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

  1. FEB 13

    Live Maps, Smarter Risk: Inside TomTom’s Insurance Playbook

    -Introduction TomTom isn’t just “navigation” anymore. In this episode of the InsurTech Leadership Podcast, Josh Hollander talks with Vinod Poomalai, Head of InsurTech Product Marketing at TomTom, about how insurers are using location, map, and traffic intelligence to improve how they price risk, validate claims, and build telematics programs that actually produce underwriting signal. Guest bio Vinod Pumalai leads go-to-market for TomTom’s insurance and InsurTech vertical. His work focuses on helping carriers, brokers, actuaries, and InsurTech teams integrate TomTom’s location and traffic data into risk models, pricing engines, and telematics workflows—with a practical emphasis on adoption inside real operating environments. Key topics -From static territories to live location intelligence -Why “territory” is a crude proxy—and how mobility patterns add resolution to risk. -Territory risk models powered by traffic + map data -How insurers use location and traffic attributes to refine pricing and portfolio strategy. -Telematics enablement: APIs, SDKs, and flexible integration -What teams actually plug into, and what the implementation path looks like in practice. -Claims validation and fraud detection using mobility history -Using historical mobility/traffic context to validate events faster and reduce leakage. -Where experimentation becomes operational value -The difference between demos and workflows that move loss ratio outcomes. -What the insurance market is missing in location data -Why the market has been underserved—and what that creates as an opportunity. -Talent and leadership required to make it real -Product, data, and insurance domain collaboration: what “good” looks like inside carriers. Quotes -“The insurance market as a whole is very underserved when it comes to location data, traffic data, and so on.” -“At the end of the day, what our clients really care about… is loss ratios.” -“Customers are leveraging our traffic data in validating auto insurance claims.” Resources -Vinod Poomalai: https://www.linkedin.com/in/vinod-kumar-poomalai/ -TomTom Insurtech: https://www.tomtom.com/solutions/insurtech/ -Joshua Hollander: https://www.linkedin.com/in/joshuarhollander/ If you found this useful, subscribe to the InsurTech Leadership Podcast on YouTube and your preferred podcast app. Share the episode with an underwriting, claims, or telematics leader on your team—and leave a review to help more operators find the show.

    29 min

  2. FEB 11

    Beyond Chatbots: How Cara Becomes Your Best CSR

    Introduction “AI in insurance” has become shorthand for chatbots and generic automation. This episode focuses on a more operational question: what would it take for AI to behave like a dependable CSR inside a real agency workflow — completing service work end-to-end, without eroding trust or the customer experience? Guest Bio Nikhil Kansal is the Co‑Founder & CTO of Cara, a domain‑specific AI platform built for insurance to automate servicing and assist with sales. Prior to Cara, Nikhil co‑founded Oyster, a digital brokerage built around customer experience and risk placement. Earlier in his career, he worked as an infrastructure engineer at Stripe, helping operate global payments at high reliability. Key Topics (with context) -Beyond “chatbots” to an AI CSR: Why the bar is task completion, not conversation quality. Delegation + trust: What changes when AI becomes a coworker you can assign work to (and verify). -System-of-record reality: How Cara is designed to sit on top of existing tools instead of forcing a rip-and-replace. -Agency workflow fit: Where service volume lives (certificates, policy changes, routine requests) and what can be automated safely. -Voice + email automation: The operational implications when AI can handle phone calls and inbox-driven work. -Cost control vs service expectations: How leaders reconcile staffing constraints with rising customer expectations. -Guardrails + change management: What “safe automation” looks like in regulated, high-trust environments. Quotes -Nikhil: “It’s a coworker that you can delegate certain tasks to — and you can trust that it gets completed end‑to‑end.” -Nikhil: “Cara is not a replacement for an AMS; it’s more of a coordinator on top of your system of record.” -Nikhil: “Cara can pick up the phone, speak to the customer, and understand what they’re calling about.” Resources Mentioned Nikhil Kansal: https://www.linkedin.com/in/nikansal/ Cara: https://www.getcara.ai/ Joshua Hollander: https://www.linkedin.com/in/joshuarhollander/ If you lead service, ops, or growth at an agency, MGA, carrier, or insurtech: subscribe for operator-level conversations. - Follow/subscribe on YouTube - Subscribe on your podcast platform (Apple Podcasts, Spotify, Podbean, etc.) - Share the episode with the colleague who owns service capacity and staffing plans

    28 min

  3. FEB 6

    Rewriting MedMal with AI: Inside Indigo (with Jared Kaplan)

    Medical malpractice is one of the most established specialty lines—and one of the hardest to modernize. In this episode of the InsurTech Leadership Podcast, Joshua Hollander sits down with Jared Kaplan, Co‑Founder & CEO of Indigo Technologies, to unpack why MedMal is finally ready for a different underwriting and distribution model. Indigo’s bet: you can make MedMal dramatically easier for physicians and brokers without relaxing underwriting discipline—by replacing slow, form-heavy workflows with alternative data, machine learning, and tight operational execution. Guest Bio Jared Kaplan is the Co‑Founder and CEO of Indigo Technologies. Indigo is rethinking medical malpractice insurance with an approach that combines broker-friendly distribution, faster quoting, and underwriting models informed by large-scale claims data and alternative data signals. Key Topics -Why MedMal is “built to resist change”: entrenched processes, long feedback loops, and the real cost of underwriting mistakes. -Underwriting without an application: what replaces the traditional intake and how you maintain discipline. -Alternative data in a high-stakes line: how Indigo uses a broad feature set (beyond prior claims history) to improve risk selection. -Risk segmentation and value creation: lowering premiums for the “overpaid” majority while avoiding the concentrated loss drivers. -The 80/20 claims reality: the small portion of physicians that drives a disproportionate share of MedMal claims. -Brokers as the distribution partner of the future: what modern carriers/MGAs must do to earn broker trust and share. -Operating model over buzzwords: where the real leverage is—quote speed, workflow simplicity, and consistency. Quotes -Jared: “We started with the premise that you don’t need an application.” -Jared: “I would argue Indigo is the baby of both… online distribution… and underwriting using alternative data and machine learning.” -Jared: “There’s no one else there that can figure out the twenty percent of docs that are driving sixty percent of the claims.” Resources Indigo Technologies (company site): https://www.getindigo.com/ Jared Kaplan (LinkedIn): https://www.linkedin.com/in/jared-kaplan-683412/ If you work in specialty insurance, broker distribution, MGAs, or underwriting modernization, this one is a pragmatic look at where AI actually earns its keep. Subscribe for more operator-grade conversations on insurtech, insurance innovation, and leadership—and if you found value here, leave a review to help more executives discover the show.

    30 min

  4. FEB 4

    AI Workflows That Ship - with Vishal Sankhla (OutMarket)

    Introduction Josh Hollander sits down with Vishal Sankhla, Co‑Founder & CEO of OutMarket, to get specific about what “AI in insurance” looks like when it actually changes operations. The focus is commercial insurance workflows—where work still runs through email, PDFs, spreadsheets, and agency management systems—and how to cut cycle time and errors without creating new risk. Guest bio Vishal Sankhla has led product teams at Uber and Meta and previously served as Head of Product at Ethos Life, helping build profitable acquisition channels, the underwriting engine, and the agency partners business. At OutMarket, he’s building an intelligence layer for commercial insurance: agent-assisted workflows that make teams faster and more consistent. Key topics discussed Why AI pilots stall: fragmented data, manual handoffs, and inconsistent processes across the submission-to-bind journey. Data first, workflows second: where insurance data lives, how it breaks, and why workflow redesign is the unlock. Policy intelligence: turning policies into structure so teams can summarize coverage, surface gaps, and improve proposals. Servicing and renewals: reducing back-and-forth, re-keying, and avoidable errors with agent-assisted workflows. Integration reality: fitting into agency management systems and carrier ecosystems instead of trying to replace them. Measuring impact: cycle time, hit rate, and error reduction (not vanity metrics). Trust, privacy, isolation: what it takes to earn permission to touch sensitive client data. Quotes “Because so much of this is happening manually, I think a lot of this data tends to get very, very fragmented.” “we built workflows that now literally allow them to drag and drop, and within a few seconds, they know exactly a quick summary” “We've seen a lot of use cases where people are now winning their businesses because of some AI workflows.” Resources mentioned OutMarket Uber Meta Ethos Life Call to action Subscribe for more operator-grade conversations on insurance and insurtech. On YouTube, drop a comment with the workflow you’d most like to fix—and why it’s stuck today.

    32 min

  5. JAN 30

    Your Core Isn’t Legacy—Your Stack Is

    Most "core modernization" programs fail for one boring reason: fragmentation. Not the tech. The contract sequencing, the handoffs, the Excel that becomes the unofficial system of record-and the silent operational risk that follows. If you're still running underwriting, claims, billing, and reinsurance as separate truths, you're not modernizing. You're just integrating failure modes. Rob Lewis, CEO of INTX Insurance Software, has built and operated carriers and a reinsurer across Africa, Europe, and now the U.S .- and he's watched the same breakdown repeat: end-to-end change gets blocked by sunk contracts, so teams stitch together workarounds and call it progress. His most telling data point: a material share of underwriters still rely on Excel as the "core," even inside serious organizations. Join live if you want to pressure-test your own replacement path-what to replace first, what not to touch, and where "phase it in" quietly guarantees permanent manual work. #InsurTech #InsuranceOperations

    29 min

  6. JAN 30

    Claims Automation’s Dirty Secret: Review Time

    Claims ops keeps buying “automation” that quietly adds work: more review, more disputes, more cycle time. The real villain is verification overhead—when you still have to check everything, “80% automated” is a new cost center disguised as progress. Ralph von Grafenstein, Founder/CEO, DocuSketch, has lived the messy middle of property claims: documentation fights, estimate friction, and payout delays between restorers and carriers. His model is blunt: shrink cycle time by redesigning the workflow and centralizing quality—not by selling buzzwords. Join us if you’re wrestling with vendor ROI, cycle-time targets, or post-cat documentation chaos. #Insurance #Claims

    28 min

  7. JAN 23

    Claims AI Isn’t a Model Problem. It’s a Plumbing Problem.

    Most claims “AI programs” die the same way: you buy models, bolt them onto core, and discover your data can’t support event-driven decisions. The result isn’t bad predictions—it’s diary-driven claims, slow closes, reserve noise, and a false sense of progress. Heather Wilson (CEO) and Mubeen Rabbani (CPO) at Clara Analytics have lived this at scale: thousands of claims triaged daily, with alerts tied to measurable financial lift and operational impact. Their thesis is blunt—AI value is an operating model problem, and the hidden constraint is ingestion, normalization, and mapping across messy, multi-source claims data. Join live if you want to review your current approach: what breaks first, what to measure, and what changes when claims becomes always-on instead of scheduled. #InsurTech #Claims

    30 min
  8. Building the Future of Insurance with AI, Hustle, and Purpose

    JAN 21

    Building the Future of Insurance with AI, Hustle, and Purpose

    Insurance isn’t short on “AI demos.” It’s short on AI that actually survives real workflows—submissions, audits, claims intake, policy comparison, compliance. Aman Gour (CEO, FurtherAI) breaks down what agentic AI actually means in practice, why “accuracy you can trust” is the real moat, and how teams move from one automated workflow to a platform-wide operating layer. What you’ll hear (high-signal takeaways) Agentic AI, defined plainly: a loop where the system executes, checks, and self-corrects until the output is right (not just “extract text from PDFs”). The winning wedge in insurance AI: workflow outcomes and reliability—not model hype. Why “one platform” matters: insurers don’t want 10 tools; they want a workspace that expands from one workflow to many. Where the real leverage is: unstructured intake + decision workflows (submissions, claims/FNOL-adjacent intake, audits, policy comparison). The operator reality: adoption happens when humans stay in control, with review points, auditability, and explainable outputs. The closing theme: speed is useless without intent—“hustle with purpose.” Chapters (timestamps) 00:00 — Intro + Aman’s background 00:36 — What FurtherAI does (where insurance ops actually bleed time) 02:22 — What “agentic AI” means (in the real world) 03:35 — The agentic loop: do → check → correct → final output 09:28 — “Not a ChatGPT alternative” (what a real platform is) 15:18 — What makes teams successful adopting AI in production 28:03 — One-person unicorn vs. small elite teams with leverage 28:56 — Closing: hustle with purpose (Margaret Mead quote) Notable Comments  03:35–04:07 — Agentic loop: execute, reflect, correct until it’s right. 09:28–09:35 — “It’s not just a data extraction platform… It’s not a ChatGPT alternative.” 28:56–29:22 — “Never doubt that a small group… can change the world… Hustle with purpose.” Guest + Company Links FurtherAI: https://www.furtherai.com/ Aman Gour (LinkedIn): https://www.linkedin.com/in/amangour/ About Our Guest Aman Gour, CEO of FurtherAI — a Y Combinator-backed startup bringing automation and AI to the most unglamorous, yet mission-critical parts of insurance. Aman’s a two-time founder, product builder, and storyteller-in-progress — who’s helping rewire how insurers handle submissions, audits, and claims intake. #InsurTech #Insurance #AI #AgenticAI #Underwriting #Claims #WorkflowAutomation

    30 min
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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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