NextGen Insurance

The Steve Jobs moment in insurance

Leave a Comment | Digital Transformation, NextGen Insurance, NextGen Leadership |

“There are worse things in life than death. Have you ever spent an evening with an insurance salesman?” – Woody Allen Well, I must admit that I work in one of the most boring industries in the world. If you read this, chances are we are on the same boat. No matter how much I try to convince myself of the purpose of this noble industry, it is hard to create a sensation at a party when you are asked which industry you are in. Just picture that: “Medicine”, “Rocket science”, “Insurance” – a long, embarrassing silence. Jokes aside, our boring industry is the enabler of resilient communities and a healthy society. But boy, is it exciting? Are people craving to buy an insurance policy for status or credibility? Insurance was never meant to be thrilling — at least not in the “Steve Jobs walking on stage” sense. It was designed to be correct. Precise. Compliant.  However, the Steve Jobs era showed us a universal truth: people do not crave products; they crave experiences. So what can we offer? The essence of excitement is not drama. It is possibility. The springboard for our ambitions Insurance becomes genuinely exciting when it acts as a springboard for human ambition. When it tells you: go build the life you actually want. Move countries. Change careers at forty-eight (ahem!). Start the company. Take the bigger, braver step because the downside is no longer catastrophic. In every bold decision, you need someone who takes the risk so you can focus on the reward. That is where this “boring” industry becomes unexpectedly powerful. Nobody dreams of a policy. They dream of the life that policy protects. Insurance is simply the structure that keeps life intact when the story takes an unexpected turn. It is not the hero of the story, but it is the reason the hero can keep going. Think about the milestones people celebrate — buying a home, opening a business, starting a family, climbing another peak simply because it feels good. Sure, we need the rush of adrenaline, but we also need stability. Stability is exactly what insurance provides, whether it gets applause or not. Simplicity is the new black Insurance needs to modernise its entire identity.Policy wording still reads like a peace treaty with Schrödinger’s cat — tiptoeing around uncertainty, wrapped in footnotes, and designed to test the patience of even the calmest human – we need to do better. Language must sound human, not bureaucratic. Clear customer journeys feel understandable instead of exhausting. Products look contemporary rather than intimidating, covering emerging threats, adapted to the sharing economy and the new realities of life.  We succeed when people can say, “This makes sense,” without needing caffeine or legal counsel. Rebuilding lives and communities There is also a collective side we rarely talk about, yet it shapes everything around us.Rebuilding cities after disasters. Helping businesses reopen after shocks. Keeping families afloat. Making sure that when something breaks, the entire community does not crumble with it. Remove insurance, and suddenly half of modern civilisation becomes uninsurable, unimaginable, or simply too risky to attempt. Insurance may never get fireworks or the drama of a product launch on a dark stage.However, it gives people something far more meaningful: the confidence to choose the bigger life instead of the safer one. That is our version of excitement.  So, do we need a Steve Jobs moment in insurance? Probably not. I do not expect an insurance CEO in a black turtleneck unveiling the “next big thing” on a stage. But I do expect something else from us as an industry: to rewrite the narrative around customer value. Insurance should help people live better, take controlled risks, and build the life they actually want. It should speak in plain, simple language. It should show people, without theatrics, why their life is safer, calmer, and more possible with insurance in it. And maybe what I miss most is the energy of building something new with the customer — not at them. Getting excited together about what is possible, instead of trying to impress them with what is “innovative.” Maybe that is our real opportunity. And maybe it is exciting enough.

The Rise of “AI-human Boards”

Leave a Comment | NextGen Economy, NextGen Insurance, NextGen Leadership |

Why AI Governance Must Start in the Boardroom AI has arrived in the boardroom — and not as a guest. It is now a core agenda item for directors worldwide. A recent paper from IMD shows that 79% of business leaders expect GenAI to drive substantial organisational change within three years. However, nearly half of the directors have never discussed AI in a board meeting, while over three-quarters admit they have a limited understanding of the technology. The Harvard Law School Forum on Corporate Governance finds that nearly half of companies (48%) now cite AI risk under board oversight of enterprise risk—three times more than last year—while 44% highlight AI expertise in directors’ biographies and skills matrices, up from 26% in 2024. AI governance is becoming the new test of leadership. It requires independent thinking, critical questioning, and the ability to connect technology with long-term strategy. Too often, AI is left to the CIO or an innovation team. That model no longer works. The way boards approach AI will shape how power, trust, and accountability evolve in business. And the topic is more urgent than ever. Today, a single flawed algorithm can move markets, a deepfake can destroy reputations overnight, and automated decisions can trigger regulatory crises before anyone notices. The familiar comfort of quarterly reviews and static risk registers belongs to another age. Companies are moving from AI-first to AI-native models; as a result, boards will increasingly need to include members with technological expertise and dedicated AI committees. The new role of the board is not only to oversee AI adoption, but to guide the organisation in learning to think with AI. How can Boards prepare for the future? Here are five things the Boards should consider to stay effective in this new landscape. The boardroom of the future will not be defined by age or background, but by awareness — the ability to think systemically and act with clarity in the face of uncertainty. Boards have long discussed ESG, diversity, and risk. AI is now the new “G” — the governance lens through which all these elements converge. The real test of modern leadership lies in how quickly boards can move from reactive oversight to proactive direction. The question is: do we have the competence and courage to govern technology before it governs us?

Building the Mental Health Ecosystem: Insurance’s Most Important Transformation Yet

Leave a Comment | Digital Transformation, NextGen Economy, NextGen Insurance |

In 2022, after her father passed away, I tried to find a therapist for my daughter.She was 11. Heartbroken.And I was told we needed to wait nine to twelve months. Nine to twelve months for a child in pain.That was the moment I realised just how broken the system is. Her story is not rare. Across the world, millions of people who need mental-health support face months of waiting, high costs, and limited access. The shortage of qualified professionals is real—but so is the opportunity for insurance to become part of the solution. For decades, insurance has been built on protection—paying out when things go wrong. But in a world where mental-health issues are now one of the leading causes of disability, absenteeism, and productivity loss, that model is no longer enough. It is time for insurance to become a system of prevention. The Data Behind the Crisis According to Swiss Re’s 2025 “The Future of Mental Health Disclosure: How Generational Openness is Shaping Insurance”, mental-health-related disability claims have surged dramatically over the last decade, now accounting for up to one-third of all income-protection and long-term disability claims in many mature markets. Depression, anxiety, and stress disorders are the main drivers. What is equally concerning is the long recovery time. Mental-health-related claims last, on average, 40–50 percent longer than physical ones. This does not just represent financial strain—it reflects how fragmented and reactive our systems remain. Swiss Re’s report also highlights a cultural shift: younger generations are far more open about mental-health challenges than previous ones. While that is encouraging, it also means the industry must adapt faster. Greater openness will bring higher disclosure, higher claims, and—if not handled wisely—greater pressure on profitability. The Global Context: From Awareness to Action The World Economic Forum’s 4 Imperatives for Improving Mental Health Care in 2025 calls this decade “a turning point.” Mental health is now viewed as an economic necessity, not a social cause. The WEF estimates that poor mental health costs the global economy over USD 5 trillion annually, a figure projected to rise sharply by 2030. The Forum identifies four priorities that align perfectly with what the insurance industry can and should drive: The good news is that insurers are finally beginning to act. How the Industry Is Evolving RGA’s recent analysis, Insurance Industry Moves Forward on Mental Health, shows that insurers worldwide are experimenting with new solutions that blend technology, data, and human support: This represents a shift from crisis payout to proactive care. Insurers are starting to see that long-term profitability depends on keeping people well, not only on compensating them when they break. A Blueprint for the Future The building blocks are already there. Here is how insurance can make prevention its next frontier: Prevention as Purpose—and Profit This evolution is not philanthropy; it is good economics. Swiss Re’s data show that mental-health claims are not only rising but lasting longer, directly affecting loss ratios. Early intervention and continuous support shorten recovery time and reduce repeat claims. The WEF reinforces the same logic: prevention is cheaper than crisis management, both for societies and for insurers. Investing in mental-health infrastructure is no longer a CSR initiative—it is a risk-management strategy. The Purpose the Industry Was Built For Insurance was created to protect. That is its core purpose. For decades, protection meant financial compensation after loss. But in today’s world, protection must mean something deeper: keeping people healthy, productive, and resilient before loss even occurs. When insurers act as ecosystem builders—connecting technology, healthcare, and community—they unlock a model where prevention and profitability reinforce each other. Mental health should never depend on luck, income, or geography. When insurers start investing where healing begins, they do more than pay claims. They fulfil their purpose—protecting life in all its forms. That is not just the next frontier of insurance.It is what the industry was built for.

Would you buy insurance from a digital avatar?

Leave a Comment | NextGen Insurance |

A conversation about insurance marketing, selling to Gen Z and digital avatars with a marketing entrepreneur – Constantin Buda Insurance is often called boring. I am the first one to admit that our industry is far from proposing to their customers to buy insurance from digital avatars. And we are probably not well-equipped to sell to Gen Z.  In this conversation, I sat down with Constantin Buda, a marketing and digital entrepreneur who leads Vidalico, a B2B growth agency with roots in Finland and a fresh footprint in Switzerland. Constantin is not from the insurance industry. And that is what makes this conversation so refreshing. We talked about what the industry looks like from the outside, how insurance could speak to a younger generation, what GenAI and digital avatars might bring—and why the magic is not in the tools, but in the mindset. How does insurance look like to a customer Mirela: So far, you’ve encountered insurance mostly as a marketing expert and as a customer. And I’m the first one to say this is a very boring industry. What does it look like from the outside? Constantin: I couldn’t agree with you more—insurance is a boring industry. And I think there are a few reasons why. It hasn’t really changed in the past 10 or 15 years. I’ve worked in Finland, in the Nordics, and now in Switzerland, and I’d say insurance is one of those “musts” in life—you need it for your car, your home, your business—but it’s not something people get excited about. It’s unattractive. When I buy insurance, I’m just comparing prices and choosing the cheapest one. The messaging is outdated, the marketing hasn’t caught up with the way people live today, where half the population is using AI to plan meals. It’s behind. How to explain an insurance product to a child Mirela: And you’re also dealing with highly regulated environments, which makes it even more difficult. But I loved what you said earlier when we talked—about how you ask your clients, “How would you explain your product to a 5- or 10-year-old?” Constantin: Exactly. When I work with clients from heavy industries—mining, energy, and so on—I ask them that. And I would ask the same of insurance companies. How would you explain your offering? And in which format? Because today, communication happens on mobile, on social media, in small doses. But insurance is often fragmented—you have the company, then you have agents, partners. So, who am I actually dealing with? Who do I go to when something bad happens? Customer experience is fragmented Mirela: Exactly. In insurance, we call that a claim. But most people outside the industry don’t even know the terminology. Constantin: Right. And it creates this fragmented customer journey. The website says one thing, mobile says another, and then there are the agents. I grew up in Romania, like you. And back then, insurance was sold through agents. You bought a policy from your friend because they were the ones selling it. But that did not translate into trust in the company behind it.  Mirela: And you trusted the friend, not the system. That’s still the case today in many places—even for simple products. Insurance is still a relationship-driven business. But with generative AI, we might see some changes. Some products still require expert advice. But for things like travel insurance? That can be easily handled by a chatbot if it’s built right. Constantin: Yes. And in insurance, like in pharma or banking, the regulation is strong. But the way we present information is… let’s say, outdated. I dread getting a new policy. The first conversation is about protection, maybe some benefits. And then: the fine print. Legal language, jargon—pages of it. I never read it. Storytelling is the most important part in insurance marketing Mirela: And I’m going to confess something here. I’ve developed insurance products—life, health, property—and even I don’t read the full terms and conditions when I buy for myself. I hate it. Constantin: Exactly. So why not simplify? I’d go further than personalisation—I’d go into hyper-personalisation. Segment the audience deeply, meet them where they are—on their channels, in their language, based on their culture, hobbies, or life stage. Then explain what insurance really does. And tell stories. Real ones. People relate to stories. If I were running an insurer’s marketing, I’d focus on mini customer success stories. “Here’s what happened when this person made a claim. Here’s how we helped.” Show the process, the emotion, the outcome. That’s how people evaluate whether to trust a brand. Mirela: I look at testimonials, ratings, and reviews. I want to see how people like me were treated. If I read that someone had a bad experience, that’s a dealbreaker for me. An insurance claim is a very stressful moment for people. They might be in an accident, injured, or dealing with illness. The experience at that moment matters a lot. This is the moment of truth, when you show your value. So what would you do differently in that case? Constantin: I’d start with those bite-sized stories—real stories. Then I’d simplify the technical language. Use chatbots to guide users, but always give them the possibility to connect with a human. When buying insurance, I’d even go a step further: build an interactive policy builder. Have a chatbot act like a virtual advisor. Ask questions in natural language. Let people choose options and understand what they’re getting. How to sell insurance to Gen Z? Mirela: I love that. Let’s go to another topic—how would you sell insurance to Gen Z? Constantin: First, I’d figure out where they spend time. Then I’d use creators or influencers they follow. Build video content—explain-it-like-I’m-five style. “You’re going to Bali? Here’s what happens if your luggage disappears. That’s why you need travel insurance.” And I’d bundle the product with something relevant. In Finland, for example, one of the insurers I use gives me loyalty points with a major retailer every time I pay my insurance. Those points

Beyond Pilots: AI in Insurance

Leave a Comment | Digital Transformation, NextGen Insurance |

AI in insurance in 2025 is overhyped and underdelivering.  There. I said it. We are witnessing an AI frenzy in the insurance industry. Vendors are pitching shiny solutions, boards are eagerly asking about AI strategies, and innovation teams are running around setting up pilots.  On paper, it looks like progress. In reality, most of these initiatives deliver little to no measurable value. “Only 1% of companies describe their GenAI rollouts as ‘mature.’” (Source: McKinsey & Company, 2025)  AI – the magic buzzword in insurance AI is not a magic wand that fixes broken foundations.  It is a multiplier. If you layer AI on top of messy workflows, unclear goals, and poor data, you will get exactly what you built—only worse. AI will amplify the dysfunction. It will accelerate chaos. It will turn small inefficiencies into expensive problems. That is why so many AI projects in insurance follow the same storyline: initial excitement, a few nice demos, then a quiet retreat when no real impact is delivered.  Six months later, the board asks, “Where is our AI ROI?” and the answer is a lot of awkward silence. McKinsey estimates that generative AI and other technologies could unlock up to $4.4 trillion in annual productivity gains across industries. For insurance alone, AI could deliver up to $1.1 trillion in annual value. (Source: McKinsey & Company, 2023). However, that is possible only if we scale AI to create impact. Overhyped and underdelivering – what if the problem is not AI? We often fall into the trap of choosing technology first, then figuring out what to do with it.  Teams get excited about GenAI, machine learning, or automation tools, but forget to ask the most important question: What business outcome are we trying to improve? If that answer is fuzzy, the project is already doomed. AI does not define business goals for you. It does not clean your data. It does not fix broken processes. It will not magically convince your teams to adopt it. These are foundations you need to build yourself before AI can deliver any meaningful results. Over the years, I have seen countless projects fail because we try to solve surface-level problems with advanced technology, without addressing the underlying issues. We throw AI at processes that are full of manual workarounds, exceptions, and legacy systems, hoping it will fix everything. It does not. In fact, it often adds more complexity. AI adoption in insurance AI is a tool. A powerful one—but only when used correctly. And it is not just about technology. How you communicate AI within your organisation matters just as much as the technology itself. Improving explainability Explainability is not a technical luxury—it is a business necessity. If your teams do not understand how AI makes decisions, they will not trust it. And if they do not trust it, they will not use it. It is that simple. Insurers need to move beyond the black-box approach and start designing AI systems that are transparent, with clear logic that human experts can audit, challenge, and refine. Explainability does not mean exposing every line of code. It means showing how decisions are made, in language that makes sense to the people who will use them daily. It means allowing human experts to intervene, correct, and improve the model’s outputs. It means positioning AI as a partner, not a competitor. AI in insurance core processes – people first approach One of the biggest reasons AI adoption fails in insurance is fear. Not fear of technology failing, but fear of people being replaced. Claims handlers, underwriters, and operations teams are often told that AI will “augment” their work, but all they hear is “this machine is here to take over your job.”  That fear creates resistance. Subtle at first: people just not using the tools, ignoring recommendations, sticking to manual workarounds. But over time, this quiet resistance kills adoption. Adoption improves when people feel empowered, not threatened. When underwriters see that AI handles repetitive data processing, they can focus on complex risks.  When claims handlers realise that AI helps them triage faster, while they bring the empathy and judgment that AI cannot replicate.  The message is not “AI will replace you.” The message is “AI will take the grunt work off your plate, so you can focus on the decisions that truly need you.” And this shift starts with leadership. Insurers need to lead this conversation, openly and honestly. A communication and upskilling plan is not a side project—it is at the core of any AI initiative that wants to succeed. Show your teams how their roles will evolve. Involve them in designing how AI integrates into their workflows. Support them with the training and tools they need to feel in control of the change, not at the mercy of it. That is how you build adoption. Not by pushing AI onto people, but by pulling them into the journey. The AI Blueprint Over the last few years, I dug deeper into the question – why most AI projects fail to deliver impact at scale?  We know the drill – most companies run in endless circles, from one proof of concept to another. It is no surprise that we speak about AI being both overhyped and underdelivering on impact. The methodology The AI Blueprint finsurtech.ai created is not a workshop, nor an endless assessment. It is a short, focused engagement that helps insurance teams move from AI experimentation to actual execution.  We look at what matters first: defining clear business objectives, mapping processes and user journeys, and assessing whether your organisation is even ready for AI.  Sometimes, we discover that a simple workflow automation or a process redesign can have a greater impact than any AI model could. And that is fine. The goal is not to use AI for the sake of AI. The goal is to solve problems and deliver value. When I say assess readiness, I mean it. Data quality, decision logic, compliance needs, and explainability requirements are not boxes to be

Forget Your Job. AI Might Be After Your Cybersecurity.

Leave a Comment | Digital Transformation, NextGen Insurance |

Everyone is talking about AI taking jobs.Fair enough. But what if the most pressing risk is how AI threatens our cybersecurity? While the world debates automation and employment, a far more dangerous threat is unfolding: AI-powered cyberattacks. In today’s digital arms race, AI is more than a tool – it is a weapon, and a potentially devastating one. What used to be handled by human analysts is now being overtaken by intelligent, self-learning systems, capable of launching attacks faster, smarter, and at unprecedented scale. The same technology we built to defend ourselves is now being turned against us. In this article, we dive into the dark side of AI: the rise of automated threats, the vulnerabilities they exploit, and the impact they could have on our economy, our institutions, and our lives. A New Generation of Threats Arguably, AI is speeding things up, but not always for the better. Today’s cyberattacks are more sophisticated, more targeted, and, most alarmingly, more automated. What once took months of reconnaissance and manual effort can now be executed in minutes with the help of generative AI. Attackers are now using AI to craft highly personalised phishing messages, often in multiple languages. By mimicking writing styles and context, these emails appear strikingly real, making them far more likely to succeed. They also use AI to clone executive voices and faces, enabling deepfake scams. A fake video call from a “CEO” can trick employees into approving fraudulent transactions. Polymorphic malware is another weapon – malicious code that constantly changes to avoid detection. Traditional antivirus tools cannot keep up with these shapeshifting AI cybersecurity threats. AI accelerates the discovery of zero-day vulnerabilities—undetected flaws in software. These are like secret doors into a system, wide open for attackers until discovered and patched. Finally, attackers are poisoning AI training data, corrupting the systems meant to protect us. By feeding AI false inputs, they cause it to ignore real threats or flag harmless actions as dangerous. In the financial sector alone, leaders are raising the alarm. A 2025 report by Business Insider revealed that 80% of banking cybersecurity executives feel unprepared for the rise in AI-driven attacks, despite increasing their budgets year over year. Impact Across Industries The impact of these threats is both broad and deep. In financial services, the rise of generative AI has supercharged fraud. Deepfake-powered scams have already led to high-profile losses, and analysts warn that AI-enabled fraud may quadruple global damages by 2027. In critical infrastructure, the convergence of operational technology (OT) and IT systems has opened the door for attackers to use AI in targeting energy grids, transport systems, and even water utilities. Researchers are now urging hybrid human-AI response systems to anticipate these evolving threats. In insurance and risk, AI-generated synthetic identities are posing challenges to underwriting and claims systems. As identity becomes easier to fake, trust becomes harder to verify. Imagine the impact on risk assessment or claims fraud. As an industry, we were struggling to prevent basic fraud. Are we going to keep up with AI-powered fraud? And across all sectors, existing cryptographic systems are facing dual threats: AI-assisted decryption techniques today and quantum computing threats on the horizon. This has accelerated interest in post-quantum cryptography, with institutions moving from research to implementation far sooner than anticipated. The Trust Gap Despite the clear need for AI in cybersecurity, a notable gap remains: the trust gap between cybersecurity leaders and those on the front lines. A recent TechRadar Pro study found that while over half of executives believe AI improves productivity, only 10% of security analysts trust AI systems to work without human oversight. Tool fragmentation, black-box models, and poor explainability continue to limit adoption and scale. Without trust, even the best tools risk becoming shelfware. The Regulatory Catch-Up The rapid advancement of AI has also caught regulators off guard. With few clear frameworks for AI governance, companies find themselves constrained. Many hesitate to deploy full-scale AI detection or prevention models for fear of unintended consequences or future legal exposure. Meanwhile, attackers have no such constraints. This imbalance is unsustainable. To level the playing field, companies, policymakers, and cybersecurity firms must collaborate to develop agile, risk-based frameworks that enable innovation without compromising oversight. What Must Change Cybersecurity in the AI era cannot be solved with more tools alone. What is needed is a shift in mindset and architecture. Human-AI collaboration must become the new norm. AI is not here to replace cybersecurity analysts but to enhance their capabilities. A well-trained analyst using AI can sift through thousands of threat signals in seconds, prioritise real threats, and respond faster than ever before. For example, platforms like IBM QRadar or Microsoft Sentinel already use AI to reduce alert fatigue and surface critical anomalies. However, they still rely on human judgment to validate and act. Second, unified threat intelligence must break through institutional and geographic silos. Today’s attackers do not respect borders—so neither should our defenses. Cross-sector and cross-border collaboration is critical to track how AI-powered campaigns evolve. Initiatives like the Global Forum on Cyber Expertise and EU-wide threat-sharing platforms are steps in this direction, but more real-time, open data exchange is needed to stay ahead. Third, resilient cryptography must move from pilot to production. As AI accelerates and quantum computing inches closer, traditional encryption like RSA and ECC is no longer enough. Post-quantum cryptographic algorithms—once considered overcautious—are quickly becoming urgent. Governments and institutions are already testing NIST-approved standards, but adoption remains uneven and slow. Lastly, governance and transparency must be built into every AI security deployment from day one. Black-box systems are dangerous in high-stakes environments. If analysts and regulators cannot explain how a model works—or why it made a decision—it undermines trust and opens the door to manipulation. Explainability is not just a compliance checkbox—it is a prerequisite for long-term resilience. In short, defending against AI-powered threats will require more than smart tools. It will require smarter strategies, shared accountability, and systems designed for adaptability and trust. The Stakes Are Rising Cybersecurity has always been a race, but the finish line keeps moving. In the age of AI, the speed, scale, and sophistication of attacks are evolving faster than

Three Predictions for the Insurance Industry

Leave a Comment | NextGen Economy, NextGen Insurance |

Insurance is (finally) getting interesting – here are three predictions regarding its future. I have spent my entire career in insurance. It is an industry that carries enormous responsibility. Insurance exists to protect people from loss, risk, and uncertainty.  But let us be honest: for decades, it felt stagnant, boring and unfriendly. Every conversation came back to the same themes – risk management in complicated models, regulation, legacy systems, and incremental change. That era is ending. Today, insurance is finally being reshaped. Not modernised, not closer to the customer, but fundamentally redefined. Below are three shifts I am seeing from the inside, and why they matter more than flashy apps or buzzwords. Prediction 1 – The Rise of the Insurance Ecosystem Orchestrator In the past, strength came from ownership. Owning tech, owning distribution, owning data. The modern model is the opposite: coordination over control. The insurers that will lead are those who understand how to curate and align the right partners rather than building everything in-house. We move towards an ecosystem-driven economy, and insurance makes no exception.  That means having a clear-eyed view of where your own capabilities end and where external partnerships genuinely add value. Maybe a start-up created a claims functionality better than anything you have seen. Shall you replicate it in-house? Copying is not cool, and maybe your capabilities can be used differently. Maybe exploring together and helping the start-up scale their solution is more lucrative for everyone involved. It also means developing governance models that can handle complexity without becoming bottlenecks. Ten Steering Committees and dozens of approvals for changing the coffee brand? That will not do when it comes to innovation and modern propositions. Perhaps most importantly, it requires the humility to acknowledge that innovation often happens beyond your own walls, and the openness to bring that innovation in without needing to control it. Hiring 300 developers offshore will not get you there. Building a flexible, composable architecture that lets you plug into insurtechs, MGAs, and alternative data sources just might. The future is happening faster than we assumed. The challenge is that most incumbents still think in terms of silos and procurement. Being an ecosystem orchestrator means changing how you make decisions, not just who you partner with. Prediction 2 – From Reactive to Proactive Insurance We have talked about prevention for a while in this industry, but no dramatic change has happened so far. Seven years ago, we were playing with apps to detect traffic incidents and inform the customer in due time. Now this is something every navigation software can do. Insurance has historically focused on what happens after an event. It is only now that we are beginning to act before it. This shift is slow but visible, especially in health, cyber resilience, and climate risk. Prevention is more than motivational emails or downloadable PDFs.  Real risk management means preventing the event from happening, not managing consequences. For example, we can integrate IoT data directly into pricing models so that risk is assessed continuously, not just at underwriting. Or use behavioural insights to help customers make the right decisions in real time, not in theory.  This is a shift in how insurers operate, not just how they communicate. It demands new capabilities: risk analytics, behavioural science, and UX design. Not typically found in underwriting departments, right?But it pays off: reduced claims, longer-term relationships, and relevance in a world where customers expect more than a payout. And one more thing: if your customer portal is still your main “innovation” story, you are likely falling behind. Prediction 3 – Customers Do Not Want Insurance. They Want Solutions. I was involved in a project to redesign the SME journey. The company had already failed at it a few times. And it was not due to lack of expertise – they had the risk knowledge, the tech, the right people in the room.  So why did it flop so many times before? They misunderstood the customer. They assumed small business owners had the time or patience to dive into cyber risks, healthcare plans, property cover, or fleet management.  But most of them were focused on something else entirely: making their business work, growing it, staying competitive. Insurance was not the priority; it was just another task to deal with. This is a systemic issue. Customers, whether individuals or businesses, are not asking for insurance. They are asking for protection, stability, and support at moments of stress or transition. We respond with PDFs, disclaimers, and policy add-ons. What actually works? Insurance that comes as part of something people are already doing: a transaction, a booking, a service. No separate process, no hunting for coverage. Design that feels obvious, not clever. And business models that make things easier, not more complicated. Simple as that. For insurers, that means moving from product-centric thinking to customer-journey design. It also means letting go of the idea that insurance has to be a standalone purchase. Believe me, no one will miss a big insurance brand when they have an end-to-end solution to their problem. Where This All Leads Insurance will not become a tech industry. But the companies that succeed will act like orchestrators, behave like service providers, and think like behavioural economists. The ones that cling to old models will not fail overnight. They will slowly lose relevance. The world is moving fast, and small, smart companies are already biting into the insurance value chain. This is the moment to get it right. Not by copying Silicon Valley or chasing shiny trends, but by getting back to the fundamentals. Rethink how you partner. Rethink how you manage risk. And most of all, rethink how you show up for the people you claim to protect. For once, insurance is not boring (the predictions above prove it). And I am here for it.

Why Operational Excellence Is the New Innovation

Leave a Comment | Digital Transformation, NextGen Insurance |

Operational excellence is the new innovation. Before you jump out of your seat, hear me out. Innovation in insurance often makes headlines when it is loud: new digital products, embedded insurance, usage-based pricing, ecosystem partnerships. And all of that is important.  But while the spotlight shines on the flashy newcomers, the backbone of this industry is still built on traditional products – motor, property, health, and life. The main problem in our industry is that many of those products are still difficult to buy, understand, and even claim. And that is where the real innovation opportunity lies – not in launching the next digital-only gadget but in reimagining what already works for millions of people and making it work better. The Uncomfortable Truth: Most Products Are Still Clunky Let’s be honest: buying a motor policy still feels like paperwork, even when done online. Most customers are lost when they go through an accident, and filing a claim still feels like a negotiation. Customer service? That is more of a ping-pong game, a “pass-the-request” across departments and systems. It is not the product that is broken – it is the experience around it. If we are serious about innovation, we must stop treating these everyday processes as legacy baggage and start treating them as core value drivers. It is always great to create a new, disruptive product, but without strong operational foundations, it will not fly. Parametric with manual payments defeats the purpose of creating it to begin with. Before creating an IoT-based insurance product, make sure you have solid data processing capabilities.  Innovation Is Not Just the New. It Is Also the Better Innovation is not only about launching something different. It is also about making something better. What if motor insurance could be bought in under two minutes using a conversational interface without the burden of scrolling through twelve pages of fine print? What if I only said what I needed, and a modern LLM suggested the best products based on my particular situation? Or take claims, the ultimate moment of truth in insurance. What if a property claim could be assessed and settled within a few minutes, rather than a week of back-and-forth emails and unclear updates?What if customers never had to chase insurers for information, because the process was so seamless that the next step always reached them first? These are not pipe dreams. They are entirely achievable, with the right focus on operational design, digital infrastructure, and customer-centric thinking. Traditional Products Still Run the Business While we love to talk about disruption, the vast majority of written premiums globally still come from traditional product lines: motor, home, health, and life. These products are familiar to everyone. And they carry the kind of long-term trust that embedded offers or parametric experiments are still trying to earn. If we want to future-proof the industry, we should not abandon these pillars. We should strengthen them by making them easier to understand, easier to purchase, more transparent to claim on, and more responsive throughout the customer lifecycle. Think automation and AI Agents, the future of smartly orchestrated workflows. The good news is that modernising the traditional products does not require reinvention. It requires the maturity and discipline to get the basics right. Operational Excellence Is the New Innovation It might not sound sexy, but fixing operations is where the magic happens. Operations are where expectations are met – or not. Where trust is built – or lost.Where cost savings are made – or wasted. We must simplify overly complex processes, orchestrate workflows to reduce inefficiencies, digitise and streamline claims handling. By enabling modern servicing through technologies like AI agents or rule-based automation, insurers can radically improve the customer experience and free up resources to focus on what really matters. You do not have to change the product to change the game.Sometimes, the real innovation is in making things finally work the way they should have all along. A New Era of Innovation Leadership The insurers that will win the next decade are not just the ones that launch new things; they are the ones that deliver operational excellence and innovation on the core business. They will be known not for how futuristic their website looks, but for how easy it is to buy a policy, how painless it is to file a claim, and how consistently they show up for customers when it matters most. They will turn operational excellence into a visible, differentiating strength—not something buried behind the scenes, but something customers feel and value. Because in a market full of promises, execution still matters. The Bottom Line If we want innovation to mean something in insurance, we have to broaden our definition. Creating new products is fancy, but whatever we do has to work. And the smartest move insurers can make today is not always to chase the next big thing. It is to make the existing big things easier, faster, and more human. Sometimes, innovation is not a launch, but something more effective, like automation and a boost to customer experience. And that is exactly what this industry needs more of.

How AI Agents Will Reshape Claims and Customer Service

Leave a Comment | Digital Transformation, NextGen Insurance |

AI Agents are quietly shaping insurance claims and customer service.  It is often said that change in insurance is slow – until it is not. Behind the scenes, smart, visionary companies work on creating the future of insurance services. Welcome to the era of AI agents. Interestingly, we do not speak about fancy customer apps or shiny front-end portals. The change happens in the plumbing, deep in operations, where decisions are made, claims are processed, and real value is won or lost. We are entering the age of AI agents. But not the kind that write (often bad) poetry or generate marketing blurbs. I mean structured, goal-oriented agents that can coordinate tasks, follow logic, and support real business processes – insurance processes. This matters more than we might think. What is an AI Agent? Let`s start by defining what an AI Agent is. No, it is not a chatbot. Not a voice assistant. An AI agent is more like a digital teammate. For example, let`s think of an AI Agent that processes a claim: it gathers documents, triggers validations, updates systems, and even notifies humans when they need to analyse a complex case.. AI is not replacing people. It rather allows them to work on value-added, creative tasks by handling the repeatable, invisible, frustratingly manual work that clogs up most insurance operations today. Imagine having hundreds of these agents working behind the scenes, keeping processes moving while your team focuses on the exceptions, the complex cases, and, most importantly, customer relationships. Why Claims and Customer Service Are the Natural Starting Points for AI Agents Claims are arguably the moment of truth for every customer. This is the whole point of buying insurance – to get help when the unthinkable happens. And yet, our industry has a poor reputation when it comes to servicing customers when they need it the most. Insurers have spent years trying to modernise their claims processes. Most have achieved partial automation, but very few can say the journey is seamless from FNOL to settlement. The real blockers are not just technology, but process fragmentation, manual handovers, and lack of orchestration. Customer service faces the same challenge. Insurers have focused more on cost-cutting and nearshoring than on customer experience. And the consequences are visible – frustrating queues, answers in line with the rules, but far from solving the customer`s problem. Ultimately, it is not about replying faster; it is about resolving issues efficiently, across departments and systems that were never designed to work together. This is where AI agents, powered by orchestration engines, become game-changers. First, you do not need to rebuild your core platforms or endure months of integration headaches. The AI Agents simply slip into the existing chaos and start making sense of it.  They connect siloed systems that were never meant to speak to each other, like digital translators at a dysfunctional family dinner. They can triage incoming requests, route tasks to the right systems or people, and follow up with robotic persistence – no reminders needed, no sticky notes involved.  And unlike human teams stretched across time zones and inboxes, they work 24/7 without breaks, burnout, or Monday morning moods. They are not here to impress; they are here to get the job done quietly, efficiently, and without ever asking for a raise. Beyond the Hype There is no shortage of hype. We have seen demos that look sleek but break in the real world. The insurance industry does not need more surface-level digital tools. It needs infrastructure that works, even when the rules are messy and the systems are old and too expensive to replace. AI agents, when used properly, are not cosmetic. They are back-end enablers. They do not replace judgment; they enhance flow. And when paired with strong orchestration platforms, they can reduce errors, increase consistency, and dramatically cut down handling times. For sure, you might want to use AI Agents for the hype or a better image in front of investors. But the primary objective of automation is getting the work done faster, better, and in a way that lets people focus on what matters. How to start with AI Agents in Claims and Customer Service The beautiful part of AI Agents automation is that you can start without doing a dramatic tech overhaul or a “burn it all down” transformation. Insurers simply need to do two things, both less glamorous than a keynote speech, but far more effective.  First, take a hard, honest look at current processes: where is the friction, the waste, the duplicated effort, the unnecessary handover? No filters, no fluff – just a sober inventory of how things really work (or do not).  Second, explore lightweight orchestration layers that can act like digital glue, sitting quietly between systems and triggering AI agents to handle the repetitive stuff no one enjoys.  This is not moonshot territory. It is practical, focused, and deeply operational – the kind of transformation that does not make headlines, but does make life easier. And yes – it can be done. The Bottom Line AI agents will not revolutionise insurance in one big bang. But they will quietly start transforming how work gets done. They will reduce delays, improve accuracy, and make life better for the people who process claims and serve customers every day. In the long run, that is how change sticks – not with hype, but with flow. If that sounds unsexy, good. The real revolution often is quiet and effective.