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Full-length episodes and replays from The Insurtech Leadership Podcast. New here? Start with the newest episode and work backwards.
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4 days ago
4 days ago
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.
Friday Apr 17, 2026
Friday Apr 17, 2026
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.
Saturday Apr 11, 2026
Saturday Apr 11, 2026
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.
Wednesday Apr 01, 2026
Wednesday Apr 01, 2026
Introduction
What happens when a bank finds the right technology but can't touch it for nine months? The procurement bottleneck in regulated financial services isn't just an inconvenience. It's a competitive disadvantage measured in quarters, lost sponsors, and dead deals.
Scott Sambucci, Managing Director of North America and Europe at NayaOne, has spent 25 years selling into and building technology for financial institutions, from CoreLogic to Blend Labs. Now he's leading the US and Canadian expansion of NayaOne's sandbox-as-a-service platform, the same infrastructure the UK's Financial Conduct Authority chose to power its own digital sandbox. In this episode, Scott breaks down why the vendor delivery problem is the real blocker to innovation in insurance and banking, and how air-gapped sandbox environments compress proof-of-concept timelines from months to weeks.
Guest Bio
Scott Sambucci is Managing Director of North America and Europe at NayaOne, where he leads market expansion for the London-based sandbox platform. Before joining NayaOne full-time in January 2024, he spent 25 years in Silicon Valley building and scaling technology companies in financial services, including executive roles at CoreLogic and Blend Labs. Scott is also founder of SalesQualia, a sales coaching firm, and teaches Sales & Marketing at Hult International Business School. A 200-mile ultramarathon finisher, he applies the same relentless-forward-progress mindset to enterprise sales and team building.
Key Topics
- The vendor delivery infrastructure gap — Banks and carriers need 6-12 months of third-party risk management, security, and compliance review before they can even pilot new technology, leaving them perpetually behind nimble competitors.
- How air-gapped sandboxes collapse procurement timelines — NayaOne's off-estate digital sandbox lets institutions run proof of concepts in weeks because the environment is completely separated from production systems, eliminating the need for individual vendor security reviews.
- The "vet once, test many" model — Once a bank approves NayaOne as a vendor, any future technology (from Y Combinator startups to CrowdStrike) can be tested inside the sandbox without repeating the TPRM process.
- Insurance-specific use cases: claims modernization — P&C carriers are using the platform to test AI-driven FNOL triage, claims routing, fraud detection, and payment automation across the full claims lifecycle.
- Multi-LLM side-by-side assessments — Banks are running comparative evaluations of ChatGPT, Gemini, and other LLMs inside the sandbox, the only way regulated institutions can safely touch these systems before committing.
- Integration testing with core systems — The platform replicates Guidewire, Duck Creek, Salesforce, and ServiceNow environments so carriers can validate interoperability before making a purchasing decision.
- Relentless forward progress as a leadership framework — Scott draws a direct line from 200-mile ultramarathons to building a US operation from scratch: plan station to station, leverage the team, and own everything that happens.
Notable Quotes
"What you've built here is a utility that every financial institution is going to need, whether they know it or not right now." — Scott Sambucci, Managing Director, NayaOne
"There's nothing more frustrating than making good progress with your sales demo, having good early conversations, but then being told it's just gonna take nine months for you to fill out all this paperwork." — Scott Sambucci
"By nature, every bank out there is going to be twelve months behind their competitive landscape because those competitors don't have those same guardrails yet." — Scott Sambucci
"No one's coming to help you. No one can pick you up and take you to the finish line. It doesn't matter how good or bad you feel — you just have to keep moving." — Scott Sambucci
Resources
Guest:
- NayaOne: https://nayaone.com/
- Scott Sambucci on LinkedIn: https://www.linkedin.com/in/scottsambucci/
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.
Friday Mar 20, 2026
Friday Mar 20, 2026
How is private equity approaching the insurance technology opportunity differently than traditional venture capital? What happens when risk capital wants to move upstream in the value chain, and AI enables it to actually get there?
Guest
Joe Zuk is an Operating Partner at Altamont Capital Partners, where he leads corporate and business development across a portfolio of insurance and insurance services companies. With 23 years of industry experience, Joe spent 10 years as a reinsurance broker and underwriter, then 8 years with two MGAs building P&C verticals and corporate development functions. At Altamont, he oversees portfolio companies including Accelerant Holdings, Augment Risk, Embark General, Fleming Holdings, Ascendex Underwriters, Kuvare Holdings, and Hadron Holdings.
Key Topics
The Insurance Stack is Compressing - Risk capital (reinsurers, ILS, carriers) is moving upstream toward origination. Traditional 8-layer distribution is collapsing into 3: origination, translation, risk capital. AI is the enabler, but relationships still matter.
AI Solves Operational, Not Structural, Problems - The industry went through shiny object syndrome with AI. Real ROI comes from mundane efficiency: submission triage, claims processing speed, underwriting augmentation from unstructured data. Not flashy, but measurable.
Why PE Beats VC for Insurance - Insurance requires patience, regulatory expertise, and operational discipline. VC timelines are destructive. PE operating partners understand the regulatory cadence and can navigate it competently.
The Founding Team Playbook Has Changed - Today's insurance startups need a CTO or head of data as a founding hire, not just an underwriter and a producer. Talent comes from adjacent industries (fintech, healthtech) not just insurance veterans.
Now Is the Best Time to Build - Technology maturity, available talent, incumbent inefficiency, and collapsed barriers to entry mean founders can build insurtech companies that compete on quality and speed with much larger organizations.
Hiring for Curiosity Over Credentials - Altamont prioritizes intellectual curiosity and adaptability, especially for tech-forward roles. Domain expertise still matters, but learning velocity matters more.
Trust Cannot Be Automated - AI compresses workflows, but it doesn't compress trust. Relationships, sales, and concierge service remain core differentiators in insurance, even as the stack contracts.
Notable Quotes
"AI can compress workflows, but it doesn't compress trust."
"The insurance stack is compressing from eight layers down to three: origination, translation, and risk capital."
"We went through a period of shiny object syndrome with AI. The real ROI is in the mundane operational efficiency."
"I believe there's never been a better time to be an entrepreneur in the insurance market."
Resources
• Altamont Capital Partners: https://altamontcapital.com/
• Joe Zuk: https://joezuk.com/
• Follow Joe: https://www.linkedin.com/in/joezuk/
• Horton International: https://www.horton-usa.com/
Subscribe & Review
Catch every episode of the Insurtech Leadership Podcast wherever you listen. Subscribe and leave a review to stay on top of insurance innovation, PE strategies, and the future of underwriting.
#InsurTech #Insurance #InsuranceInnovation #Leadership #ExecutiveLeadership
Wednesday Mar 18, 2026
Wednesday Mar 18, 2026
Introduction
What happens when carriers can predict where risk exists but have zero control over how that risk changes after the policy is written? Valkyrie Holmes, CEO and Co-Founder of Faura, returns to the Insurtech Leadership Podcast to answer that question with a new playbook: turn policyholders into active risk managers, and retention follows.
In this episode, Holmes unpacks Faura's retention engine for high-risk consumers, the two-page resilience report reshaping how homeowners engage with their own property risk, and why MGAs have become her favorite distribution partners. The conversation covers carrier trust, first-party data strategies, composable platform architecture, and what it takes to lead a scaling insurtech as the youngest person in every room.
Guest Bio
Valkyrie Holmes is the CEO and Co-Founder of Faura, a climate risk intelligence platform that evaluates property survivability across all five NATCAT perils: wildfire, hurricane, hail, flood, and earthquake. Holmes skipped college, interned at NASA and SpaceX, and co-founded Faura in 2023. The company has raised $3.5M in seed funding from Harlem Capital, Building Ventures, MetaProp, and Dorm Room Fund, won the State Farm Pitch Competition at InsureTech Connect, and secured a strategic partnership with Insurity to embed resilience analytics into P&C underwriting workflows.
Key Topics
• The Retention Engine - Faura's new approach to turning policyholders from passive premium-payers into active risk managers through engagement and behavioral data
• Two-Page Resilience Reports - Homeowner-facing reports that prioritize easy action items first, building momentum before introducing harder mitigation steps
• QR Codes and CA Compliance - How carriers use Faura's walkthrough module as a compliance tool for state-mandated wildfire discounts in California
• First-Party Property Data - Filling modifier gaps in carrier datasets by partnering with homeowners for ongoing risk information in exchange for incentives
• MGA Strategy - Why MGAs move faster, require less consensus, and have become Faura's ideal distribution partners over tier-one carriers
• Composable Platform Architecture - Building a system flexible enough to customize endpoints, reports, and fields for any carrier, broker, or distribution partner
• Differentiation in High-Risk Markets - What carriers need beyond price to retain policyholders as competition increases in FL, CA, and emerging catastrophe zones
Notable Quotes
"Historically, many carriers have been very good at predicting where risk exists, but have very little control over how that risk changes after the policy is written."
• Valkyrie Holmes, CEO/Co-Founder, Faura
"If you're re-entering a market or trying to take up market share, what is the reason someone stays with you over switching to another carrier for a fifty-dollar premium reduction next year?"
• Valkyrie Holmes
"Talk to everyone. Talk widely. And then narrow to your mission."
• Valkyrie Holmes
Resources
Guest:
• Faura: https://www.faura.us/
• Valkyrie Holmes on LinkedIn: https://www.linkedin.com/in/valkyrieholmes/
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.
Friday Mar 13, 2026
Friday Mar 13, 2026
Introduction
What if the biggest friction point in insurance isn't underwriting or distribution, but the moment a policyholder actually gets paid? For an industry built on the promise of financial protection, the claims payout process remains stubbornly analog, slow, and vulnerable to fraud.
In this episode of the Insurtech Leadership Podcast, host Joshua Hollander sits down with Andrew Jernigan, Head of Insurance, North America at Pliant, to dissect how card-based payout infrastructure is reshaping claims operations. From single-use virtual cards that eliminate fraud vectors to tokenized wallet payouts that meet policyholders where they already transact, Jernigan makes the case that modernizing the last mile of claims isn't just an ops upgrade, it's a revenue strategy.
Guest Bio
Andrew Jernigan is the Head of Insurance, North America at Pliant, a card-as-a-service platform modernizing claims and benefit payouts for insurers and payers. Prior to Pliant, he was the founder and CEO of Insured Nomads, a company built to serve globally mobile professionals with embedded insurance and financial wellness products. Jernigan brings a rare combination of carrier-side operating experience and fintech product instincts to the claims payout problem.
Key Topics
• Card-Based Claims Payouts - How single-use and virtual cards replace checks and ACH transfers, reducing settlement time from days to seconds
• Fraud Reduction Through Card Infrastructure - Why single-use cards with merchant category restrictions eliminate common payout fraud vectors
• Interchange as a Revenue Lever - The economics of card-based payouts: insurers can generate interchange revenue while reducing operational costs
• Tokenized Wallet Payouts - The near-term future where claims land directly in Apple Pay or Google Wallet, removing the need for physical cards entirely
• Branded Payout Experience - How carrier-branded payment cards turn the claims moment into a customer experience and retention touchpoint
• Implementation Simplicity - Why modern card-as-a-service platforms can integrate in weeks rather than the months-long cycles of legacy payment systems
• Communication as Retention Strategy - The hidden cost of poor claims communication and why payout speed alone doesn't solve the customer experience gap
Notable Quotes
"Use other people's money. That's literally the best advice in payments."
• Andrew Jernigan, Head of Insurance, North America, Pliant
"People are tired of believing that insurance is going to be like pulling teeth. They're waiting for innovation to happen."
• Andrew Jernigan
"It's not just speed. It's control. A single-use card means the money can only go where it's supposed to go."
• Andrew Jernigan
Resources
Guest:
• Pliant: https://www.pliant.io/
• Andrew Jernigan on LinkedIn: https://www.linkedin.com/in/andrewjernigan/
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.
Thursday Mar 12, 2026
Thursday Mar 12, 2026
Introduction
What happens when you stop trying to make claims adjusters faster and instead redesign the entire workflow from first notice of loss? Most insurers are layering AI co-pilots on top of legacy processes, but Ravin AI is arguing for something more disruptive: a fully automated claims pipeline that collects evidence, detects fraud, applies business rules, and routes decisions before a human ever touches the file. In this episode, Eliron Ekstein, Co-Founder and CEO of Ravin AI, breaks down how their Ravin Inspect platform automates up to 80% of auto claims, and why the economics of full automation are fundamentally different from incremental efficiency gains.
Guest Bio
Eliron Ekstein co-founded Ravin AI approximately eight years ago out of Shell Ventures, where he led new business development in Shell's Digital Ventures unit in London. What began as a concept for scanning vehicles at petrol stations has grown into a $35M+ funded insurtech operating across multiple continents. Eliron holds an MBA from London Business School and has spent the past decade digitizing automotive and transportation workflows. Ravin AI now serves insurance carriers, fleets, and remarketing customers globally with its patented DeepDetect technology.
Key Topics
-Full Automation vs. Co-Pilot Augmentation — Why Ravin's "pilot, not co-pilot" approach delivers fundamentally different economics than AI tools that assist adjusters within existing workflows.
-Ravin Inspect: End-to-End Claims Pipeline — How the platform gathers policyholder data, vehicle images, location, speed, and fraud signals upfront to build a complete claim file before human review.
-80% Auto-Adjudication Target — The threshold at which automation rewrites carrier unit economics, from staffing models to cycle times to customer satisfaction scores.
-Purpose-Built AI vs. Generic GenAI — Why domain-specific computer vision and decision logic outperform general-purpose large language models for claims adjudication.
-Integration Without Disruption — Ravin's approach to plugging into existing core systems and claims platforms without requiring carriers to rip and replace.
-International Market Entry — Lessons from expanding an Israeli-founded insurtech into the U.S. and Australian markets, including regulatory and go-to-market differences.
-Fraud Detection as a Byproduct — How automated evidence collection at FNOL creates a stronger fraud signal than retroactive investigation.
Notable Quotes
"Our pilot is not a co-pilot — it will run the claim up until the very last minute where you have to give a final approval."
— Eliron Ekstein, Co-Founder & CEO, Ravin AI
"We can actually gather all the relevant data from you — images, location, speed, fraud detection — and build a complete file that already includes business rules according to which you can settle the claim."
— Eliron Ekstein
"This is more of a radical approach that results in significant benefits, significant speed."
— Eliron Ekstein
Resources
Guest:
Ravin AI: https://www.ravin.ai/
Eliron Ekstein on LinkedIn: https://www.linkedin.com/in/elironekstein/
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.
Thursday Mar 05, 2026
Thursday Mar 05, 2026
Episode Overview
How many insurance organizations have launched an AI pilot, watched it work in the lab, and then watched it quietly disappear in production? Today we're dismantling the myth that AI adoption is a technology problem—and making the case that it's a workflow problem.
Guest
Jake Sloan, VP of Global Insurance at Appian, is an operator first. He has run large-scale insurance operations, owned a $150M P&L, and delivered transformations that only happen when you understand how work actually moves—handoffs, exceptions, controls, and accountability. At Appian, he leads the insurance vertical for a process automation and low-code platform focused on claims, underwriting, and operational process orchestration.
Key Topics
• Pilot Purgatory: Why 90% of AI Projects Stall — Pilots work in controlled environments. Then reality hits: no data pipeline, no workflow integration, no governance, no frontline buy-in. Organizational alignment—not technology—is the breaking point.
• The Orchestration Layer — Appian's core thesis: build an orchestration layer first. It sits between your legacy monolith and the next chapter. Additive, keeps work flowing during transformation, and creates the foundation where AI and automation actually stick.
• Email as Infrastructure — Underwriters spend 40%+ of their day in inboxes. The AI mailbox use case embeds AI into a workflow that extracts data, routes work, makes decisions, and triggers actions. Underwriters gain 2–3 hours a day back.
• Claims Velocity: Days to Hours — One global insurer went from 24–72 hours (FNOL to assignment) to minutes. Digital intake feeds orchestrated workflows. AI triages, categorizes severity, flags fraud risk. The adjuster gets a complete, pre-organized package.
• Alignment = Culture, Not Just Tech — Appian's workshops put business, IT, data, and operations in one room to design the ideal state and work backward. Underwriters don't get replaced—they become superhuman. Admin work gets stripped away.
• The Talent Problem Is a Workflow Problem — Entry-level insurance work is repetitive email categorization. When AI handles the mundane, these jobs become analytical and attractive again. The organizations winning reskill existing teams and position domain expertise as more valuable.
• The 90-Day Deployment Mindset — Pick one workflow. Build the orchestration layer. Plug in AI. Show ROI in 90 days. Then iterate.
Key Quotes
-"When you go to scale it, it's like, well, we don't have the data pipeline. We don't have the workflow. We don't have the governance. We don't have the buy-in from the frontline team. And so it just stalls."
-"It's not about the AI itself. It's about the workflow that the AI sits inside."
-"We're not here to replace underwriters. We're here to make them superhuman."
-"Get started. Don't let perfect be the enemy of good. Start with a use case, build the orchestration layer, plug AI into it, show value in 90 days."
Resources
• Appian: appian.com
• Jake Sloan LinkedIn: https://www.linkedin.com/in/jacobpsloan]
• Joshua R. Hollander, Host: https://www.linkedin.com/in/joshuarhollander/
• Horton International: https://www.horton-usa.com/
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Follow the show on LinkedIn: https://www.linkedin.com/showcase/insurtech-leadership-show
#InsurTech #Insurance #InsuranceInnovation #FutureOfInsurance #ExecutiveLeadership
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#InsurTech #Insurance #InsuranceInnovation #FutureOfInsurance #Leadership #ExecutiveLeadership
Wednesday Mar 04, 2026
Wednesday Mar 04, 2026
Episode Overview
What does it actually take to run a digital insurance operation at the system level—not at the chatbot layer, but at the transaction layer? Joshua R. Hollander speaks with Wayne Slavin, CEO and Co-Founder of Sure, about the infrastructure required to deliver true digital insurance in an AI-agent world. Wayne describes Sure's role as "what Visa and Mastercard were in the early days of credit cards"—building the rails for digital insurance distribution.
Key Topics
1. What "Digital Insurance" Really Means
Digital insurance is not about moving forms online or replacing phone calls with web interfaces. True digital insurance is straight-through processing from quote to policy issuance to payment—mirroring the speed and frictionlessness of e-commerce transactions. Wayne explains: "If that transaction requires some asynchronous process, some process that is interrupted, that we are actually not doing digital insurance." The benchmark: the entire process happens within minutes, not days or weeks.
2. API-First Infrastructure vs. Legacy Core Systems
Sure's platform differs fundamentally from monolithic core policy administration systems (like Guidewire or Duck Creek) because it was built API-first with data normalization at its foundation. Legacy cores encourage over-customization, which locks insurers into inflexible, non-compliant systems. Sure's approach standardizes policy data across product types (homeowners, renters, fine art, landlord), enabling rapid changes and integrations. Unlike legacy systems, Sure doesn't force carriers to choose between their existing tech and innovation—it coexists alongside legacy infrastructure.
3. Model Context Protocol (MCP) and AI Agent Integration
In February 2026, Sure announced the industry's first MCP server integration, enabling Claude AI agents to interact directly with Sure's infrastructure. MCP is a standardized protocol that allows AI agents to connect to business systems without custom integrations for each use case. This means insurers and brands no longer need 6-12 months of engineering to embed insurance; AI agents can quote, bind, manage, and renew policies conversationally.
4. Why Non-Endemic Brands Will Build Insurance
The next major insurance distributors won't be insurance companies. They'll be brands, e-commerce platforms, fintechs, and technology companies with massive customer bases. Wayne's economic thesis: if a brand can convert customers to insurance at 20-30x the typical rate (vs. giving customer data to a third party), the unit economics change entirely. Large brands now have a path to retain customers and data while building insurance revenue.
5. The Transaction Layer as Moat
Insurance isn't like retail or travel—regulatory consequences are real, policy admin systems are complex, and compliance layers must operate end-to-end. Sure's competitive advantage lies in building the foundational transaction layer that carriers either cannot replicate internally or would take years to engineer. This infrastructure layer is what enables AI agents to work reliably within compliance and regulatory constraints.
6. Insurance as an Ecosystem
The future isn't a single insurer offering multiple products—it's an ecosystem where brands, platforms, and technology companies collaborate on insurance delivery. AI agents, powered by Sure's infrastructure, enable this distributed, composable insurance ecosystem.
Key Quotes
-"What digital insurance really means is truly a straight-through process where you're starting to get a quote that quote will be a real quote. It's not an estimate. It will become a real policy. You will pay real money. You will get a real coverage document. And the timing of all of that is pretty close to what you expect from regular old e-commerce."
-"The next big insurance distributors won't be insurance companies. They will be brands. They'll be technology companies. They'll be fintechs. They'll be AI companies. They'll be companies that are currently sitting on large customer bases that don't have insurance products today."
-"Before MCP, if an AI agent wanted to interact with an insurance system, you'd have to build a custom integration for each system, each use case. MCP standardizes that."
Resources
• Sure: https://sure.com
• Wayne Slavin LinkedIn: https://www.linkedin.com/in/wayneslavin
• Horton International: https://www.horton-usa.com/
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