Full Episodes | Insurtech Leadership Podcast

The Insurtech Leadership Podcast
  • 4.4 (21)
  • Entrepreneurship
  • Updated Weekly

Full-length episodes and replays from The Insurtech Leadership Podcast. New here? Start with the newest episode and work backwards.

  1. 5d ago

    The $2M Mistake: How Global Insurtechs Burn Cash Entering the U.S.

    Introduction International tech companies burn through $2 million trying to crack the US market every day. Not because their product is wrong. Because they hire a sales team before they have a sales motion. Dan Griffith has spent 15 years watching this mistake play out—and building the playbook to prevent it. Griffith is the founder of Greater Gain Group, a go-to-market firm that helps software and technology companies—most of them international—land and scale in US insurance, financial services, and healthcare markets. As the first US hire for a South African company, he scaled it from $3M to $150M in three years. Those hard lessons became the foundation for Greater Gain Group's 90-day go-to-market framework. In this conversation, Josh Hollander and Griffith dig into why the unicorn sales hire is the most dangerous move an international founder can make, what has to be true before you put a rep in a seat, and where the insurtech market is creating real demand for cross-border go-to-market right now. Guest Bio Dan Griffith is the Founder and Principal Consultant at Greater Gain Group, a go-to-market consultancy specializing in helping international software and technology companies enter and scale in the US insurance, financial services, and healthcare markets. With 30 years in enterprise sales and marketing, he has served as a first US hire and go-to-market architect for companies entering from South Africa, France, Europe, and beyond. His 90-day framework takes founders from "we're entering the US" to a repeatable sales motion—without the $2M mistake. Key Topics • The $2M mistake — A VP of Sales, two account executives, a marketing hire, an office, and conference travel. You're at $2M in under a year with nothing built and no pipeline. Fifty percent of Greater Gain Group's clients have already made this mistake before they call. • Don't hire salespeople (yet) — The tell that a founder is about to flame out: they say they're going to hire a sales team. Griffith's rule: build the sales motion before you build the team. A rep can't fly a plane that hasn't been designed. • The founder has to come — For companies under $50M, having a founder on the ground for early US conversations is the strategy. Hearing objections directly is how you convert from founder-led to team-led sales—the transition Greater Gain Group is built to facilitate. • Three to five segments, not one — Pick no fewer than three and no more than five market segments, understand the pain in each, and build an outreach engine that generates sales conversations—not leads. Leads have no value. • Paid pilots and MSA reality — US buyers do paid pilots. Free pilots signal low value and waste time. On contracts: insurance companies have ten times more lawyers than you. Know your non-negotiables, keep the list short, and don't let MSA rigidity keep you out of the market. • Price higher than you think — International companies consistently underprice the US market by 20–40%. Corporate budgets at US insurers are significantly larger than abroad. One client was surprised a health insurer's CTO had $475K of year-end budget left for a POC they'd hesitated to price. Notable Quotes "They hand you your laptop and say, go sell us some stuff. I learned a lot of hard lessons on how not to do things." "If you don't bring value, you're out. The US market is transactional. As much as I hate to say it." "A lead has no value. Build an outreach engine that generates sales conversations." "Your only competitor is the status quo. If you're getting into a feature-function-benefit argument, you've already lost." Resources Guest: • Greater Gain Group: https://www.greatergaingroup.com • Dan Griffith on LinkedIn: https://www.linkedin.com/in/dangriffithsr/ Host & Organization: • Joshua R. Hollander on LinkedIn: https://www.linkedin.com/in/joshuarhollander/ • Horton International (USA): https://www.horton-usa.com/ • Insurtech Leadership Podcast (LinkedIn Showcase): https://www.linkedin.com/showcase/insurtech-leadership-show Subscribe & Review If you enjoyed this episode, subscribe on your favorite platform and leave a review. The Insurtech Leadership Podcast is available on YouTube, Apple Podcasts, and Spotify.

    29 min

  2. 5d ago

    The $13B Last Mile: Why Leak Detection Never Gets Installed

    Introduction Non-weather water damage costs insurers $13 billion a year. Interior leaks account for 39% of all homeowner claims. And yet most carriers still treat prevention as a brochure recommendation—send the homeowner a discount offer, hope they find a plumber, and call it a program. Paul Wauquiez thinks that's why it isn't working. Wauquiez is the founder and CEO of Beagle Services, a water security company that solves the last-mile problem carriers and homeowners can't solve on their own: getting leak detection hardware actually installed, monitored, and maintained. A California-barred litigation attorney turned insurtech operator, he built the insurance carrier playbook at Flow Technologies before Moen acquired it. What he learned there—that the technology exists but deployment at scale does not—became the genesis for Beagle. In this conversation, Josh Hollander and Wauquiez dig into why the installation gap is where loss prevention falls apart, how the industry is shifting from carrot to stick on water shutoff requirements, and what Beagle's work with carriers like PURE tells us about where prevention programs are actually headed. Guest Bio Paul Wauquiez is the Founder and CEO of Beagle Services, a water security company operating across 17 states that installs, monitors, and maintains automatic water shutoff valves and leak detection systems for insurance carriers, brokers, and homeowners. Before founding Beagle, he built the insurance carrier go-to-market at Flow Technologies, which was later acquired by Moen (now Flow by Moen). He is a California-barred litigation attorney who came to insurtech through the startup world. Key Topics • The last-mile problem nobody solved — Leak detection technology has existed for over a decade. The gap isn't the hardware—it's professional installation, ongoing monitoring, and maintenance at scale. Carriers recommend devices; homeowners can't find qualified installers; the device sits in a box. Beagle exists to close that gap. • From carrot to stick — Carriers are shifting from discount incentives ("send us a photo of your installed valve") to hard underwriting requirements at specific coverage thresholds. High-net-worth carriers like PURE have led the way. Standard lines carriers are following. The stick is now backed by data. • The compliance illusion — A photo of an installed device and a paid invoice doesn't mean the system is on and actively protecting the home. The same problem exists with alarm systems: discounts are given, but nobody checks if the alarm was set before you left for vacation. Beagle's Watchdog product monitors device status—online, offline, alert conditions—in real time. • What Beagle does with the data — Watchdog ingests alert data across every installed system: high pressure, small drips, thermal expansion risk, shutoff frequency, device connectivity. When an alert fires, Beagle dispatches a service visit to fix the underlying problem—toilet flappers, angle stops, pressure regulators—before it becomes a claim. • Scaling a physical services business — Unlike SaaS, physical services don't go straight to margin as you grow. The key variable is drive time: how many installs can a technician complete per day in Atlanta, Los Angeles, or Dallas? Beagle grows market-by-market only when carrier partners generate enough demand to support a full-time local team, which drives economies of scale that lower costs for everyone. • AI can't turn a wrench — Beagle uses AI for route optimization and operational efficiency, and is training internal models as a knowledge base for field technicians and customer service. But the core product requires humans on-site at every property. No bot can cut the pipe. Notable Quotes "Most carriers still treat prevention as a brochure recommendation rather than an operational program." "You'd have a picture of the installed device and a paid invoice—but that doesn't necessarily mean the system is on and active protecting the home." "The AI can't turn a wrench. No matter how smart the valves get, you still have to put it on. Until that day comes, we'll be here." "Beagle's intent is to be a proactive, preventative maintenance plumbing company. All we do is referred-in work to help prevent leaks from occurring." Resources Guest: • Beagle Services: https://www.beagleservices.com • Paul Wauquiez on LinkedIn: https://www.linkedin.com/in/paulwauquiez/ Host & Organization: • Joshua R. Hollander on LinkedIn: https://www.linkedin.com/in/joshuarhollander/ • Horton International (USA): https://www.horton-usa.com/ • Insurtech Leadership Podcast (LinkedIn Showcase): https://www.linkedin.com/showcase/insurtech-leadership-show Subscribe & Review If you enjoyed this episode, subscribe on your favorite platform and leave a review. The Insurtech Leadership Podcast is available on YouTube, Apple Podcasts, and Spotify.

    28 min

  3. May 21

    Reinventing the Broker Experience: Tech, Trust, and the Future of Personal Lines

    Introduction What if the biggest gap in personal lines insurance technology isn't the consumer experience—it's the broker experience? Every major insurtech wave of the past decade has tried to disintermediate the agent. Jon Kelly thinks that's the wrong bet. In his view, the broker is the product in personal lines, and the tools they work with are embarrassingly behind. Kelly has been building at the intersection of insurance and technology since 1998, when he co-founded eCoverage—the first venture-backed startup to underwrite car insurance online. After selling SureHits in 2008, he spent years watching high-net-worth clients get onboarded with hundreds of questions spread across weeks of back-and-forth, proposals built in Excel, and data managed across disconnected systems. He called it "the Columbo experience"—always just one more thing. That frustration led him to co-found Kelly Klee Private Insurance in 2016 and build Discover, the platform powering it, from the inside out. Kelly Klee was acquired by Foundation Risk Partners in 2022. Now, as CEO of Modern Metric, he's selling Discover to the largest national brokers in the country. In this conversation, Josh Hollander and Kelly dig into the technology gap in personal lines, why enterprise-first was the right strategic bet, what it takes to hire high-agency people, and why trust is the ultimate product in this business. Guest Bio Jon Kelly is the Founder and CEO of Modern Metric, makers of the Discover platform for personal lines insurance distribution. His career began in 1995 at Mercer Management Consulting, advising Prudential, CNA, and Fireman's Fund. In 1998 he co-founded eCoverage, the first venture-backed startup to underwrite car insurance online, followed by SureHits (acquired by QuinStreet, 2008) and Kelly Klee Private Insurance (acquired by Foundation Risk Partners, 2022). He chairs Hometown Quotes, sits on the board of Great Range Capital, and earned a BA in Economics and Political Science from Stanford University. Key Topics • The missing layer in the tech stack — Independent agents have AMS systems for back-office accounting, CRMs for lead tracking, and form builders as pipes to carriers. But there is no purpose-built system for the client-facing workflow: data discovery, market presentation, and proposal delivery. That gap is what Discover was built to fill. • Relationship business vs. transactional business — The real split in personal lines isn't private client vs. mass market—it's relationship (multi-line) vs. transactional (monoline). Form builders work fine for monoline. They fall apart the moment complexity enters the picture. • Enterprise-first as a strategic decision — The most consequential decision at Modern Metric was targeting the largest national brokers from day one. Building for complex, enterprise-scale accounts forces architectural decisions that cannot be retrofitted later. You can scale down from enterprise; you cannot scale up from a form builder. Their first anchor tenant is a top-20 national broker. • The Uber Black analogy — If you order an Uber X and the Uber Black shows up, you're thrilled. If you order the Uber Black and the old Honda arrives, you're not happy. A platform built for simple transactions will never feel right in a complex private client context, no matter how much you add to it. • Hiring for high agency — The through line across all of Kelly's businesses: he hires for high agency. He looks for people who have clear motivations for every role on their resume. His favorite interview story: asking a candidate about their favorite exhibit at the natural history museum where they worked. The answer was "that was okay." They didn't get the job. • Trust as the ultimate product — Kelly's answer to what he'd want co-founders, teammates, and customers to say: that he delivered on what he said he would, that they got good value, and above all, that they can trust him. Trust is number one. Notable Quotes "I called it the Columbo because it was always just one more thing. Oh, your house is in a trust? Just one more question. I couldn't help think that maybe there were some issues with technology and personal lines, especially at the high end." "The whole process of how do you get the data in, how do you take that to market, how do you do your proposal—that's all done in paper and pencil, Excel and Word and Outlook." "If you order an Uber X and the Uber Black comes, you're thrilled. If you order Uber Black and the old Honda comes, you're not happy. You can't go from one to the other." "What I'd want them to say is that I delivered-that whatever I said I was going to do, I did, and that they got value out of it. More than anything, that they feel like they can trust me. Trust is number one." Resources Guest: • Modern Metric: https://www.modernmetric.com • Jon Kelly on LinkedIn: https://www.linkedin.com/in/jonkelly/ Host & Organization: • Joshua R. Hollander on LinkedIn: https://www.linkedin.com/in/joshuarhollander/ • Horton International (USA): https://www.horton-usa.com/ • Insurtech Leadership Podcast (LinkedIn Showcase): https://www.linkedin.com/showcase/insurtech-leadership-show Subscribe & Review If you enjoyed this episode, subscribe on your favorite platform and leave a review. The Insurtech Leadership Podcast is available on YouTube, Apple Podcasts, and Spotify.

    30 min

  4. May 21

    Rebuilding Underwriting From the Inside Out: The AI OS for Modern MGAs

    Introduction What if the real bottleneck in commercial insurance isn't distribution or pricing—it's the workflow itself? Nearly $100 billion of SME P&C insurance is placed every year using manual processes, disconnected systems, and data that lives in spreadsheets and email threads. Hamesh Chawla has spent the last four years building the infrastructure to change that. Before founding Mulberri in 2021, Chawla led product and technology at Edelman Financial Engines and Asurion. He came to insurance not as a lifer but as a technologist who saw an industry still running on 20th-century tooling. Mulberri is his answer: an AI operations platform connecting PEOs, brokers, SMEs, and carriers—from smart submission and risk scoring to quote-and-bind and certificate of insurance. In this conversation, Josh Hollander and Chawla dig into why the MGA market was the right pivot, what AI governance looks like when binding decisions carry real capital risk, and why the SME segment is the most underserved frontier in commercial insurance. Guest Bio Hamesh Chawla is the Co-Founder and CEO of Mulberri, an AI operations platform for MGAs, PEOs, brokers, and carriers serving the SME market. Before Mulberri, he was EVP and Chief Product & Technology Officer at Edelman Financial Engines, with prior roles at Asurion and Zephyr (acquired by SmartBear). He holds an MS in Computer Science from Texas A&M University. Mulberri has raised $10.8M from Eos Venture Partners, Altamont Capital Partners, MS&AD Ventures, and Hanover Technology Management. Key Topics • The $100B manual workflow problem — Nearly $100B of SME P&C is placed annually using ACORD forms emailed back and forth, loss runs parsed by hand, and decisions made without the data that exists in the market. Mulberri automates this stack. • From embedded insurance to AI operating system — Chawla explains why he pivoted from embedded distribution to building the workflow layer MGAs actually run on—ingesting unstructured data, structuring it through a GenAI OS, and routing decisions with full context. • AI governance when capital is at stake — When AI is binding real policies, black-box models get rejected. Mulberri surfaces claim propensity, frequency, severity, and loss ratio so underwriters can interrogate and trust the output. • The PEO channel as data and distribution — PEOs sit on firmographic and workforce data directly predictive of workers' comp risk. Embedding into that channel is both a data strategy and a go-to-market strategy. • Building for carriers, brokers, and SMEs simultaneously — Carriers need loss ratio visibility, brokers need submission efficiency, SMEs need straightforward access. Aligning all three is the hardest product problem in the space. Notable Quotes "Our mission since day one has been to leverage technology to complement underwriters' expertise—simplifying and streamlining the business insurance process while ensuring transparency." "The Risk Engine puts the information underwriters need at their fingertips to make fast, accurate decisions—not replacing them, but making them dramatically more effective." Resources Guest: • Mulberri: https://www.mulberri.io • Hamesh Chawla on LinkedIn: https://www.linkedin.com/in/hameshchawla/ Host & Organization: • Joshua R. Hollander on LinkedIn: https://www.linkedin.com/in/joshuarhollander/ • Horton International (USA): https://www.horton-usa.com/ • Insurtech Leadership Podcast (LinkedIn Showcase): https://www.linkedin.com/showcase/insurtech-leadership-show Subscribe & Review If you enjoyed this episode, subscribe on your favorite platform and leave a review. The Insurtech Leadership Podcast is available on YouTube, Apple Podcasts, and Spotify.

    30 min

  5. May 8

    Why Nobody Is Scoring the Road Ahead (And What It’s Costing Insurers)

    Introduction What if the most dangerous thing about a commercial fleet route could be identified before the truck ever left the yard? The insurance industry has spent decades pricing commercial auto risk using historical loss data and, more recently, real-time telematics. But neither tells you what's waiting around the next bend. The forward-looking layer has never existed. Goetz Weber is a theoretical physicist turned mapping executive turned insurtech founder. After a decade at TomTom and HERE Technologies optimizing routes for time and distance, he asked a different question: why isn't anyone optimizing for risk? RouteRisk.ai is his answer. The company scores every commercial route across sixty-plus variables before dispatch, producing what Weber calls "a FICO score for fleet routes." In this conversation, Josh Hollander and Weber dig into the science behind segment-level route scoring, the insurance market's fourteen-year losing streak on commercial auto, and why giving the technology away for free might be the smartest distribution strategy in fleet insurtech. Guest Bio Goetz Weber holds a PhD in quantum field theory and spent over a decade in the navigation and mapping industry, serving as VP of Innovation at TomTom and previously at HERE Technologies. In those roles, he worked directly with fleet operators, fleet management companies, and logistics platforms. He founded RouteRisk.ai to address a gap he identified firsthand: routing companies optimize for cost, time, and distance, but nobody scores risk. RouteRisk is now Series A funded, integrating with platforms like Samsara, and building its go-to-market for insurance distribution. Key Topics • The missing layer in fleet risk assessment - Historical data looks backward, telematics looks at the present, but nobody scores what's about to happen. RouteRisk fills the forward-looking gap with pre-dispatch route scoring. • Sixty-plus variables in a single route score - Static road geometry, forward weather, traffic predictions, vehicle physics, cargo sensitivity, theft corridors, and incident history, all scored at the segment level and aggregated with interaction effects. • The FICO analogy for fleet routes - A composite risk score that tells dispatchers, fleet operators, and insurers the risk profile of a specific route, at a specific time, for a specific vehicle carrying specific cargo. • Risk appetite as underwriting data - When a fleet operator chooses a route scored at 80 over one scored at 40, that decision is captured. Over time, this builds a behavioral profile of risk appetite that insurers have never had access to. • Free-to-fleet, monetize-through-insurance - RouteRisk gives the scoring tool to fleet operators at no cost (reducing their accidents and insurance leverage) and sells the risk decision data to carriers and reinsurers. • Three paths to insurance market entry - Form a proprietary MGA, partner with existing fleet insurers on incentive-based pricing, or go directly to reinsurers who bear nuclear verdict risk. • Why this isn't the telematics adoption problem - Telematics monitors drivers (creating resistance). RouteRisk scores roads and empowers dispatchers. No cameras, no surveillance, no cost barrier. Notable Quotes "I think of vehicles moving through space as moving through risk fields, dynamic risk fields that come and go, whether it's weather, traffic, road conditions, theft hotspots." "If I show you two routes and one has a risk score of forty and one has a risk score of eighty, and you choose the eighty, I've captured your risk appetite. And that data is gold for an insurer." "If you and I both go to a ski resort, but you do extreme downhill and I do cross-country, technically we should have different insurance programs. Our data reveals which fleet operators are the extreme downhillers and which are the cross-country skiers." "Risk should be visible and manageable before it materializes, not just measured after it has." Resources Guest: • RouteRisk.ai: https://www.routerisk.ai • Goetz Weber on LinkedIn: https://www.linkedin.com/in/goetzweber/ Host: • Joshua R. Hollander on LinkedIn: https://www.linkedin.com/in/joshuarhollander/ • Horton International (USA): https://www.horton-usa.com/ • Insurtech Leadership Podcast (LinkedIn Showcase): https://www.linkedin.com/showcase/insurtech-leadership-show Subscribe & Review If you enjoyed this episode, subscribe on your favorite platform and leave a review. The Insurtech Leadership Podcast is available on YouTube, Apple Podcasts, and Spotify.

    33 min

  6. Apr 30

    From Travelers Executive to AI Startup: What’s Harder, What’s Easier

    Introduction What happens when a decade-long carrier executive decides that the best way to fix insurance operations is to stop advising from the inside and start building from the outside? Vijay Laknidhi spent his career at Travelers and Amtrust, sitting in the rooms where technology decisions stalled, procurement cycles stretched past usefulness, and AI pilots died in committee. Now, as GM of Commercial Insurance at Liberate, a voice AI company built exclusively for P&C, he runs what he calls "a Series A company inside a Series B company," tasked with scaling a P&L dramatically in a single year. In this episode of the Insurtech Leadership Podcast, host Joshua Hollander sits down with Vijay to unpack what it actually looks like to cross from buyer to builder, why commercial insurance is uniquely ripe for AI disruption, and what separates production-grade insurance AI from a compelling demo. Guest Bio Vijay Laknidhi is the General Manager of Commercial Insurance at Liberate, a voice AI company focused exclusively on property and casualty insurance. Before joining Liberate, Vijay spent over a decade in executive roles at Travelers and Amtrust, where he led underwriting, product, and operational functions across commercial lines. His carrier-side experience gives him rare dual fluency: he understands the internal politics, compliance requirements, and procurement friction that slow AI adoption at large insurers, and he now builds the products designed to break through those barriers. At Liberate, he operates with startup autonomy and carrier-grade expectations. Key Topics • The carrier-to-startup leap - Why a successful insurance executive would leave the stability of a Top 10 carrier to join a Series B startup, and what that transition actually demands • Voice AI in P&C operations - How Liberate applies voice AI to claims intake, FNOL, and policy servicing, replacing legacy IVR and manual call center workflows • Why commercial insurance is the AI beachhead - The structural reasons (submission volume, manual underwriting, broker friction) that make commercial lines more amenable to AI than personal lines • The demo-to-production gap - What separates an impressive AI proof-of-concept from a system that handles edge cases, compliance, and carrier-grade uptime in production • Selling to the buyers you used to be - How Vijay's decade on the carrier side shapes his approach to navigating procurement, legal review, and stakeholder alignment at prospect companies • Why every insurance leader must get hands-on with AI - The argument against delegating AI strategy to innovation teams or consultants, and why executives need direct fluency • AI-native architecture vs. legacy tech debt - Why recent startups like Liberate have a structural advantage over incumbents trying to bolt AI onto decades-old policy admin systems Notable Quotes -"I'm running a Series A company inside a Series B company. I own the P&L, I own the roadmap, and I have one year to prove the commercial insurance thesis." -"When you've sat in the buyer's chair for a decade, you know exactly which objections are real and which ones are just procurement theater." -"The gap between an AI demo and a production deployment in insurance is compliance, edge cases, and the willingness to handle the 2% of calls that don't fit a script." -"If you're a carrier executive delegating AI to your innovation team, you've already lost. You need hands-on fluency, not a briefing deck." Resources Guest: • Liberate: https://www.liberatetech.ai/ • Vijay Laknidhi on LinkedIn: https://www.linkedin.com/in/vijaylaknidhi/ Host & Organization: • Joshua R. Hollander on LinkedIn: https://www.linkedin.com/in/joshuarhollander/ • Horton International (USA): https://www.horton-usa.com/ • Insurtech Leadership Podcast (LinkedIn Showcase): https://www.linkedin.com/showcase/insurtech-leadership-show Subscribe & Review If you enjoyed this episode, subscribe on your favorite platform and leave a review. The Insurtech Leadership Podcast is available on YouTube, Apple Podcasts, and Spotify.

    26 min

  7. Apr 17

    Special Virtual Episode: Applied Systems and the Digital Round Trip

    Introduction What happens when the insurance industry's dominant agency management platform decides manual data entry is no longer acceptable? Applied Systems is betting its product roadmap on a three-ring strategy they call the "digital round trip," combining embedded AI, strategic acquisitions, and platform overhauls to eliminate the operational drag that costs agencies thousands of hours per year. This deep dive unpacks the core strategy shifts, the specific technologies driving change, and the leadership decisions behind a platform serving 37,000 agencies and 300,000 users. Key Topics The Digital Round Trip Framework - Applied's three concentric rings: core agency management (Epic), carrier collaboration (Ivans, Cytora), and embedded AI. Each ring represents a strategic investment layer aimed at turning Epic from a system of record into a system of action. Cytora Acquisition and Zero-Training AI - How Cytora's "agentic team" of seven LLMs running at different temperature settings extracts structured data from unstructured inputs (emails, PDFs, voice calls) without pre-labeled training data, cutting submission prep from hours to minutes. Epic AutoFill for Benefits and Commercial Lines - AI-powered extraction that reads SBC documents and complex vehicle schedules in seconds, saving an estimated 30 minutes per plan and 2-3 hours per commercial submission in manual data entry. Epic Max: The Natural Language Copilot - Applied's AI assistant targeting the 2-3 hours per day agency staff spend searching for information. Goal: recapture 12,000 hours (equivalent to 6 FTEs) in its first year through instant natural language queries with auditable source chains. BPO Disruption - Applied's aggressive stance that AI should replace outsourced data entry, directly challenging the business model of agencies spending $500K+ annually on BPO for routine tasks. Agency Valuation and M&A Implications - How AI adoption and system consolidation make agencies more attractive to acquirers. Clean data, lower operating costs, and standardized workflows command premium multiples. Notable Quotes "Their strategy comes from clients saying, we're spending way too much money outsourcing stuff that the software should just do." "The initial fear of AI seems to be turning into FOMO on AI. Because if your competitor is saving 2 hours per person per day, you literally can't afford not to adopt." "An agency that uses this tech to streamline workflows, clean up its data, lower operating costs becomes way more attractive to buyers. It's the after photo." "Automating the simple decisions is becoming table stakes. Using AI to master the triage and routing of the most complex risks to the human brain might be the real competitive advantage in the next decade of insurtech." Resources Applied Systems: Applied Systems: https://www.appliedsystems.com/ AppliedNet Conference: https://www.appliednet.com/ Host & Organization: Joshua R. Hollander on LinkedIn: https://www.linkedin.com/in/joshuarhollander/ Horton International (USA): https://www.horton-usa.com/ Insurtech Leadership Podcast (LinkedIn Showcase): https://www.linkedin.com/showcase/insurtech-leadership-show Subscribe & Review If you enjoyed this episode, subscribe on your favorite platform and leave a review. The Insurtech Leadership Podcast is available on YouTube, Podbean, Apple Podcasts, and Spotify.

    54 min

  8. Apr 11

    Beyond Wildfire: How Jessica Leong and Octagram Analytics Are Rethinking Fire Risk in Insurance

    Introduction In this episode of the Insurtech Leadership Podcast, host Josh Hollander welcomes back Jessica Leong, co-founder of Octagram Analytics, to discuss FireRQ — a non-catastrophe fire risk model delivering actionable risk scores for any U.S. address. While the industry fixates on headline-grabbing catastrophes, Jessica and her team are tackling the everyday fire risk that quietly drives loss ratios, underwriting decisions, and portfolio performance. Guest Bio Jessica Leong is co-founder of Octagram Analytics, an actuarial analytics firm. Before founding Octagram, she served as Head of Data & Analytics at Zurich North America, where she led the team that built all predictive models for pricing and claims. She is also a former President of the Casualty Actuarial Society. Jessica brings over a decade of experience in insurance predictive analytics to the problem of non-catastrophe fire risk. Key Topics Non-cat fire risk: the overlooked loss driver — Fire (excluding wildfire) accounts for 15–30 points of property loss ratio in homeowners and commercial lines, yet most carriers treat it as a solved problem. Jessica explains why it isn't. The dataset advantage: 1.7 million fires — Octagram built FireRQ on the National Fire Incident Reporting System (NFIRS), a publicly available dataset of fires reported by U.S. fire departments. Even Fortune 500 carriers only see ~1% of this data in their own books. Repeat fires and fire clusters — The data reveals that buildings with prior fires are significantly more likely to burn again, and that fires cluster by geography and occupancy type. The Myrtle Beach hotel cluster (10–15 hotel fires per year in a single zip code) is a striking example. Machine learning for fire prediction — FireRQ uses a gradient boosting machine (GBM) that starts with building-level history, then branches outward to area and occupancy-level fire experience. The model captures 80% of fires in the worst 20% of buildings. How underwriters use FireRQ — Carriers apply the score for pricing adjustments, risk selection (declining high-score accounts), and early warning. Octagram offers a free proof of concept using an older model version so clients can validate on their own loss data. Model transparency and explainability — As larger accounts adopt FireRQ, demand for "why" behind scores is growing. Octagram is adding context layers: prior fires at the location, area-level fire frequency, occupancy benchmarks. What's next for Octagram — LiabilityRQ and CrashRQ are in development, extending the same data-driven approach to liability and auto crash risk. Quotes "We can look at 100% of the data where you're staring at 1% of the data." "If we tell you these buildings are the worst 20% buildings in the U.S., we do see they have 80% of the fires." "No one talks about [non-cat fire] anymore, but it's still a very, very real risk." Resources Octagram Analytics website: octogramanalytics.com The Little Book of Fires: Free resource available on the Octagram Analytics website National Fire Incident Reporting System (NFIRS): Publicly available U.S. fire data Subscribe & Review If you enjoyed this episode, subscribe to the Insurtech Leadership Podcast on YouTube, Apple Podcasts, Spotify, or wherever you listen. Leave a review — it helps other insurance and technology professionals find the show.

    28 min
See All (222)

4.4
out of 5
21 Ratings

About

Full-length episodes and replays from The Insurtech Leadership Podcast. New here? Start with the newest episode and work backwards.

Information

You Might Also Like