InsTech - insurance & innovation with Matthew Grant & Robin Merttens

In this episode, Matthew Grant sits down with Nicola Turner and Alex Ley, co-founders of Scrub AI, to explore one of the most pressing strategic questions facing insurers today: Build vs Buy in the age of generative AI.  Five years into building an AI-driven data cleansing platform for carriers and brokers, Nicola and Alex have seen the market shift from scepticism to urgency. Boardrooms are now asking how AI is being embedded into underwriting workflows, and whether those capabilities should be developed internally or sourced from specialists.  Drawing on their experience building deterministic AI models for exposure data and catastrophe modelling, they offer a grounded perspective on what works, what breaks and where the real risks sit.  At the heart of the discussion is a simple truth: getting to 80% is easy. Getting the final 20% right is where strategy, domain expertise and long-term thinking matter most.  In this conversation, Nicola and Alex share:  Why Build vs Buy has intensified as generative AI moves from experimentation to executive priority  How investor pressure and board-level scrutiny are shaping AI strategy inside large carriers  Why generative AI can accelerate development but does not remove the complexity of insurance data  The danger of plausible but wrong outputs in exposure management and catastrophe modelling  Why deterministic AI still plays a critical role in delivering consistent, renewal-ready data  How inconsistent data cleaning can distort underwriting decisions and renewal pricing  The hidden cost of technical debt when insurers attempt to build internally  Why maintaining and iterating ai tools is often harder than building the first version  If you like what you’re hearing, please leave us a review on whichever platform you use or contact Matthew Grant on LinkedIn.  Sign up to the InsTech newsletter for a fresh view on the world every Wednesday morning.

In this episode, Robin Merttens sits down with Frank Perkins, CEO and Co-founder of inari, to explore what it really takes to build and scale a modern MGA in 2026.  From founding an insurance business himself to leading a technology company serving specialist MGAs across Europe, Frank brings a rare dual perspective. He understands both the pressure of getting premium through the door and the responsibility of building systems that underwriters actually want to use.  As private equity capital accelerates into the sector and niche, digital-first MGAs proliferate across continental Europe, the conversation turns to speed, integration and the quiet evolution of the underwriting workbench.  In this conversation, Frank shares:  Why technology literacy is now firmly in the hands of business users, not just IT departments  How the rise of highly specialised MGAs is reshaping what underwriting platforms need to deliver  Why “rip and replace” transformation programmes are giving way to orchestration and coexistence  How AI is materially accelerating integrations and onboarding, cutting rollout times from months to days  The difference between generic AI tooling and insurance-specific intelligence  Why speed of execution is becoming a defining competitive advantage  What a tightening market cycle will mean for operational efficiency  Why continental Europe may offer the next major growth wave for MGAs  How culture and domain expertise can matter as much as code in a crowded market  If you like what you’re hearing, please leave us a review on whichever platform you use or contact Robin Merttens on LinkedIn.  Sign up to the InsTech newsletter for a fresh view on the world every Wednesday morning.

In this episode, we bring you a live panel from InsTech’s May event at CodeNode, exploring how automation is reshaping claims in the Lloyd’s and London market — and why the belief that specialty is too complex to automate no longer stands.  Moderated by Matthew Grant, CEO of InsTech, the panel features Simon White, Chief Claims Officer at Apollo, Aidan O’Neill, Founder and CEO of DOCOsoft, and Zoe Woods, Claims Improvement Manager at Lloyd’s.  Specialty claims have long been viewed as too bespoke, too nuanced and too reliant on human judgement for automation to play a meaningful role. But as underwriting becomes algorithmic and distribution turns digital, claims can no longer lag behind.  This conversation moves beyond theory to evidence. Automation is already embedded in live workflows across the market. The firms adopting early are seeing measurable operational gains.  In this conversation, they share:  Why the myth that specialty claims cannot be automated is finally breaking down  How Apollo processed more than 23,000 claims through automated checks, cutting handling times to under a working day  What happens when you ask claims handlers to map every task they repeat on each file  Why automation should augment decision-making rather than create black boxes  How structured data and integrated dashboards unlock meaningful AI use cases  What Lloyd’s is doing to balance innovation with oversight in a syndicated market  Why modular, plug-and-play services are replacing large-scale transformation programmes  What specialty can learn from automation in motor and property lines  Why starting small with repeatable processes creates fast, tangible wins  How claims is shifting from cost centre to strategic differentiator  If you like what you’re hearing, please leave us a review on whichever platform you use or contact Matthew Grant on LinkedIn.  Sign up to the InsTech newsletter for a fresh view on the world every Wednesday morning.

What actually makes automated and enhanced underwriting work in practice?  In this episode, three early movers in automated underwriting share hard-earned lessons from building digital underwriting propositions that have survived real market cycles. Rather than theory or hype, this conversation digs into where technology genuinely creates advantage, where it does not, and how underwriting judgement remains central even in highly algorithmic models.  Drawing on experience across cyber, US property and digital facilities, the panel explores why complexity, not commoditisation, is often where automation delivers the greatest edge. From AI-driven cyber underwriting to high-cat surplus lines property and digitally distributed specialty products, each speaker explains how they chose their focus and what they learned along the way.  Key themes include the role of data discipline in sustaining AI-led underwriting, why platform design matters more than speed to market, and how underwriters’ roles are shifting from generalists to specialists embedded in algorithmic decision making. The discussion also tackles unstructured data, submission quality and why “no data, no deal” may become a defining principle of future underwriting models.  What you’ll learn in this episode:  Why complex risks can be better suited to automated and augmented underwriting than simple, commoditised ones  How AI and machine learning are being applied in live underwriting decisions, not just analytics  The importance of volume, homogeneity and risk differentiation when building algorithmic models  Lessons from re-platforming early digital products and avoiding long-term technical debt  How generative AI is changing data cleaning, exposure management and submission handling  What enhanced underwriting means for underwriter skills, careers and decision making  Featuring perspectives from Marek Shafer of Vave, Tom Squires of AEGIS London and Jonathan Spry of Envelop Risk, moderated by Matthew Grant of InsTech.  You can also watch the video version of this panel here.  If you like what you’re hearing, please leave us a review on whichever platform you use or contact Matthew Grant on LinkedIn.  Sign up to the InsTech newsletter for a fresh view on the world every Wednesday morning.

What happens when AI meets the backbone of the insurance industry - policy administration systems? In this episode, Liselotte Munk, CEO of Fadata, joins Robin Merttens to unpack how artificial intelligence is reshaping the software layer of insurance.  With candid insights into Fadata’s AI strategy, Liselotte reveals how the company is using AI to accelerate software development and reduce implementation costs while improving quality. She tackles the big question: will AI make policy admin systems obsolete? Her answer offers a pragmatic view on cost, complexity, compliance and collaboration.  In this conversation, Liselotte shares:  How AI is already streamlining configuration, documentation and testing in core systems Why the true opportunity lies in faster implementations and reduced transformation costs How the role of developers is shifting, and what this means for insurance talent Why insurers should invest in AI to enhance - not replace - their core platforms What the smartest insurers are doing now to future-proof operations in an AI-first world If you like what you’re hearing, please leave us a review on whichever platform you use or contact Robin Merttens on LinkedIn.  Sign up to the InsTech newsletter for a fresh view on the world every Wednesday morning.

In this episode, Robin Merttens is joined by Tobi Schneider, Sector Engagement Lead for Financial Services & FinTech at the Edinburgh Futures Institute, to unpack one of the most ambitious research initiatives currently shaping the future of AI risk in insurance. Backed by UKRI and developed in collaboration with AXA Group and three leading universities, the project aims to build a foundational blueprint for how insurers can understand, audit and underwrite emerging AI risks.  Tobi shares why the shift from traditional to generative and agentic AI has outpaced current risk frameworks, leaving insurers exposed to risks that are poorly defined, difficult to monitor and impossible to price using historic loss data. He explains how his team is exploring dynamic underwriting models, parametric solutions and novel assurance techniques like LLM-based judges and automated red teaming, all with the goal of enabling safer, more accountable AI adoption.  Ahead of the Agentic AI Half Day event, hosted in collaboration with AI Risk, Tobi Schneider and Lukasz Szpruch wrote an article The New Frontier: Managing and insuring generative and agentic AI risks, further exploring this topic.   In this conversation, Tobi shares:  Why AI systems that function “correctly” can still produce harmful or costly outcomes  How traditional insurance models fail in the face of opacity, model drift and dynamic learning  What makes AI risk so difficult to price and how parametric triggers can help bridge the gap  Why better assurance leads to better insurance, and how incentives can drive safer AI deployment  How continuous monitoring tools are being developed to audit AI models in real time  What today’s early AI insurance offerings (from the likes of Munich Re and Relm) are actually covering  The role of non-profit research in supporting commercial innovation without commercial bias  What insurers can do now to prepare for an AI-driven future even without historical data  If you like what you’re hearing, please leave us a review on whichever platform you use or contact Robin Merttens on LinkedIn.  Sign up to the InsTech newsletter for a fresh view on the world every Wednesday morning.

This week we bring you an episode of Bootstrap Confidential featuring InsTech’s very own CEO, Matthew Grant, who joined Charles Green in the latter half of 2025 to reflect on the eight-year journey of building InsTech from the ground up without outside funding, and with an intentional focus on sustainable growth.  Matthew’s route to growing InsTech wasn’t typical. With a background in risk, analytics and around 400 podcast episodes as a host, he brought a deep understanding of the insurance sector and what it takes to build a commercially viable, insight-led business. The result? A thriving community of over 30,000, a high-margin membership model and a successful exit achieved through discipline, focus and clear-eyed decisions.  In this conversation, Matthew shares:  Why he sees bootstrapping as risk management, not risk taking The importance of paying yourself from day one and how that shaped InsTech’s trajectory Lessons from testing (and killing) products that didn’t deliver Why hiring curious, early-career talent paid off What most founders get wrong about option schemes and equity How to handle financial stress without losing your team or your sanity Why co-founders matter and why investors aren’t a substitute The hard truth about building the business your customers want, not just the one you’d love to run  If you like what you’re hearing, please leave us a review on whichever platform you use or contact Matthew Grant on LinkedIn.  Sign up to the InsTech newsletter for a fresh view on the world every Wednesday morning.

In this episode, Robin Merttens is joined by Andy Yeoman, CEO of Concirrus, to unpack how a key player in marine insurance tech has reinvented itself as a core platform provider for the specialty market, and what that transformation says about where the industry is heading.  Andy shares the thinking behind Concirrus’ pivot from ship tracking to full risk lifecycle processing, what it takes to build end-to-end technology in just 18 months, and why underwriters, not just CTOs, are now leading the charge on system change.  In this conversation, Andy shares:  Why marine was just the beginning and why modern platforms must serve multiple lines with depth, not just breadth  What today’s insurers really want from core systems: speed, interoperability and business outcomes  How Concirrus became an AI-first company and what that’s meant for product delivery, talent and culture  The rise of the tech-fuelled MGA and why they’re now the “risk entrepreneurs” to watch  How verticalised platforms are winning over underwriters by solving for class-specific nuance  What the shift from admin-heavy roles to empowered underwriting means for job satisfaction and talent retention  Why managing change is as important as building tech and what Concirrus learned from its own internal AI adoption  What’s next for insurance infrastructure as constraints fall away and innovation accelerates If you like what you’re hearing, please leave us a review on whichever platform you use or contact Robin Merttens on LinkedIn.  Sign up to the InsTech newsletter for a fresh view on the world every Wednesday morning.

How can AI weather models improve the accuracy and scale of catastrophe modelling? Matthew Grant is joined by David Wood, Managing Director at JBA Risk Management, and Jochen Papenbrock, Head of Financial Technology (EMEA) at NVIDIA, to explore how accelerated computing is unlocking new ways to simulate and manage flood risk. JBA has long been a pioneer in flood modelling, while NVIDIA’s GPU technology has helped drive the recent breakthroughs in AI and generative modelling. Together, they discuss how high-resolution simulations, new ensemble methods and open-source tools are pushing the limits of what’s possible in climate and catastrophe analytics. Key Talking Points: The early bet – how JBA’s adoption of GPU computing over a decade ago made national-scale flood mapping possible From gaming to GenAI – how NVIDIA's evolution from graphics to AI led to the development of physics-informed weather models Ensemble power – why running 1,000+ simulations helps capture more extremes than the historic record ever could Event sets reimagined – how AI models are enabling richer, more diverse flood scenarios for Europe and beyond Real-time relevance – the potential to use AI models to simulate how a flood might unfold, as it’s happening Making AI usable – how Earth-2 Studio and open-source frameworks are opening up generative models to catastrophe modellers Proving value – how NVIDIA and JBA worked together to quantify the benefits of faster, more flexible modelling approaches Looking ahead – why cross-sector collaboration will be essential to turn acceleration into real-world impact If you like what you’re hearing, please leave us a review on whichever platform you use or contact Matthew Grant on LinkedIn.  Sign up to the InsTech newsletter for a fresh view on the world every Wednesday morning.

In this episode, Robin Merttens is joined by Dr Thomas Kuhnt (HDI Global SE), Ed Ackerman (Qover) and Vincent De Ponthaud (AXA) for a rare C-suite perspective on Agentic AI — what it is, how it's being deployed and why senior leaders are walking a tightrope between bold innovation and operational risk. Agentic AI promises transformative value, but for decision-makers at the top, it also brings real uncertainty. What do you build vs. buy? How do you prove ROI? And how do you prevent over-trusting agents that are inherently probabilistic? In this conversation, Thomas, Ed and Vincent share: Why Agentic AI is different from past tech trends and why this one feels real The cultural and leadership challenge of balancing excitement with governance How AXA and HDI are enabling safe experimentation at scale across complex organisations How Qover is building 20+ AI agents to automate claims micro-tasks — and when they build vs. buy What customers really think about AI agents  and why nearly none opt out The risks of shadow AI and why IT needs to move faster than ever Why “human in the loop” is flawed and how user trust in AI could become a blind spot What’s missing: industry standards, agent evaluation tools and new roles like “agent managers” The case for cautious iteration, deep collaboration and constant re-evaluation Sign up to the InsTech newsletter for a fresh view on the world every Wednesday morning.

In this episode, Claire Souch is joined by Tom Philp, CEO of Maximum Information; James Lay, AVP of Product Management at Verisk; and Stephen Martin, Head of Catastrophe Modelling at Westfield Specialty, for a timely discussion on the future of catastrophe model evaluation, and why it's no longer enough to simply trust what’s in the black box. As new specialist model vendors emerge and market expectations evolve, the panel unpacks a growing demand for transparency, interoperability and smarter ways to adopt models that fit real-world portfolios. At the heart of the conversation is a shared belief: the industry doesn’t just need more models, it needs better ways to evaluate and use them. In this conversation, they explore: Why traditional model validation no longer meets the needs of modern risk teams The shift from 'black box' outputs to meaningful model evaluation that supports business decisions How tools from Maximum Information and Verisk’s Model Exchange reduce the burden on small or lean teams The role of Oasis as a framework for opening up access across multiple model vendors Why standardisation and open data formats are essential for meaningful interoperability The growing role of niche vendors in reshaping perceptions of model transparency How automation is changing the regulatory and investor reporting game Why this is more than a tech upgrade—it's a cultural reset in catastrophe modelling Sign up to the InsTech newsletter for a fresh view on the world every Wednesday morning.

In this episode, Brian Owens is joined by Dana Foley (Head of Catastrophe Research at Chaucer), Joss Matthewman (Chief Revenue Officer at Reask) and Olivia Sloan (Head of Catastrophe Products at Fathom) to explore the growing influence of specialist model vendors in catastrophe risk modelling and why they’re anything but “niche”. With decades of combined experience across underwriting, model development and scientific research, the panel discusses how climate change, regulatory pressure and the need for portfolio-specific insight are pushing insurers to reconsider single-platform dependency. They explore how new vendors are filling gaps left by traditional models offering science-led, transparent and highly customisable solutions tailored to specific business needs. Drawing on their respective roles across the risk ecosystem, the panellists explain why the return to multi-modelling is gaining momentum and how platforms like Oasis are helping democratise access to emerging tools. In this conversation, the panel explores: Why “niche” models are proving critical in underserved perils, regions and use cases The evolution from black-box outputs to transparent, collaborative frameworks How science-first models enable faster innovation and user-driven risk views What’s enabling and blocking wider adoption of multi-modelling approaches How Fathom and Reask are using AI and machine learning to improve model fidelity Why regulatory scrutiny and climate change demand a more agile modelling approach The role of open platforms like Oasis in supporting innovation and vendor access What insurers need to consider when building a tailored, future-ready modelling strategy Sign up to the InsTech newsletter for a fresh view on the world every Wednesday morning.

Introduction In this episode, Robin Merttens is joined by Jack Miller, CEO and Co-founder of nettle, to explore how generative AI is being applied to one of insurance’s most complex and resource-constrained challenges: risk engineering. Jack shares how his work at McKinsey, leading AI transformations for insurers, exposed him to the inefficiencies in assessing commercial property risks and how that inspired Nettle’s founding. From mass retirements of risk engineers to the reality that most properties are never physically assessed, Jack outlines why the status quo is unsustainable and how AI can help underwriters make faster, more informed decisions without sacrificing depth or judgement. He explains how nettle is already working with insurers like Allianz to roll out configurable, production-ready tools that reduce manual burden, unlock previously inaccessible insights and integrate directly into existing underwriting platforms. In this conversation, Jack shares: Why risk engineering is facing a capacity crunch and how that affects underwriting quality The surprising statistic that sparked nettle’s creation: 97.5% of properties are never visited How generative AI can enhance, not replace, expert judgement in high-value underwriting Why depth, not breadth, is the key to building meaningful AI solutions in insurance Lessons from building a product insurers can implement in weeks not years The importance of involving underwriters in AI adoption from day one What most insurers get wrong about pilots, procurement and “proper” GenAI strategies How nettle’s partnership with Allianz helped shape a scalable, enterprise-ready product Why commercial P&C is the perfect proving ground for next-generation InsurTech If you like what you’re hearing, please leave us a review on whichever platform you use or contact Jack Miller or Robin Merttens on LinkedIn. Sign up to the InsTech newsletter for a fresh view on the world every Wednesday morning.

In this episode, Richard Gunn, President & CRO at hyperexponential, joins host Matthew Grant to share the inside story of hyperexponential's expansion journey from the UK to the US, and how the company is reshaping pricing and underwriting in the insurance sector. Richard reflects on seven years at hyperexponential, starting as the first non-engineering hire to now leading a fast-growing US team in New York. He explains how hyperexponential has evolved from a pricing platform into a broader decision infrastructure provider, with tools spanning triage, portfolio intelligence and AI-powered underwriting support. In this conversation, Richard shares: Why hx's "pro-code" platform sits between build vs buy, offering flexibility without compromising enterprise-grade credibility How the team landed major US clients before even setting up a US office The strategic lessons behind building trust with US insurers, from culture to communication The practical impact of generative AI and "vibe coding" in hx's product development and internal operations Why hx believes AI isn't about replacing roles but redrawing their boundaries to boost effectiveness What it's like to move across the Atlantic with a young family while scaling a tech business How New York's transient tech culture supports rapid networking and hiring His predictions on shifting insurer priorities from growth to profitability Resources & Mentions: AI Daily Brief (podcast recommendation) Book: Papillon by Henri Charrière Previous guests: Amrit (hyperexponential Co-founder & CEO), Marcus Ryu (Co-founder and Chairman at Guidewire and Partner at Battery Ventures) If you like what you’re hearing, please leave us a review on whichever platform you use or contact Richard Gunn or Matthew Grant on LinkedIn. Sign up to the InsTech newsletter for a fresh view on the world every Wednesday morning.

In this episode, Robin Merttens is joined by Tim Hardcastle, CEO and Co-founder of INSTANDA, to reflect on what it takes to turn a contrarian vision into a global insurtech platform and what the next decade of innovation might look like. Tim left a senior role at Hiscox to build a no-code platform for insurers at a time when most said it couldn’t be done. Ten years on, INSTANDA powers operations around the world and is gearing up for its next big leap. This conversation revisits the early sparks of that journey, including a memorable chat at the Royal Exchange, and dives into the personal and professional lessons Tim has gathered along the way. In this conversation, Tim shares: Why the earliest versions of INSTANDA were built despite zero market demand How a falling out with a boss became the unexpected catalyst for entrepreneurship The reality of scaling a tech company in insurance including a motorbike sale to make payroll Why belief, timing and architecture were crucial to gaining traction How humility shaped both leadership style and product design What it means to lead through survival, scale and reinvention His view on legacy, moonshot AI and the importance of letting go What’s fuelling his passion ten years in and where the next decade might lead This one is part retrospective, part roadmap and full of insight for anyone thinking long-term about change in insurance. Sign up to the InsTech newsletter for a fresh view on the world every Wednesday morning. Continuing Professional Development This InsTech Podcast Episode is accredited by the Chartered Insurance Institute (CII). By listening, you can claim up to 0.5 hours towards your CPD scheme. By the end of this podcast, you should be able to meet the following Learning Objectives: Describe the early challenges of launching a no-code insurance platform in a sceptical market. Explain how belief, architecture and timing contributed to INSTANDA’s success and scalability. Define the role of humility in effective insurtech leadership and product design. If your organisation is a member of InsTech and you would like to receive a quarterly summary of the CPD hours you have earned, visit the Episode 382 page of the InsTech website or email cpd@instech.co to let us know you have listened to this podcast. To help us measure the impact of the learning, we would be grateful if you would take a minute to complete a quick feedback survey.

In this episode, Robin Merttens sits down with Haris Khan and Arved Pohlabeln, co-founders of Novee, to unpack what’s broken in specialty underwriting — and how AI is finally in a position to fix it. Having met as consultants at Deloitte, Haris and Arved kept encountering the same themes: overworked underwriters, inconsistent submissions, and transformation efforts that rarely made a real difference. That frustration turned into action. Today, they’re building Novee — an AI assistant designed specifically for underwriters, combining insight generation with targeted automation. In this conversation, Haris and Arved share: Why underwriting processes remain complex, fragmented and hard to standardise What makes specialty submissions so variable — and why every case feels like an edge case How Novee delivers value in two ways: by surfacing better risk insights and automating manual tasks Why underwriters are embracing AI tools now — not resisting them What it takes to get live in weeks, not months, with meaningful value The real-world impact of extracting information from unstructured submissions How they raised £1.6 million in seed funding and what they’re doing with it Why verticalised AI is outperforming generic solutions in insurance What it means to redesign underwriting interaction patterns — and why inbox to insight is the future The case for using AI before you fix your data, not after Sign up to the InsTech newsletter for a fresh view on the world every Wednesday morning. Continuing Professional Development This InsTech Podcast Episode is accredited by the Chartered Insurance Institute (CII). By listening, you can claim up to 0.5 hours towards your CPD scheme. By the end of this podcast, you should be able to meet the following Learning Objectives: Describe the real-world challenges underwriters face when working with inconsistent, unstructured submissions. Define the concept of verticalised AI in the context of specialty underwriting and how it differs from generic AI solutions. List the specific ways Novee supports underwriters through both insight delivery and task automation. If your organisation is a member of InsTech and you would like to receive a quarterly summary of the CPD hours you have earned, visit the Episode 381 page of the InsTech website or email cpd@instech.co to let us know you have listened to this podcast. To help us measure the impact of the learning, we would be grateful if you would take a minute to complete a quick feedback survey.

In this episode, Matthew Grant sits down with Jonathan Rake, CEO of Risk Data Solutions at Swiss Re, to explore how a major reinsurer is building data and analytics as core capabilities beyond traditional risk‑transfer. Jonathan explains why the shift matters, how analytics are being embedded in real‑time workflows, and what insurers and corporates should focus on as risk becomes more interconnected and dynamic. In this conversation, Jonathan shares: Why Swiss Re launched Risk Data Solutions and how it leverages internal analytics for client value How “certainty of insight” and real‑time decision‑making are redefining insurance workflows The differing risk‑analysis needs of large corporates versus insurers, and what each must prioritise How Swiss Re approaches partnerships: enabling versus enriching, and why you cannot go it alone The acquisition of Fathom (UK) and how model‑blending is raising the accuracy bar in catastrophe modelling His approach to leadership, maintaining balance outside work and keeping pace with change A bold prediction for 2026 — and the book he recommends to anyone interested in adventure, risk and innovation 'A Voyage for Madmen' by Peter Nichols If you like what you’re hearing, please leave us a review on whichever platform you use or contact Jonathan Rake or Matthew Grant on LinkedIn. Sign up to the InsTech newsletter for a fresh view on the world every Wednesday morning. Continuing Professional Development This InsTech Podcast Episode is accredited by the Chartered Insurance Institute (CII). By listening, you can claim up to 0.5 hours towards your CPD scheme. By the end of this podcast, you should be able to meet the following Learning Objectives: Specify the tools and workflows that allow insurers to consume insights directly within underwriting platforms. Measure the business case for embedding analytics in risk workflows versus maintaining separate data functions. Produce a clearer understanding of how large insurers are operationalising resilience through data, modelling and partnerships. If your organisation is a member of InsTech and you would like to receive a quarterly summary of the CPD hours you have earned, visit the Episode 380 page of the InsTech website or email cpd@instech.co to let us know you have listened to this podcast. To help us measure the impact of the learning, we would be grateful if you would take a minute to complete a quick feedback survey.

Catastrophe models have come a long way - but are decision-makers keeping up? In this panel from InsTech’s The future of catastrophe risk: where science meets reality, Alice Kaye (Inigo), Caroline McMullan (Verisk) and host Dickie Whitaker (Oasis LMF) confront the challenges of turning sophisticated risk models into clear, actionable decisions. Together, they explore why uncertainty is often more valuable than the average, how human biases still cloud our understanding of extreme events, and what’s needed to close the communication gap between modellers, underwriters and boards. This conversation gets real about the behavioural, structural and cultural shifts the insurance industry must make to better navigate risk in an increasingly volatile world. What you'll learn in this episode: Why point estimates often mislead decision-makers - and how scenarios can bring data to life The role of behavioural bias in catastrophe risk assessment (think hindsight, anchoring and mean reversion) How leading insurers like Inigo are integrating model outputs into daily underwriting and board-level strategy The importance of early-career training to build confidence in managing uncertainty How the interface between climate science, data science and vulnerability modelling is evolving Why pre-competitive collaboration with academia is critical for the industry's future If you like what you’re hearing, please leave us a review on whichever platform you use or contact Matthew Grant on LinkedIn. Sign up to the InsTech newsletter for a fresh view on the world every Wednesday morning. Continuing Professional Development This InsTech Podcast Episode is accredited by the Chartered Insurance Institute (CII). By listening, you can claim up to 0.5 hours towards your CPD scheme. By the end of this podcast, you should be able to meet the following Learning Objectives: Identify gaps in skills and training that hinder effective risk modelling and decision-making. Produce more informed underwriting decisions by integrating multiple views of risk. Summarise best practices for bridging the gap between research, modelling and commercial application. If your organisation is a member of InsTech and you would like to receive a quarterly summary of the CPD hours you have earned, visit the Episode 379 page of the InsTech website or email cpd@instech.co to let us know you have listened to this podcast. To help us measure the impact of the learning, we would be grateful if you would take a minute to complete a quick feedback survey.

In this special episode of the podcast, originally hosted by Indico Data’s Unstructured Unlocked, Matthew Grant, CEO of InsTech, joins Tom Wilde and Michelle Gouveia to discuss how insurers are harnessing third-party data and AI to make more informed, efficient underwriting decisions. With over 25 years in catastrophe modelling and analytics, Matthew shares his view on where the real innovation is happening and where insurers are still facing friction. From the rising value of external data sources to the operational impact of generative AI, the conversation is packed with insights that go beyond the buzzwords. InsTech is sharing this episode to highlight the practical challenges and opportunities facing carriers and reinsurers as they modernise their approach to risk. What you’ll learn Why many insurers still struggle to access the most basic risk data What third-party data needs to prove before it’s trusted in underwriting How AI is changing both the speed and depth of catastrophe modelling When it makes sense for carriers to build proprietary models—and when it doesn’t What reinsurers have taught the market about effective model use The quiet power of improving underwriting efficiency, not just accuracy How better data and analytics can help insurers write more risk with more confidence If you like what you’re hearing, please leave us a review on whichever platform you use or contact Matthew Grant on LinkedIn. Discover more episodes of Tom Wilde's and Michelle Gouveia's podcast at Indico Data's Unstructured Unlocked. Sign up to the InsTech newsletter for a fresh view on the world every Wednesday morning. Continuing Professional Development This InsTech Podcast Episode is accredited by the Chartered Insurance Institute (CII). By listening, you can claim up to 0.5 hours towards your CPD scheme. By the end of this podcast, you should be able to meet the following Learning Objectives: Measure the practical value of generative AI in improving underwriting efficiency and catastrophe modelling accuracy. Specify the thresholds third-party data must meet—cost and confidence—before it can support underwriting decisions. Explain how insurers are approaching the build vs buy decision when it comes to proprietary AI models. If your organisation is a member of InsTech and you would like to receive a quarterly summary of the CPD hours you have earned, visit the Episode 378 page of the InsTech website or email cpd@instech.co to let us know you have listened to this podcast. To help us measure the impact of the learning, we would be grateful if you would take a minute to complete a quick feedback survey.

What are we still missing in catastrophe modelling and how can we close the gap? As part of InsTech’s The Future of Catastrophe Risk: Where Science Meets Reality event, this expert panel explored the limitations of current catastrophe models and how the insurance industry can evolve its approach to risk. Hosted by Ludovico Nicotina (Inigo), with insights from Sandra Hansen (Guy Carpenter) and Paul Wilson (Twelve Securis), the discussion focused on where models fall short, how emerging risks are challenging traditional assumptions and what it will take to build more resilient, climate-aware modelling frameworks. In this conversation, the panel explores: What current models overlook — from unmodelled sub-perils to social and infrastructure vulnerabilities How inter-annual clustering and systemic effects drive outsized losses The tension between increasing model flexibility and responsible use of adaptation features Whether vendors are providing enough transparency to support custom views of risk How the industry can better incorporate future climate states into today’s modelling tools The case for cross-sector collaboration and more open sharing of internal risk perspectives If you like what you’re hearing, please leave us a review on whichever platform you use or contact Matthew Grant on LinkedIn. Sign up to the InsTech newsletter for a fresh view on the world every Wednesday morning. Continuing Professional Development This InsTech Podcast Episode is accredited by the Chartered Insurance Institute (CII). By listening, you can claim up to 0.5 hours towards your CPD scheme. By the end of this podcast, you should be able to meet the following Learning Objectives: Identify best practices for using adaptation and resilience features within CAT models responsibly. Produce informed strategies for interpreting and adjusting model outputs to reflect internal views of risk. Summarise the practical steps insurers and risk managers can take to bridge the gap between science and real-world application. If your organisation is a member of InsTech and you would like to receive a quarterly summary of the CPD hours you have earned, visit the Episode 377 page of the InsTech website or email cpd@instech.co to let us know you have listened to this podcast. To help us measure the impact of the learning, we would be grateful if you would take a minute to complete a quick feedback survey.