re supported. That “community ideology” is what draws her to the industry — and she believes that when women align around a shared goal and support each other, something close to magic happens. It’s not just about policies. It’s about belonging. Bootstrapping teaches you fast (even if it’s messy) Sam’s first business started in the most founder way possible: from her sister’s conservatory, picking up the phone and asking brokers if she could handle their claims. The upside? You don’t need funding. You can build your way. You learn fast through direct feedback. The downside? The foundations aren’t always perfect — but the momentum is priceless. This is entrepreneurship in its rawest form: imperfect starts, relentless learning, and building confidence through action. Leadership, self-awareness, and the relationships that shape success Sam also shares an insight that goes beyond business: you can’t build a great relationship with someone who doesn’t have a solid relationship with themselves. For leaders, that’s a reminder that emotional maturity is a strategy — not a soft skill. Resilience, dyslexia, and doing the first hard thing Sam speaks openly about being diagnosed with dyslexia as a child, and how it shaped her mindset: resilient, creative, and wired for problem-solving. And she delivers one of the most honest leadership truths in the episode: confidence doesn’t arrive before the work. It’s built through the work. Especially for women, she notes, imposter syndrome can run high — reinforced by social conditioning and constant second-guessing. The way through it isn’t waiting to feel ready. It’s doing the first hard thing… and surviving it. Why this episode matters For enterprise leaders, founders, and anyone building in insurance, this episode is a powerful reminder: Innovation isn’t only technology. Sometimes, the most disruptive thing you can do is build a company with a different worldview — and prove it performs. Because the future of insurance won’t be shaped by louder voices. It’ll be shaped by leaders like Sam, who build trust, rewrite norms, and make protection work for everyone.

Transcribed - Published: 30 July 2025

On this episode of Scouting For Growth, Sabine VdL sits down with Amélie Breitburd, former CEO of Lloyd’s Europe and one of the most compelling voices pushing the industry to rethink how we insure the risks we’d rather not talk about. From climate and cyber to long-tail systemic shocks, Amélie brings a bold message: the future of insurance won’t be won by avoiding uncertainty — it will be won by designing new ways to share it. Insurance isn’t a product. It’s an enabler of civilisation. Amélie reminds us why insurance exists in the first place: people wouldn’t take a bike ride, drive a car — let alone “fly to Mars” — without protection. Insurance is a fundamental enabler of progress, innovation, and risk-taking. And for leaders in the industry, that means purpose isn’t optional. It’s the job. Diversification is the real superpower One of the sharpest insights in this episode is Amélie’s view on capital efficiency: risk is at the heart of insurance, and risk management is fundamentally about diversification. She points out that syndicates operating only in the US could expand into Europe with minimal additional capital impact—because diversification reduces concentration risk and can lower the cost of capital. The statistical power of pooling risks is what makes insurance affordable at scale. In short: together, we take risk better. From “buying” to partnerships: the era has changed Amélie also highlights a shift that founders and enterprise leaders should pay attention to: the industry is moving from a “we’ll buy it” mindset to a true partnership era. Why does that matter? Because partnerships allow startups to work with multiple carriers, increase diversity of learning, and spread innovation faster across the ecosystem — without burning teams out through endless acquisition cycles. The data problem: yesterday’s risk doesn’t model tomorrow’s world Insurers have mountains of data… but much of it is becoming outdated. Amélie explains why: as industries evolve, the nature of risk changes. In motor, for example, we’re moving toward autonomous vehicles—meaning driver behaviour becomes less important, while software integrity and battery performance become critical. Then there are frontier risks where we have no historical dataset at all: carbon capture, space travel, emerging technologies. The conclusion is uncomfortable but undeniable: We can’t insure tomorrow’s risks with yesterday’s data. Coopetition: the strategy to unlock the inaccessible market Perhaps the most provocative idea in this episode is Amélie’s call for “coopetition”—competitors working together to unlock markets that are currently uninsurable or unaffordable. By collaborating on shared infrastructure, smarter pricing, and diversified capacity, insurers can open access to protection for more people and businesses. That’s how you close the protection gap—not by competing harder, but by building smarter together. The next evolution: from PDFs to true digital exchange Amélie describes today’s transformation as “moving from paper to PDF.” Necessary, but not revolutionary. The next wave is bigger: fully digitalised exchanges across the value chain, with better access to data, distributed underwriting, and multi-layer diversification—captured in her vision for next-gen insurance infrastructure like Euro DIEM. Why this episode matters For executives, founders, and market shapers, this conversation is a blueprint for the next era of insurance: diversify to lower capital strain partner to move faster modernise data to match emerging risks collaborate to unlock inaccessible markets Because the future of insurance won’t be defined by who plays it safest. It will be defined by who dares to build the systems that let society take the next leap.

Transcribed - Published: 23 July 2025

On this episode of Scouting For Growth, Sabine VdL speaks with Geetha Sham, MD & President of CamCom Europe, and Sathes Singam, Innovation Scout & Programme Manager at ERGO Group, to unpack what most insurers struggle to do: turn an AI pilot into production—across multiple countries, regulations, and realities. This isn’t a story about “innovation theatre.” It’s about execution. And it’s proof that when governance is done right, it doesn’t slow progress… it accelerates growth. The problem: inspections were slow, inconsistent, and expensive CamCom’s entry point was a pain every claims leader recognises: vehicle inspections are time-consuming, labour-intensive, and prone to human fatigue. That leads to long cycle times, inconsistent assessments, and avoidable cost. Their AI solves that with a “machine vision eye”—enabling mobile devices to capture accurate images and support faster damage assessment, while reducing false positives. In simple terms: better evidence, faster decisions, cleaner outcomes. Democratise capture. Don’t overcomplicate scale. Geetha shares one of the smartest scale strategies in the episode: CamCom designed its technology to work on any form factor and on mobile devices made since 2016. That matters for insurers operating across different markets, device policies, and distribution models. It removes friction at the edge—where adoption is won or lost. And CamCom stays disciplined: focus on doing one thing exceptionally well, rather than scattering attention in the name of “doing everything.” Multi-market AI is not copy-paste. It’s localisation + trust. Sathes brings the enterprise reality: deploying AI across borders isn’t just customisation—it’s localisation. Every country has different laws, operational nuance, and stakeholder expectations. That’s why governance becomes essential. Not as bureaucracy, but as a structure for: compliance consistency transparency and controlled learning loops (especially for edge cases) A powerful theme emerges: you can’t deploy AI safely without designing how it behaves when the unusual happens. The Venture Client model: why this worked This episode highlights ERGO’s Venture Client approach—working closely with startups as partners, not vendors. It’s what turned a promising pilot into production capability. Geetha and Sathes emphasize that startup collaboration should be on the management agenda—because scale requires sponsorship, alignment, and decisions that cut through inertia. The real unlock: stakeholder orchestration Both guests reinforce the same truth: success comes from involving everyone early. Engineers, claims teams, compliance, legal, local business owners—aligned through clear and transparent communication. And critically: local insight matters. Having someone who understands the culture, the stakeholders, and how decisions actually get made in-country is often the difference between progress and paralysis. Why this episode matters For insurers and enterprise leaders, this conversation is a blueprint for AI deployment in regulated environments: solve a real operational bottleneck design for adoption at the edge localise for multi-market reality govern learning loops intentionally treat startups as partners, not add-ons Because the winners in AI won’t be the ones with the most pilots. They’ll be the ones who can take a great idea… and ship it into production across the real world.

Transcribed - Published: 16 July 2025

On this episode of Scouting For Growth, Sabine VdL sits down with Joel Agard, Group Head of Innovation at Zurich Insurance, the leader behind one of the most effective corporate-startup engines in the insurance industry — driving partnerships and pilots across 40+ markets. This is not an episode about “cool tech.” It’s an episode about how a 150-year-old giant learns to move at startup speed — without breaking trust, compliance, or the business. The origin story: a World Cup idea that became a global innovation engine Joel shares the spark that launched Zurich’s now-famous Innovation Championship: the 2018 football World Cup. At the time, working with startups in insurance wasn’t the default. Zurich, like many large organisations, was partnering mostly with big technology providers. Joel and his team asked a simple but powerful question: How do we show the art of the possible — and prove startup collaboration can actually work? That’s when they created the Zurich Innovation World Championship: a structured “competition-style” platform to raise awareness, attract high-quality ventures, and build a repeatable process for corporate-startup engagement. The hardest part: aligning pace, expectations, and risk appetite Joel is candid about the early friction: startups move fast because they have to. Zurich moves carefully because it must. The challenge wasn’t capability — it was tempo. So the breakthrough wasn’t a new tool. It was designing a safe environment where Zurich teams could: test quickly learn fast and accept that “failure” is part of innovation — if it’s cheap, fast, and controlled The lesson every enterprise needs: shiny tech isn’t the point Joel admits something many innovation leaders won’t say out loud: it’s easy to fall in love with exciting technology. He’s a self-described geek — and proudly so. But Zurich learned the hard way that even brilliant tech isn’t valuable if it doesn’t solve a real problem for customers or internal stakeholders. Sometimes it’s simply too early. Sometimes it’s not a fit. Innovation isn’t about what’s possible. It’s about what’s useful. Making “fail fast” real inside a big corporation One of the most important cultural wins Joel describes: shifting the perception of failure. In large organisations, failure often comes with fear, reputation risk, and internal resistance. Zurich proved that failing fast and cheaply isn’t reckless — it’s responsible innovation. And once teams see it working, experimentation becomes normal rather than dangerous. COVID accelerated everything — including startup pilots Like many organisations, Zurich used the pandemic moment as an accelerator. With digital transformation suddenly urgent, the team increased startup pilots and expanded opportunities to move initiatives forward faster than the old playbook would ever allow. Why Zurich wins with startups: the right trade Joel sums up the partnership dynamic beautifully: Zurich brings brand, reputation, and 150 years of insurance expertise. Startups bring agility, speed, and digital-native execution. When done well, it’s not vendor procurement — it’s a strategic partnership where both sides multiply each other. Why this episode matters For enterprise leaders, founders, and innovation teams, this episode is a blueprint for venture-client success: build a repeatable engagement model (not one-off pilots) align expectations on pace and risk early create safe environments for fast experimentation obsess over real business problems, not shiny technology treat “fail fast” as a discipline, not a slogan Because innovation isn’t about showing off. It’s about building partnerships that actually deliver results — market by market, pilot by pilot, win by win.

Transcribed - Published: 9 July 2025

On this episode of Scouting For Growth, Sabine VdL sits down with Gregor Gimmy, founder of 27pilots and the visionary behind the Venture Client Model — the approach that’s rapidly redefining corporate innovation by helping enterprises adopt startup technology faster, at scale, and at significantly lower cost and risk than traditional venture capital. If you’ve ever watched a corporate innovation program move at the speed of a committee meeting… this episode is your escape route. The BMW wake-up call: CVC can’t scale to what corporates actually need Gregor takes us back to 2012, when he joined BMW and realised something shocking: despite the scale of BMW’s technology needs across the value chain, the company was only leveraging a small number of startups. He points out that Corporate Venture Capital funds typically invest in an average of 2.8 startups per year. That’s fine if your job is to invest. It’s useless if your job is to modernise a global business. Gregor’s argument was simple: if a company wants to solve real technology challenges, it doesn’t need three startups. It needs closer to a hundred. Investment ≠ technology transfer The breakthrough insight is one every executive should write on a whiteboard: VC is not a technology transfer process. It’s an investment process. BMW was told that investing in 50 startups per year would create a portfolio nightmare: within five years, they’d be managing equity stakes in 250 startups. Not scalable. Not realistic. And not aligned with the goal of rapid technology adoption. That’s when Gregor realised the core problem: CVC isn’t built to help corporations access and adopt cutting-edge tech at operational speed. It’s built to make bets. The Venture Client Model: cut out the middleman Gregor compares accelerators and CVC models to something indirect: like using someone else’s battery technology — but only after you’ve invested first. The Venture Client approach cuts through that logic. Instead of investing first and hoping adoption follows, a Venture Client simply buys the technology — directly, early, and intentionally — through procurement (and sometimes M&A when appropriate). It’s corporate innovation with one defining feature: value now, not maybe later. Why venture clienting needs a dedicated unit (not a side hustle) Gregor also makes a leadership point that hits hard: if you want to be good at something, you need a dedicated unit. Innovation can’t live as a part-time hobby inside procurement, strategy, or IT. When it becomes a formal department, it gains: dedicated time dedicated budget measurable KPIs operational muscle to scale adoption That’s when it stops being “innovation theatre” and becomes a repeatable capability. A reality check: corporates don’t outbuild great startups Gregor delivers another truth that enterprise leaders often avoid saying out loud: A corporation can’t compete against a great startup when that startup is at its peak velocity — think Palantir or Oracle in their early days. The advantage corporates do have is distribution, customers, and scale. So the smartest move isn’t trying to out-startup the startups. It’s adopting the best startup tech faster than your competitors can. Why this episode matters For executives in insurance, banking, automotive, and beyond, this episode is a strategic roadmap for modern innovation: scale matters more than individual bets adoption beats investment procurement can be an innovation engine dedicated venture client units drive repeatable outcomes the fastest path to transformation is often partnership, not invention Gregor’s bold claim is clear: the Venture Client Model won’t just complement Corporate VC. It will replace it as the default standard of corporate venturing. And after this episode, it’s hard to argue otherwise.

Transcribed - Published: 2 July 2025

On this episode of Scouting For Growth, Sabine VdL launches a bold new series on one of the most practical (and underused) innovation engines in enterprise today: the Venture Client Model. Because let’s be honest — “innovation” has been oversold for years. Too many corporates invest in startups, attend demo days, publish glossy reports… and then wonder why nothing changes inside the business. The Venture Client Model flips that script. Instead of betting on startups with equity and hoping value shows up someday, corporations buy from startups and create value now. What if your next breakthrough isn’t built — but bought? Sabine asks the question that should make every executive sit up straighter: What if your company’s next breakthrough isn’t built in-house… but deployed through an early pilot with a venture-backed startup? And what if being a startup’s customer is actually more powerful than being its investor? That’s the essence of venture clienting: innovation as procurement, not prediction. What a Venture Client actually is At its core, a venture client is a corporation that becomes an early customer of a startup — buying and using its solution to gain strategic advantage. No equity stakes. No controlling shares. No waiting for an exit. Instead, the corporation gets: real product capability real business learning real speed-to-value And the startup gets: revenue feedback enterprise validation a path to scale It’s a win-win relationship built on execution, not speculation. Why insurance is the perfect testbed Insurance is traditionally conservative — heavy on compliance, high on caution, slow on adoption. And that’s exactly why venture clienting is so powerful in this sector. It creates a safe sandbox for experimentation: piloting startup solutions with structure, governance, and measurable outcomes, without the organisational risk of “big bang transformation.” Zurich’s model: no CVC, all outcomes Sabine highlights a standout example: Zurich doesn’t operate a group-level corporate VC arm. So when they engage startups, it’s typically through venture client relationships or partnerships. The result? Effort goes into tangible pilots and deployments, not minority stakes that may never align with business priorities. It’s bold — and it’s paying off. A real-world example: claims and underwriting without the friction Sabine brings the model to life with a practical case: motor insurance. Instead of physical car inspections or long claims assessments, a solution like CamCom lets customers capture a video of the vehicle while AI identifies damage (scratches, dents, cracked glass) and can even estimate repair costs. That means: faster underwriting faster claims less manual overhead a smoother customer experience This isn’t theory. It’s enterprise-ready capability delivered through venture client execution. The big shift: from “innovation tourist” to innovation magnet Sabine sums up the strategic power of the model perfectly: Instead of investing in ten startups and hoping one hits, you pay one startup to solve a problem — and benefit immediately. Over time, it turns the enterprise into an innovation magnet: the best startups want to work with you because you’re known for buying, deploying, and scaling new tech. Why this series matters This series isn’t just about strategy — it’s about how to actually make it work. By the end, Sabine promises listeners will understand the full playbook: from leadership alignment to operating model design to practical execution tips (like one-page startup contracts and killing the word “impossible”) Because the future of corporate innovation won’t belong to the companies that “monitor startups.” It will belong to the companies that buy from them — early, fast, and intelligently.

Transcribed - Published: 25 June 2025

On this episode of Scouting For Growth, Sabine VdL sits down with Lou Smith — a true trailblazer across financial services and insurance — to explore what happens when you combine data, digital distribution, culture change, and bold leadership into one clear mission: make financial services work better for real people. Lou shares her journey from pioneering digital breakthroughs to now leading Neuron, a transformative initiative focused on helping the insurance ecosystem modernise how it serves customers — with brokers at the centre. Financial data shapes lives (even when we avoid it) Lou opens with a truth most people feel in their gut: there are moments when the last thing anyone wants to look at is their credit rating or history. But that data influences how you access financial services, often long after the moment that created it. Her passion has always been about making financial services more usable and more human — translating data into narratives people can understand, trust, and act on. A career built on “firsts” Lou has consistently been ahead of the curve, from helping deliver the first end-to-end online mortgage renewal, to breaking down investment access so it reaches “the many, not the few.” Her story is a reminder that industry transformation doesn’t start with a perfect plan. It starts with curiosity, a problem worth solving, and the courage to build the future before it has a name. Insurance isn’t “behind” — it’s finally moving with intent Lou challenges the old narrative that insurance is behind other financial services. It doesn’t matter where it ranked before — what matters is what’s happening now. She’s seen a major shift in the last 12–18 months: a new urgency and energy around connecting the dots between digital, distribution models, analytics, and AI — and using them together to move the industry forward, not in silos. The real blocker isn’t tech. It’s adoption. Lou doesn’t sugarcoat it: the hardest part of transformation is always leadership, culture, and change adoption. Because stepping into the unknown is difficult — even when the future is objectively better than the present. The organisations that win will be the ones that help their people cross that gap with clarity, trust, and momentum. The broker upgrade: remove admin, elevate advice A major theme of the episode is the future of broking. Lou’s goal is to empower brokers with better data and capabilities so they can focus on what they’re brilliant at: finding the best product and positioning for the client. Neuron’s role — and the wider shift happening in the market — is to remove the administrative weight that drags brokers down, and create workflow-driven support that makes the experience faster, more consistent, and easier to trust. That’s also how the industry attracts the next generation into broking: not by offering more paperwork, but by enabling great client conversations. Why this episode matters For insurance leaders, this is a blueprint for modern distribution transformation: make data accessible through clear narratives connect digital + analytics + AI into real workflows prioritise adoption, not just deployment empower brokers to advise, not administrate and build trust through predictability and consistency Lou’s story proves the future isn’t built by people who “wait and see.” It’s built by leaders who bring the technology and the humans forward — together.

Transcribed - Published: 24 June 2025

On this episode of Scouting For Growth, Sabine VdL sits down with James Birch, Director of Strategic Technology Solutions at Ki Insurance — the first fully algorithmic syndicate in the history of Lloyd’s of London. If you want to understand what “digital underwriting” really means in specialty insurance (beyond buzzwords), this episode delivers. Ki isn’t modernising around the edges — it’s rebuilding how Lloyd’s capacity can be accessed: faster, cleaner, and in seconds. From VC mindset to algorithmic underwriting execution James brings a venture-capital lens into a regulated market: Ki isn’t an incumbent protecting market share — it’s a growth-stage challenger trying to win it. That means differentiation is survival. Ki’s advantage comes from redesigning the value chain, removing manual toil, and creating a broker experience that feels more like modern financial services than a centuries-old marketplace. “Digital Lloyd’s” starts with broker pain Ki began by asking a simple question: where is the friction in the traditional model? James explains how they mapped the broker workflow, identified the slow, repetitive parts, and used digital capabilities they’d seen in FinTech to streamline the process. The goal wasn’t to impress people with complexity — it was to make transactions simpler and faster. One of James’s biggest lessons: they still sometimes trip themselves up by overcomplicating things. The win is always simplicity. Regulation isn’t the blocker — it’s the pathway Lloyd’s is heavily regulated, and James is clear: Ki treats regulation as foundational, not a hurdle to work around. From day one, they engaged regulators early, stayed transparent about what the algorithm could and couldn’t do, and avoided overstating maturity. That openness built trust — and Lloyd’s support — allowing Ki to scale alongside the market instead of fighting it. Why brokers care: speed + less running around for 2% James highlights a practical broker benefit: algorithmic underwriting reduces the grind. Instead of brokers physically running around the Lloyd’s building to secure tiny percentages of capacity, they negotiate with the lead underwriter, then use Ki’s platform to efficiently fill the follow-on placement. That saves time, reduces friction, and frees brokers to focus on higher-value work: new business, client strategy, and advisory. Algorithmic Underwriting 2.0: partnerships + smarter data streams The episode also explores what’s shaping the next wave of algorithmic underwriting: tighter partner ecosystems, stronger cloud architecture, and richer data streams that let Ki quote in seconds — while staying aligned with market rules. James is a strong advocate for the partner model: when 2–4 strategically aligned companies build together, the ecosystem moves faster than any one player could alone. Why this episode matters For brokers, carriers, and capacity partners, this conversation is a preview of how specialty insurance is being reshaped: speed becomes a competitive advantage simplicity beats complexity regulators reward transparency partner ecosystems scale faster than solo builds automation shifts humans toward higher-value work As James puts it: any business has to evolve with market dynamics — and leaders need to think 2–5 years ahead. Because algorithmic underwriting isn’t “coming.” It’s already here — and it’s changing how Lloyd’s does business.

Transcribed - Published: 11 June 2025

On this episode of Scouting For Growth, Sabine VdL speaks with Mark Stern, Founder & CEO of Custom Box Agency, an award-winning boutique that helps digital businesses create unforgettable customer journeys through high-impact offline box experiences. If you’ve ever launched a digital offer and thought, “Why does this feel so… forgettable?” — Mark has the answer: Digital gets attention. Physical creates emotion. And emotion drives action. The unboxing effect: turning customers into ambassadors Mark shares how his early project, Entrepreneur Elements, proved a powerful insight: when you blend physical with digital, people don’t just consume the product… they share it. Recipients started posting unboxing videos, creating organic traffic and turning customers into ambassadors — something a digital-only offer struggles to achieve. In a noisy market, the box becomes a stage. The pivot that changed everything During COVID, virtual events became brutally competitive overnight. Everyone suddenly became a “virtual event expert,” and differentiation disappeared fast. But Mark spotted an opportunity hiding in plain sight: the box was still a frontier. He went all-in — and the business scaled from zero to $1M in its first year, simply by focusing on a physical experience that delivered faster, more tangible results than screens alone. This isn’t swag. It’s product design. Mark is adamant: these boxes are not “SWAG” (Stuff Without A Goal). They’re engineered experiences designed to drive outcomes. Inside a great box isn’t random merch — it’s structure: a welcome note a “getting started” guide (his most powerful sales asset) a journey map showing the path to results tools and resources to reduce friction The goal is simple: help customers take the next step with clarity and momentum. Done beats perfect — but the customer always comes first Mark brings a blend of startup speed and corporate standards. His philosophy is sharp: in online business, done beats perfect — but only if the customer experience is intentional. His north star is customer-centricity: it’s not about you, it’s about what your customer needs to succeed. Feedback loops that improve the product (and retention) Mark also explains how he uses boxes to engineer smart feedback loops: when customers hit milestones, the experience prompts them to share insights. That enables two wins: customers feel celebrated the business gets real data to improve the offer It’s retention design disguised as delight. Why this episode matters For founders, growth leaders, and enterprise teams building digital products, this episode is a reminder that the next conversion lift might not come from another funnel tweak. It might come from adding the one thing digital can’t deliver: a tangible experience that makes progress feel real. Because when customers can touch the journey… they’re far more likely to stay on it.

Transcribed - Published: 4 June 2025

On this episode of Scouting For Growth, Sabine VdL sits down with Colin Hirdman — lifelong entrepreneur, co-founder of Monkey Island Ventures, and the founder behind Rainmaker, a white-glove service that ethically automates LinkedIn outreach to turn connections into real revenue. If you’re tired of AI-driven spam, lazy “Hey {FirstName}” messages, and outreach that feels like it was written by a toaster… Colin is your antidote. This episode is a playbook for B2B founders, sales leaders, and growth teams who want to win on LinkedIn with what still beats automation every time: authenticity, micro-targeting, and consistency. Rainmaker’s “Authentic Engine”: why human still wins Colin explains how Rainmaker was born from his own growth experiments. After years of growth hacking through email and LinkedIn, he discovered he consistently got better outcomes on LinkedIn — so he built a repeatable system, then offered it to others. His key point: you don’t need Rainmaker to do this. You can run the entire strategy manually. Rainmaker just makes it easier to execute at scale. The core framework is what matters: campaigns tailored to micro-audiences education-first outreach (not pitch-first) and authentic interactions that build trust over time Because nobody wants to be sold to on LinkedIn… but almost everyone is open to being educated. The founder-friendly growth habit: 25 people/day Colin shares a simple rhythm that even solo founders can replicate: connect with 15–25 people a day, Monday to Friday, during working hours. That adds up to roughly 500 new outreach touches per month, staying safely under LinkedIn’s limits. With a typical ~20% connection rate, your network grows steadily — and compounding kicks in. His hygiene rule is equally practical: if someone doesn’t connect within 30 days, withdraw the invite. Then re-approach later with relevance, not desperation. LinkedIn growth hacks that aren’t gross Colin dives into smart ways to build targeted prospect lists without spamming: LinkedIn Events: attend events your ideal buyers attend (even competitors’) and build a relevant list Proxy audiences: use thought leaders in your niche as filters to find “people like them” Sales Navigator: hone in on micro-audiences with precision The goal isn’t volume. It’s relevance. Why first connections matter more than people realise Colin makes a point too many teams miss: being a first-degree connection unlocks real visibility and optionality — messaging access, richer context, and more ways to engage meaningfully. In other words: audience-building isn’t vanity. It’s infrastructure. Automation guardrails: ethical vs banned This episode also draws a hard line between automation that supports authentic outreach… and automation that gets you flagged or banned. Colin is blunt: if your automation is inauthentic, it won’t work — and it shouldn’t. You wouldn’t walk up to a stranger at a conference and ask for a meeting in sentence one. LinkedIn is no different. Spam is lazy, and the market is tired. The story behind the strategy Alongside tactics, Colin shares his entrepreneurial journey — including the “criminal justice grad” twist and the accidental early startup sale that set him on his path. It’s a reminder that growth isn’t reserved for the perfectly credentialed — it’s built by people who test, learn, and iterate. Why this episode matters If you’re building in B2B, this conversation is a modern growth blueprint: stop spraying messages start teaching micro-audiences build consistency into your calendar and use automation to support authenticity, not replace it Because in a world flooded with AI outreach… human wins — when it’s done with intention.

Transcribed - Published: 29 May 2025

On this episode of Scouting For Growth, Sabine VdL is joined by Georgiana “Gia” Laudi — strategic advisor, keynote speaker, and co-founder of Forget The Funnel — for a masterclass on one of the most underestimated growth levers in B2B SaaS: stop chasing leads… and start designing for the customers who actually stay. If your go-to-market strategy currently feels like “throw spaghetti at the wall and hope something sticks,” Gia delivers the cure: a truly customer-led approach that turns recurring revenue into something predictable (instead of panic-fuelled). Forget the funnel. Follow the customer. Gia explains why funnel-first thinking often traps teams in constant acquisition mode, while ignoring the real engine of sustainable growth: retention and expansion. Even if you’re not a pure recurring revenue business, the principle holds: existing customers are worth more, cost less to keep, and grow faster when the experience works. Or as Gia puts it perfectly: your relationship with the customer doesn’t end at purchase — it begins there. The 900% growth lesson: customer experience as an operating system One of the standout stories in the episode: after mapping the customer experience end-to-end through the customer’s lens, Gia’s company grew revenue by 900% over two years. Why? Because the map created something most teams don’t have: a shared language across departments. It aligned product, marketing, sales, and customer success around the same goal — making decisions faster, reducing internal friction, and operationalising around what customers actually need to succeed. Customer research doesn’t have to be painful (or expensive) Gia reframes “customer research” into something far more usable: customer insights. Instead of massive, slow projects that leave teams overwhelmed, she recommends targeted, intentional research using the Jobs To Be Done approach. The magic is in the pattern recognition: you can learn a shocking amount from just 10–12 conversations — enough to identify why customers seek you out, what triggers buying decisions, and what value they’re really hiring your product for. Not all customers are created equal Gia’s advice for scaling companies is refreshingly blunt: don’t try to serve everyone. Focus on your best-fit customers — the ones who: deeply care about the problem you solve have high willingness to pay understand your value quickly and would recommend you loudly Those are the customers worth building around. Early-stage? Nail one customer segment perfectly. Later-stage? Don’t flatten customers into one generic group — segment meaningfully so experiences still convert and resonate. Why this episode matters For founders, growth leaders, and enterprise innovators, this conversation is a blueprint for durable growth: orient operations around customer experience prioritise retention and expansion over constant acquisition use lightweight insight loops to drive clarity focus on the customers who value you most Because the fastest way to grow isn’t always more leads. It’s more customers who stay, succeed, and tell everyone else to follow.

Transcribed - Published: 21 May 2025

On this episode of Scouting For Growth, Sabine VdL sits down with Ron Rock, Managing Director for the Financial Services Sector at JobsOhio, to challenge a common assumption: If you’re building a FinTech or InsurTech business, your next strategic move doesn’t have to be New York or Silicon Valley. It might be Ohio. And yes — the heartland is quietly building a serious edge. Ohio: the FinTech hub hiding in plain sight Ron shares why Ohio is becoming an increasingly attractive base for financial services innovation. It’s the 4th largest financial services economy in the U.S., with a major advantage founders can’t ignore: access. Ohio puts you within a two-hour flight of 75% of U.S. and Canadian financial services industry players—a practical edge for partnerships, enterprise sales, and scaling relationships. Add to that lower operating costs compared to the coasts, and the value proposition gets very real, very fast. The growth formula: economy + ecosystem + talent Ron breaks down what every region needs to become a true innovation engine: a strong financial services economy an ecosystem of players (investors, corporates, startups with traction) talent that matches the jobs of the future And talent is where his message becomes a call to action: if you’re an IT graduate thinking about your career path, financial services should be on your radar. The opportunity in FinTech and InsurTech is growing—and the next generation needs curricula that include AI and low-code environments, not just legacy computing theory. Why Ohio works for testing and scaling Ron highlights another underrated advantage: Ohio is a stable environment for innovation. With fewer catastrophic loss events compared to some coastal markets, startups can test products with less volatility in the background. He calls Ohio a “microcosm” of the larger market — a practical sandbox where you can validate before scaling nationally. JobsOhio: support built for founders (not one-size-fits-all) Ron is candid that early programs weren’t perfect for early-stage startups. So they adapted. JobsOhio now offers more targeted support — including multiple innovation hubs across the state — and connects founders to incentives like the JobsOhio Growth Cap to help earlier-stage ventures build momentum. And that’s Ron’s role in a nutshell: he doesn’t pretend to be the product expert. He’s the connector — the facilitator who listens, understands what a company needs, and links them to the right partners, people, and pathways. Why this episode matters For founders, this conversation is a strategic wake-up call: geography is a lever. If you’re trying to scale in insurance or financial services, Ohio offers access, partnerships, and talent without coastal burn rates. For enterprise leaders, it’s a reminder that innovation ecosystems aren’t only forming in the usual places. Because sometimes the smartest move isn’t where the hype is. It’s where the relationships are easier, the economics work, and growth is actually buildable.

Transcribed - Published: 14 May 2025

On this episode of Scouting For Growth, Sabine VdL sits down with Alon Kaufman, CEO and Co-Founder of Duality Technologies, to tackle one of the biggest contradictions in modern enterprise growth: We need more data collaboration to win… but we also need more privacy, security, and regulatory control to survive. Alon and his team are solving that tension with privacy-preserving technology that lets organisations analyse and collaborate on data without exposing it—a capability that becomes exponentially more valuable in the age of AI and Big Data. The problem: data value rises… while data risk explodes Alon explains why combining datasets is getting harder — and why that’s actually a good thing. Privacy regulations, security expectations, and data localisation rules are tightening globally. That makes old-school collaboration models risky: centralising data in one place emailing datasets between partners relying on a “trusted third party” In today’s world, that’s not innovation — it’s liability. Duality’s mission is to unlock the value of joint data while keeping privacy intact: get the utility without leaking the data. The breakthrough: compute on data without sharing it At the heart of Duality is a powerful concept: homomorphic encryption. In plain terms, it allows organisations to run analytics on encrypted data—so the data stays protected while still producing insights. Alon gives a simple example: two companies want to know how many customers they share. Traditionally, one company would have to hand over their customer list (or send both lists to a third party). With Duality, they can compute the intersection without either side ever seeing the other’s raw data. That’s a huge unlock for partnership, fraud prevention, and responsible AI. Why this matters for government, healthcare… and insurance Duality has proven impact in high-stakes environments like government and healthcare, where datasets are large, sensitive, and heavily regulated. They also discuss a critical use case insurers will recognise instantly: fraud. Fraudsters exploit the fact that insurers don’t share enough information. They hit one carrier, then the next, knowing data collaboration is limited. Alon makes the case that insurers need ways to work together without violating privacy rules — and privacy-preserving analytics makes that possible. Privacy-preserving collaboration is a strategic advantage A key message from Alon: companies that already know how to manage and control their internal data can now take the next step—collaborate externally in a safe way. This isn’t just about compliance. It’s about unlocking growth: the more value you can create by enhancing datasets together, the stronger your decisions become—without increasing exposure. Why this episode matters For enterprise leaders, this episode delivers a clear roadmap for the next era: AI depends on data growth depends on collaboration trust depends on privacy and regulators aren’t going away Duality shows what future-proofing looks like: running analytics where the data is, generating the insight you need, and keeping the underlying information protected. Because in the AI era, the companies that win won’t be the ones who collect the most data. They’ll be the ones who can use it together — safely.

Transcribed - Published: 7 May 2025

On this episode of Scouting For Growth, Sabine VdL sits down with Sara Simeone, award-winning entrepreneur and Founder of NoCodeLab.ai — the first Vibe Coding Launchpad helping non-technical founders ship AI-powered products in just five weeks. If you’ve ever had a brilliant idea but didn’t have a technical co-founder, a dev team, or the patience for “learn to code first”… this episode is your permission slip. Because Sara’s message is simple (and slightly rebellious): You can build in plain English now. What is Vibe Coding — and why should leaders care? Sara defines Vibe Coding as building products using natural language prompts while “vibing” with the code — watching how the product changes as you add features and refine instructions. Think of it as the next evolution beyond drag-and-drop no-code: more expressive than templates faster than traditional development and accessible to anyone who can think clearly and communicate well It’s not coding as we knew it. It’s product building through conversation. The real problem: accelerators teach launching, not building Sara shares the moment she spotted a massive gap in the startup world: thousands of subject matter experts have real ideas and real domain knowledge — but can’t turn them into tangible products. Most accelerators assume founders either: have a technical co-founder, or can build the product themselves Which quietly excludes a huge portion of potential entrepreneurs. Sara’s take is empowering: founders don’t need to become engineers — but they do need a process that makes technology work for them. And that’s exactly where AI changes the game. Non-technical founders can now move fast — with discipline NoCodeLab.ai isn’t just about speed. Sara’s goal is to give non-technical founders the freedom to move fast with the discipline of the corporate world — helping them build real products, not messy prototypes held together by hope and duct tape. She describes the mindset shift beautifully: AI enables founders to step into multiple roles — CPO, CEO, CMO, COO — as long as they have the right structure and community around them. The playbook: start with the customer, not the tech Sara’s advice cuts through the noise: before generating requirements or building anything, ask: Who is the customer? What do they actually need? What will I charge for this? Once that’s clear, AI can help translate the vision into technical foundations—front end, back end, databases, APIs—without you needing to speak fluent developer. AI isn’t magic — it’s leverage One of the most practical insights: AI gives you tools, but you must learn how to use them well. The upside is enormous: if something breaks, you can interrogate the code, understand what’s wrong, and ask the AI to fix it. That feedback loop turns building into learning — fast. Why this episode matters Whether you’re a Gen Z founder, an investor scanning for the next scalable platform, or an enterprise leader looking for new growth engines, this episode is a preview of what’s coming: product creation is being democratised. Because the next wave of builders won’t be defined by who can write code. It’ll be defined by who can think clearly, move quickly, and turn ideas into products — one prompt at a time.

Transcribed - Published: 30 April 2025

On this episode of Scouting For Growth, Sabine VdL speaks with Ivan Pylypchuk, CEO of Softblues, and Olha Pylypchuk, the company’s COO, to unpack what many leaders are sensing but struggling to operationalise: Agentic AI isn’t a feature upgrade. It’s a new operating model. Together, they explore what agentic AI really is, why multi-agent systems are poised to disrupt traditional business processes, and what it takes to deploy AI agents that teams actually trust and use. Agentic AI: from “single task” to autonomous execution Ivan breaks down the difference clearly. Traditional AI systems typically handle one narrow task: image recognition, classification, or content generation. Agentic AI goes further. It can manage multi-step decision-making, coordinate actions, and operate with higher autonomy—especially when designed as controlled multi-agent systems, where each agent has a defined role and guardrails. In other words: not just intelligence… agency. The real blocker isn’t AI — it’s data fragmentation Softblues sees one challenge again and again: companies have valuable data spread across disconnected systems—CRMs, email, customer databases, business tools. And when those systems don’t talk to each other, AI can’t deliver reliable outcomes. Their message is simple: for AI to work, data must be collected neatly, accurately, and integrated across the organisation. Without that foundation, even the best model will produce weak results. The hidden issue: companies often don’t understand their own workflows One of the most striking insights from Ivan and Olha is that many organisations don’t actually know how work gets done day-to-day. When they observe real processes, they often find missing steps, informal workarounds, and operational blind spots—details leadership didn’t realise existed. That matters because implementing AI on top of an unclear process can lead to wasted investment later. Softblues addresses this by spending serious time mapping workflows from Point A to Point B, then enhancing them with AI rather than forcing automation into chaos. Adoption wins or loses everything Ivan and Olha emphasise that even a “perfect” AI solution fails if teams don’t use it. That’s why they focus on: simple interfaces recommendations explained in plain language and explainability that builds trust quickly Agentic AI only scales when humans feel confident in what it’s doing—and why. Start small. Prove value. Then scale. Their deployment philosophy is practical: start with a small part of the project where AI can show fast results. Once value is proven, scale confidently. It’s how organisations move from experimentation to transformation without breaking operations—or trust. Real outcomes: speed + quality Softblues shares measurable impact from their solutions, including: reducing time-to-hire by 60% increasing quality of hires by 40% The bigger payoff, though, is strategic: freeing teams from data wrangling so they can focus on higher-value work that moves the business forward. Why this episode matters For enterprise leaders in insurance and financial services, this episode is a blueprint for agentic AI adoption that’s grounded in reality: agentic AI thrives in controlled multi-agent systems data integration is non-negotiable workflow clarity comes before automation trust and usability drive adoption small wins create scalable momentum Because the future of work won’t be shaped by AI that’s impressive in demos. It will be shaped by AI agents that quietly make organisations faster, smarter, and more strategic—every single day.

Transcribed - Published: 23 April 2025

On this episode of Scouting For Growth, Sabine VdL meets Areiel Wolanow, Managing Director of FinServ Experts, for a sharp, strategy-first conversation on emerging tech, responsible AI, and why most “digital transformations” fail before they ever create value. Areiel’s journey spans IBM to founding FinServ Experts, but his message is refreshingly consistent: Don’t fall in love with the technology. Fall in love with the business model it enables. Stop modernising the old — design the new Areiel challenges one of the biggest traps in enterprise innovation: using new technology to simply re-engineer yesterday’s operating model. Instead, he argues emerging tech should be used to unlock new business models, new value chains, and new ways to serve customers. That mindset shift is what separates “innovation theatre” from real advantage. AI success starts with brutal self-awareness When it comes to AI, Areiel is clear: the biggest risk isn’t model selection — it’s solving the wrong problem. Before applying maturity models or gap analyses, leaders must ask a tougher question: Is the proximate cause actually the real problem? AI adoption should be grounded in organisational self-awareness: understanding what’s broken, what’s possible, and what the enterprise is mature enough to operationalise safely. Responsible AI: the EU AI Act is a blueprint, not just regulation Areiel points to the EU AI Act as one of the most useful frameworks available for responsible AI. Its value goes beyond compliance: it offers risk categories, controls, and governance principles that can help organisations everywhere build ethical AI practices with more clarity and less guesswork. In his view, it may even benefit companies outside the EU more — because they can adopt the structure without carrying the compliance burden. Quantum computing: the security clock is ticking Areiel also raises a forward-looking concern many executives aren’t planning for yet: quantum computing. As quantum capabilities advance, today’s encryption methods could become vulnerable. The organisations that win won’t be the ones reacting late — they’ll be the ones planning early by adopting quantum-resilient algorithms and preparing their data strategy long before the risk becomes urgent. Transformation vs migration: the smarter path forward Perhaps the most provocative line in the episode is Areiel’s blunt take: Digital transformations have two things in common: they’re expensive, and they always fail. His alternative? Think migration, not transformation. Move deliberately, reduce disruption, and evolve your operating model through staged progress rather than big-bang reinvention. Give younger talent the keys (with guardrails) Areiel also challenges leaders to rethink how they use internal talent. Younger team members often have stronger fluency in emerging technologies — but they’re rarely given the responsibility to drive meaningful outcomes. His advice: empower them with autonomy, support, and real ownership. That’s where unexpected innovation can emerge. Why this episode matters For insurance and financial services leaders, this conversation is a practical playbook for navigating the next wave of change: build business models, not tech demos diagnose root causes before deploying AI use governance frameworks to scale trust prepare now for quantum security risk migrate strategically instead of “transforming” blindly Because in the next era of financial services, the winners won’t be the ones with the newest tools. They’ll be the ones who turn technology into strategy — and strategy into results.

Transcribed - Published: 16 April 2025

On this episode of Scouting For Growth, Sabine VdL sits down with Lisa Bechtold, a global executive at the intersection of technology and law, and formerly Head of AI Governance at Zurich Insurance Group (now leading Group Risk Management at Nestlé). This is not an “AI trends” episode. It’s a leadership playbook for any executive asking: How do we scale AI innovation in insurance… without scaling risk along with it? AI governance isn’t bureaucracy — it’s the engine of trust Lisa makes a powerful point early: AI governance isn’t about slowing things down. It’s about how we use AI responsibly in a world where AI increasingly touches every part of business and private life. And success isn’t universal. The acceptance of AI tools varies by region, shaped by legal systems and cultural norms. For global insurers, that means governance must be both structured and context-aware—because trust isn’t built the same way everywhere. Lisa’s core principle is simple: optimise AI’s benefits while minimising its risks. Scaling AI takes literacy, not just platforms Zurich didn’t just build AI tools—they focused on enabling adoption across the organisation. Lisa explains how scaling requires both: reusable solutions that prove value repeatedly AI literacy so teams know how to use tools properly Even something as basic as prompt quality can determine whether GenAI delivers insight… or noise. Education becomes a multiplier: it drives adoption, improves output quality, and reduces misuse. Experimentation needs boundaries — and a sandbox Lisa highlights a critical balance: if you want innovation, you must allow experimentation. But experimentation without guardrails becomes chaos. Her approach is to create safe sandbox environments where teams can explore AI responsibly—building confidence while preventing uncontrolled risk. Insurance is already data-driven, so AI adoption is a natural evolution across the value chain—from modelling to operations. The difference now is speed, scale, and autonomy. 2025 and beyond: the multi-agent era raises the stakes Looking ahead, Lisa outlines a major shift: AI systems are beginning to interact autonomously and adapt based on one another. As multi-agent systems become more powerful, they unlock enormous business opportunity—but also introduce new challenges: information asymmetry miscoordination complexity that’s hard to audit behaviours that must be monitored continuously Managing that complexity “in a safe and lean way” while optimising value is, in Lisa’s view, one of the defining priorities for 2025. Why this episode matters For C-suite leaders, this conversation reframes governance as a competitive advantage. AI governance isn’t the compliance tax. It’s the foundation for: scalable AI adoption high-quality outcomes sustainable business value and digital trust that customers reward Because in the AI era, the winners won’t be the companies that deploy the fastest. They’ll be the ones that deploy responsibly—and at scale.

Transcribed - Published: 10 April 2025