Introduction

What happens to a company that has run two hundred proofs of concept and still cannot point to one that paid for itself? Rafael Broshi says that is roughly where financial services sits after two years of generative AI experimentation, and he does not think the models are the reason.

Broshi has an unusual vantage point on this. He built a brand new insurance product, took it to the admitted market, watched it fail to find buyers, and rebuilt his company around the software his team had written to run it. In this episode he walks host Joshua R. Hollander through why demos survive and production launches do not, what has to be written down before a process can be automated at all, and where an AI agent should never be allowed to improvise.

Guest Bio

Rafael Broshi is co-founder and CEO of Notch, an AI platform for building and deploying agents inside highly regulated industries. He spent nearly ten years in the Israeli military, as did both of his co-founders, and the three of them started Notch about five years ago as something else entirely: a specialty product insuring digital assets including crypto and social media accounts, launched in the admitted market across 47 states with Hartford Steam Boiler. That product did not find a market. The platform the team built to run their own MGA became the company. Notch now deploys agents across customer experience, claims intake, document ingestion, and underwriting workflows for insurers, banks, and asset managers, and is backed by Lightspeed, Jibe Ventures, Munich Re Ventures, and Phoenix.

Key Topics

-Why a new insurance product is the wrong startup bet - Cyber insurance launched in 1997 and took until roughly 2015 to catch on, and no startup survives an eighteen year runway regardless of how much it raises.

-Innovate on distribution, not on the product - Broshi argues that the insurtechs that generated real returns over the past decade changed how insurance was sold rather than inventing new coverage.

-What happens between a working POC and a failed launch - Agents are non-deterministic, so they break as knowledge, guardrails, and process complexity scale, and by the time a project reaches that point its trajectory is easy to change.

-Why he does not believe in forward deployed engineers - He calls the FDE model system integration under a new name, and asks what happens at use case number two hundred inside a five thousand person carrier.

-Why breaking down the process is the part that actually fails - He ties the 75% digital transformation failure rate to the difficulty of mapping a process across departments, and describes AI agents as RPA 7.0 with the same underlying requirement.

-Where agents stay probabilistic and where they must not - Empathy in a first notice of loss conversation cannot be scripted, but the order of the fifteen intake questions cannot be left to a model.

-The subagent architecture behind auditability - Fifteen to twenty subagents run concurrently in a single conversation, each owning one question, so no action happens without a model that can explain it.

-What disqualifies a process entirely - No API access to the data, prediction problems that belong to older machine learning, and any process with no written SOP.

Notable Quotes

"With Gen AI it's extremely easy to show a demo and to show something working in a POC, but when it reaches production, things go south extremely fast."

"Launching a new agent is a business transformation to a specific department. And it's an HR problem as much as it's an IT problem."

"The scars that you now carry on your back, those are your only assets that are worthwhile."

"Everyone says they're doing AI. Don't choose vendors according to presentations. Always do multi-vendor POCs."

Resources

Guest:

Notch: https://www.notch.cx/

Rafael Broshi on LinkedIn: https://www.linkedin.com/in/rafael-broshi-435a77105/

Notch on LinkedIn: https://www.linkedin.com/company/notchapp/

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.

Introduction

What happens to a claims operation when the manipulated photo comes from an ordinary policyholder instead of a fraud ring? Verisk's 2026 fraud study found that 55% of Gen Z consumers and 49% of millennials would make a small rule-bending edit to a claim photo or document, and Aviva stopped £233 million of suspected claims fraud last year with a growing share of it built on AI-generated images and manipulated paperwork.

Jeppe Nørregaard spent seven years building AI systems to detect fake content before deciding the detectors were going to lose. He now runs a company built on the opposite bet, which is that you protect real content instead of chasing fake content. In this episode he walks host Joshua R. Hollander through why detection breaks down under generative AI, what signing content at the point of capture actually asks a carrier to change, and why a flat fraud number next year should worry a claims leader rather than reassure them.

Guest Bio

Jeppe Nørregaard is co-founder of InReality, a Copenhagen company that cryptographically signs photos, video, and documents at the moment they are captured so whoever receives them can prove the content is real and unaltered. He holds a PhD from the Technical University of Denmark, where he worked on AI and misinformation, and his research on how fake news detection degrades over time and under attack is among his most cited work. He did a research stay with an American research group in upstate New York studying AI for misinformation detection, and he sat alongside the researchers building deepfakes while he was building the detectors. InReality works today with news organizations and insurers, and is backed by the Deloitte Innovation Accelerator, the IBC Accelerator, and Antler.

Key Topics

-Why detection loses the arms race - Across seven years of research, Jeppe watched AI strengthen the attacker faster than it strengthened the defender, first with bots and automation and then with deepfakes.

-Flipping the problem - InReality does not evaluate fake content at all. It builds cryptographic guarantees around real content and treats everything outside that pipeline the way the internet already works.

-What a flat fraud number actually means - If detected fraud stops climbing while deepfake use keeps rising, the likelier explanation is that carriers have stopped seeing it rather than that it stopped happening.

-Where signing happens inside a claim - The policyholder photographs the damage through the carrier's own app, and the security sits inside that capture rather than as a review step afterward.

-Cryptography instead of prediction - Detection produces false positives because it is a prediction system. A signature either verifies or it does not, and InReality uses post-quantum signatures.

-Why they refused to build on a blockchain - A blockchain proof cannot be removed, which collides with GDPR's right to be forgotten, so they built an alternative way to produce the same cryptographic proofs.

-What to do with a detection budget already spent - Jeppe separates deepfake detection, which he would stop funding, from the rest of the AI claims stack, which he says carriers should keep investing in.

Notable Quotes

"We don't actually deal with fake content at all in our company. We completely ignore fake content. Instead, we build security guarantees for real content."

"I sat next to the guys who did deepfakes. They tried to deepfake Barack Obama, and I tried to find misinformation. So I knew where this was headed."

"A lot of money has gone into deepfake detection, and fundamentally we believe that it was a mistake, but it's a mistake that everyone made across the planet."

"If we start to see a flattening or a decrease in the amount of fraud that we find, then I would say we have a real problem, because it most likely means that we don't catch it."

Resources

Guest:

InReality: https://inreality.io/

Jeppe Nørregaard on LinkedIn: https://www.linkedin.com/in/jeppe-n%C3%B8rregaard/

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.

Introduction

What does it take to launch an insurance product that did not previously exist, get it live in twelve states in under five months, and run it with a deliberately small team? Vital Coverage Insurance Services did exactly that, and in this episode Josh Hollander brings both sides of the build into the same conversation.

Arvind Kaushal, Co-Founder and CEO of Cogitate, and Justin Krone, COO of Vital Coverage Insurance Services, join Josh for a rare three-way conversation on the show. They cover why Justin left a twenty-year carrier career to run an MGU, why Arvind tells founders to underwrite their technology partner the way they would underwrite a risk, and where each of them draws the line on AI in an underwriting workflow. They do not fully agree on that last one, which is the most useful part of the discussion.

Guests

Arvind Kaushal co-founded Cogitate in 2012 and leads the company as CEO. He came to insurance software from the operator side. Before founding Cogitate he was CFO and CIO at Insurance House, which meant, in his words, that he was signing the checks and responsible for the systems at the same time. The first version of what became the DigitalEdge platform was not a product, it was a fix for his own company's broken workflows. Earlier in his career he spent eight years at Delta Air Lines, including work as an architect on Delta.com, and started out at Wipro in Mumbai.

Justin Krone spent twenty years at CNA Insurance, the last ten running small business and small commercial strategy, before becoming COO of Vital Coverage Insurance Services. Vital is a lean, single-product MGU selling a first-of-its-kind business continuity coverage for small medical practices, protecting physician, dental, and veterinary offices against the loss of a key practitioner. The program launched across twelve states in under five months and is now live in seventeen.

Key Topics

-Underwrite your partner. Arvind's rule for choosing a technology vendor is to run the same diligence on the partner that you would run on a risk, because every provider in the market will tell you they can do everything.

-Principles over capabilities. Justin has seen most of the policy administration platforms on the market, and argues the deciding factor was not the feature comparison but whether the two organizations approached problems the same way.

-The lean MGU thesis. Vital was designed so that a tenfold jump in quote volume would not require materially more staff, and that constraint shaped the underwriting model as much as the technology stack.

-AI as a guardrail rather than an autopilot. Arvind's position is that AI should surface the risk a human misses under volume pressure and flag what falls outside appetite, while the decision stays with the underwriter.

-The case for keeping AI out of underwriting. Justin built a deliberately tight, binary risk-selection model and uses AI heavily across marketing, research, and operations while leaving underwriting alone for now.

-Why the culture change is harder than the tooling. Cogitate began its AI-first push three years ago and stumbled early, and Arvind argues the models were never the difficult part.

-Waiting for regulation to catch up. Both guests work through the NAIC AI model bulletin and what compliance looks like in practice when the carrier remains responsible for what a vendor's AI does.

Notable Quotes

"I don't think of AI in underwriting as an autopilot. I think of it as a guardrail."

"It's not about the tools or LLM models. It's actually about the mindset. The tools are the easy part. Shifting how people think is the hard part. And everyone underestimates it."

"It's not that they have the best capabilities out there. It's that our principles aligned."

"Ideas are easy and execution is hard. And the one thing that I think AI might be kind of changing is that second piece."

Resources

Guests:

Cogitate: https://cogitate.com/

Arvind Kaushal on LinkedIn: https://www.linkedin.com/in/arvind-kaushal-cogitate-digital-insurance/

Vital Coverage Insurance Services: https://myvitalcoverage.com/

Justin Krone on LinkedIn: https://www.linkedin.com/in/justin-krone-78b96563/

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.

Introduction

What would it take for businesses to treat flood the way they treat fire? At a flood-exposed site, flooding is now twice as likely as fire, and 99% of those businesses have a fire plan. Only 8% have a flood action plan, down from 30% a year ago.

In this episode, Joshua Hollander talks with Jonathan Jackson, CEO of Previsico, about why preparedness collapsed while adoption of early warning systems rose from 35% to 49%, and what the insurance industry could do about it, because it has closed a gap like this before. Listeners will leave with a working picture of how property-level flood forecasting gets built, bought, and priced into insurance programs, and what a founder-led CEO succession actually takes.

Guest Bio

Jonathan Jackson is the CEO of Previsico, the flood forecasting company he spun out of Loughborough University in January 2019 while serving as the university's entrepreneur in residence. Previsico predicts surface water flooding at individual property level up to 48 hours ahead, generates a new forecast every hour, and is live with Zurich, Liberty, Generali, Marsh, and around 200 corporates. Previsico is Jackson's fourth start-up, after ventures in telecoms, agriculture (Farming Online, the UK's longest-running B2B internet business), and CPG digital promotions. He hands the CEO role to Mark Trumper at the end of October and will stay on through the transition.

Key Topics

-Why flood plans collapsed from 30% to 8% - A broader survey base pulled in mid-sized firms with thinner risk management, and warning users discovered their generic emergency response plans don't actually cover flood.

-The smoke detector playbook - US insurers drove fire alarm adoption from 25% to over 70% in about six years through premium incentives, and Jackson argues flood needs the same treatment now that US direct flood losses run five times fire.

-What 48 hours of warning buys - Balfour Beatty went from a multimillion dollar loss on a rail bridge project to zero loss on the next flood, with a 36-hour first warning, staged action plans, and a sensor-triggered evacuation.

-How insurers package prevention - Zurich Municipal embeds Previsico warnings in its premium at no added cost, while Liberty issues risk management bursaries (underwriting credits in US terms) to nudge exposed clients toward prevention.

-Why surface water is the hardest flood to forecast - Every storm floods differently depending on track and intensity, which is why a live hydrodynamic model, rather than a static flood map, is required.

-Cracking the US market - Under 5% of US properties carry flood insurance, carriers have limited appetite, and brokers and captives carry more of the load, so Previsico entered customer-led, with proof points at the Port Authority of New York and New Jersey, the MTA, and Governors Island.

-A three-year CEO succession - The handover stretched from a board conversation through a three-investor fundraise and a long search before Mark Trumper's arrival this October.

Notable Quotes

"Flood is five times bigger now than fire in terms of direct loss in the US. From an insurance point of view, it's the new fire."

"They went from a multimillion dollar loss to a zero loss and were able to resume work the next day."

"The original reason for us going into the US is because the customers wanted us over there, particularly the insurers."

"It doesn't work like that in my life, it seems, because we then decided that actually we needed to go and do a fundraise."

Resources

Guest:

Previsico: https://previsico.com/

Jonathan Jackson on LinkedIn: https://www.linkedin.com/in/jonathan-jackson-a393102/

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.

Introduction

Most carriers have stopped arguing about whether the model is accurate. So why does an MIT study keep finding that roughly 95% of AI pilots show no return on what was spent on them?

Dr. Gleb Tsipursky spent fifteen years as a behavioral scientist in academia before moving into consulting, and his answer is that the failure is emotional rather than technical. He names three emotions that block adoption inside insurance organizations: fear of losing the job, threat to professional identity, and shame about being seen using the tools. The third is the one Josh pushed back on, twice, and Gleb did not give ground.

The episode is a companion to the July conversation with Stan Smith at Gradient AI, who argued that an accurate model gets ignored when an underwriter cannot follow its reasoning. Gleb takes it one layer down. Even when the reasoning is legible, the underwriter, the adjuster, and the auditor may still decline to use it, and the fix belongs to executives and middle managers rather than the data science team.

Guest Bio

Dr. Gleb Tsipursky is the CEO of Disaster Avoidance Experts, a Columbus, Ohio consultancy advising leadership teams on AI adoption and decision making. He holds a PhD from UNC-Chapel Hill, spent seven years as a professor at Ohio State studying behavioral economics and cognitive bias, and has consulted for Fortune 500 companies including Aflac, Wells Fargo, Honda, and Xerox. The New York Times called him the "Office Whisperer." His eighth book, "The Psychology of AI Adoption at Work: From Resistance to Results," comes out from Georgetown University Press in September 2026 with a foreword by Nick Bloom of Stanford, and draws on more than a hundred consulting projects and fifty executive interviews. He recently ran a leadership workshop for Citizens Property Insurance in Florida.

Key Topics

-The three emotions - Fear of job loss, threat to professional identity, and shame about being seen using AI. None of the three are addressed by a standard technology rollout.

-Training your own replacement - Employees resist because they believe adoption speeds their own obsolescence, a fear he ties to displacement among junior staff and recent graduates.

-The shame problem - People use AI privately and will not tell colleagues, which preserves individual gains and destroys the team handoffs insurance workflows depend on. Josh pushed back on this twice.

-AI alarmists and pragmatic resistors - Two of the eight psychographic profiles in his book, each needing a different fix from a different level of the organization.

-The skill of the future is editing - Professional pride has to move from drafting the claims letter to evaluating what the tool drafted, which is also what regulators require.

-Why license-plus-training fails - Buying seats and running online education worked for previous technology and does nothing for the emotional blockers under AI.

-Middle managers become supervisors of supervisors - Employees become managers of agents, middle managers manage those supervisors, and leadership is left doing strategy.

-Start in claims - Of every department he has worked with, claims gets a short-term return fastest, beginning with an initial coverage read an adjuster then decides on.

Notable Quotes

"It doesn't matter how accurate the model is, if the underwriter doesn't want to use it. And if the claims adjuster doesn't want to use it and if the auditor doesn't want to use it."

"The biggest resistance to change is not the hassle. The biggest resistance to change is the emotions."

"People are very reluctant to use AI because they feel that they are training their own replacement."

"The skill of the future is not the initial generation. It's the editing and evaluating of that product."

Resources

Guest:

Disaster Avoidance Experts: https://disasteravoidanceexperts.com/

"The Psychology of AI Adoption at Work": https://press.georgetown.edu/Book/The-Psychology-of-AI-Adoption-at-Work

Dr. Gleb Tsipursky on LinkedIn: https://www.linkedin.com/in/dr-gleb-tsipursky/

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.

Introduction

Most carriers have stopped asking whether AI works. So why does so little of it ever leave the pilot?

Kurt Diederich has spent 25 years building the core policy, billing, and claims systems that property and casualty insurers run on. Two years ago he looked at AI and, in his words, thought it was a pile of trash. He kept retrying it every six months anyway, and the thing that flipped him was a bread recipe. He asked a model to cut it in half, it correctly turned tablespoons into one and a half teaspoons, and he went in with both feet.

That arc is the episode. Kurt walks through the adoption curve he sees in most organizations, from skepticism, to being wowed, to badly overestimating what the technology can do, and then the hard landing into execution where the roadblocks show up. His argument is that the software was never the constraint. The constraint is whether a company will restructure how it works, put the right people in front of the change, and actually measure what it gets.

Guest Bio

Kurt Diederich is the Chief Executive Officer and co-founder of Finys, a Troy, Michigan software company whose Suite covers policy administration, billing, claims, portals, and business intelligence for P&C carriers, mutuals, and state FAIR Plans. He started writing assembly-language games as a teenager on TRS-80s and Apple IIs, worked his way through college as a consultant, and has been an entrepreneur ever since. He spent the 1990s building custom claims and policy systems for carriers, then founded Finys in 2001 and went all in on insurance, building the platform on Microsoft .NET. Finys marked its 25th anniversary in 2026 and employs roughly 175 people.

Key Topics

-The four-stage adoption curve - Skepticism, then being wowed, then overestimating what AI can do, then the drop into execution where the real roadblocks appear.

-30% versus three to five times - Let people work the way they always have and you get a modest lift. Restructure the work into small pods and the number changes completely.

-The SDLC becomes the AI PLC - Kurt argues the software development lifecycle is turning into a product lifecycle, where the idea of developers sitting down to write code starts to go away.

-The 40-point measurement gap - Studies found developers predicting a 20% productivity gain while actually running a 20% deficit, and most organizations never measure at all.

-Champions rather than training - Training wears off because people default back to old habits. Kurt uses people who have already done it to coach teams through real work, repeatedly.

-Why carriers have it harder - Governance and regulatory exposure slow carrier adoption compared with a software company, and improper usage draws regulators.

-Spending AI dollars badly - Everyone reaches for the frontier model. Kurt watches an internal credits leaderboard, argues most problems are solved by cheaper models, and says AI should be used to build deterministic solutions rather than being run over and over.

Notable Quotes

"Developers were predicting they're getting a 20% productivity lift with AI when in reality they were at a 20% productivity deficit. So you've got a 40% gap between reality and perceived value."

"If you allow the developers to just work as they've always worked, what we find is you get maybe a 30% productivity lift. By restructuring the way you work, you see these huge productivity lifts."

"I don't think the typical worker is going to have that aha moment where they realize what they've been doing for the last ten, fifteen, or twenty years is wrong. They've been successful at it."

"The AI industry has kind of done themselves some harm by saying you're not going to need all the people to do the work anymore."

Resources

Guest:

Finys: https://finys.com/

Finys on LinkedIn: https://www.linkedin.com/company/finys/

Kurt Diederich on LinkedIn: https://www.linkedin.com/in/kurt-diederich/

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.

Introduction

How much of your agency's new business comes from a source you don't control? Jake Cash spent five and a half years inside GEICO's national agency marketing operation, managing more than $500 million in ad spend, and watched the fastest-growing agencies ride a single channel up and then back down. On this episode of the Insurtech Leadership Podcast, he and host Joshua R. Hollander get into what it takes for a P&C agency to own its growth engine instead of renting it, and why the answer usually starts with the book of business the agency already has.

Guest Bio

Jake Cash is the Founder and CEO of Senryx Group, a Carmel, Indiana firm that builds marketing systems P&C agencies own and run themselves. At GEICO he led agency marketing strategy for more than 300 agencies nationwide, managed over $500 million in ad spend, and negotiated partnerships with Meta, Google, and NBA and MLB teams. He left that Fortune 500 seat (the same day his wife returned from maternity leave and his daughter started daycare) to build Senryx around a diagnostic-first model with no retainer lock-in: assess and plan, build the systems, then train the agency's own team to run them. His goal for most clients is self-sufficiency within six to twelve months.

Key Topics

-The five buckets of dependence - Carrier, channel, tactic, people, and vendor dependency, and how Senryx diagnoses which ones are capping an agency's growth.

-The 50% red flag - Why more than half of new business coming from one source is a vulnerability, and the first question every owner should be able to answer.

-From 100 to 800 policies a month - The 18-month rebuild of a Texas personal lines agency, and the channel mix (Google ads, Meta ads, cross-sell email, organic social) behind it.

-The book you already have - Retention runs seven to nine times cheaper than acquisition, and cross-sell revenue is already sitting in the existing client base.

-Owning your data - Lead vendors sell the same lead to five or ten agencies and share nothing, while owned ad accounts and email put the numbers in the agency's hands.

-AI: admin speed over content volume - Where AI actually helps an agency today, why unedited AI content fails, and Senryx's early tests running ads inside ChatGPT.

-Hiring for growth mindset - What roughly 30 hires in 10 years taught Jake, and why owners have to stop wearing every hat around the $1M revenue mark.

Notable Quotes

"If you don't know where you're getting new business from, then you're just flying blind."

"A lot of times there's kind of a secret pile of cash that's already sitting in your book of business."

"You're just getting the average of the internet as the reply."

"If we get to a point where they don't need us anymore, then we've done our job."

Resources

Guest:

Senryx Group: https://www.senryx.com/

Free two-minute Marketing Independence assessment: https://www.senryx.com/podcast

Jake Cash on LinkedIn: https://www.linkedin.com/in/jakecash/

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.

Introduction

What happens when the personal lines book that carried an agency for years stops feeling safe? Rising home and auto rates, constant remarketing, and carriers pulling back have pushed a lot of independent agencies to look at commercial lines as the way to build a more resilient book. The appetite for the business has always been there. The submission process is what gets in the way.

On this episode of the Insurtech Leadership Podcast, host Joshua Hollander sits down with Michael Rabinowitz, who leads commercial lines product for EZLynx at Applied Systems. Rabinowitz started on the agency side when commercial rating meant loading a floppy disk of carrier rates every month, and he has spent nearly three decades trying to make the work simpler.

They get specific about why commercial has stayed hard, what changes when real-time carrier quoting moves inside the submission, and where AI actually helps an agent who is new to commercial.

Guest Bio

Michael Rabinowitz leads product management for the commercial lines business at EZLynx, part of Applied Systems, the largest provider of cloud software for insurance agencies in North America. His career in insurance spans nearly 30 years. He started on the agency side handling commercial submissions, then moved to the technology side around 2000 to work on some of the industry's early multi-carrier commercial rating. At EZLynx, he led the rearchitecture behind Instant Commercial Quoting, which brings real-time carrier rates into the EZLynx submission workflow. His focus has stayed consistent across all of it: build the tools he would have used as an agent, and make commercial simple enough that more agencies take it on.

Key Topics

-The resilient book - Why the personal lines hard market, with higher rates and heavier remarketing, is pushing agencies to diversify into commercial to stabilize the business.

-The four-times problem - How one small commercial submission can mean entering the same data into three or four carrier portals, often eating the entire commission on the account.

-Commercial by accommodation - Almost every personal lines agency already writes a few commercial policies for long-time customers, which makes commercial an extension of existing relationships rather than a cold start.

-Real-time appetite - Why carrier appetite now shifts day to day, and how live rating inside the submission changes which carriers get seen first.

-AI as an accelerant - How AI helps with class-code and NAICS lookups and catches misclassification, like the ice cream shop that is really a manufacturer, so newer commercial agents build confidence.

-Get out of the way - Rabinowitz's product philosophy that technology should cut context switching and re-keying, not add one more interface to learn.

-Carriers and friction - Why carriers that make real-time connectivity easy will earn the first look, and the ones that do not may get left off the submission.

Notable Quotes

"For me to be doing my job correctly required me to enter in the data four times. That is a tremendous amount of time wasted for maybe a two thousand dollar premium. I've probably eaten up my commission, if not more, just on that activity alone."

"I can't afford to have technology get in my way. Technology either helps me be more productive, or it causes me to lose opportunities."

"They're not an ice cream store, they're actually an ice cream manufacturer. If you misclassify a business and bind the policy and there's a claim, that's a headache down the road waiting to happen."

"If they have to go to five markets and only three are on real-time rating, they may go to those three first. As a carrier, you might get left off of a submission."

Resources

Guest:

EZLynx: https://www.ezlynx.com/

Applied Systems: https://www.appliedsystems.com/

Michael Rabinowitz on LinkedIn: https://www.linkedin.com/in/michael-rabinowitz-32998138/

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.

Introduction

Why does an industry that talks about digital transformation still pay so many claims by paper check? The answer is not stubbornness; it is complexity, and it is worth billions. Josh Hollander sits down with Kevin Ostrander, Chief Revenue Officer at One Inc, to unpack what it actually takes to move carriers off checks, why multi-party claims payouts are the hard part nobody solved first, and what happens when enough carriers and payees are connected that the network, not the processing, is what carriers are buying.

Guest Bio

Kevin Ostrander is Chief Revenue Officer at One Inc, the insurance-specific payments network processing over $245 billion in annual payment volume for more than 300 carriers. He has spent nearly sixteen years selling enterprise technology into insurance, including six years at Thunderhead before its acquisition by Accel-KKR, and he joined One Inc ten years ago when the company had single-digit customers. He owns everything from new business acquisition through customer success.

Key Topics

-Why checks persist - More than half of claims payouts go to third-party vendors, lienholders, and mortgagees, and fifty states each add their own compliance rules, so single-party digital solutions never covered enough of the workflow.

-The malleable ROI case - Checks cost $6 to $25 each fully loaded, digital claim payouts land in minutes instead of days, and the same platform argument works whether the carrier's priority that year is cost, retention, or customer experience.

-Adjuster adoption decides outcomes - If issuing a digital payment adds manual steps, adjusters revert to checks, so One Inc pairs its technology with change management, FAQs, and training on the carrier side.

-One platform for pay-in and pay-out - Over 40% of One Inc's carriers now run both PremiumPay and ClaimsPay, giving policyholders one wallet across premium payments, refunds, and claims.

-The network is the moat - One Inc's escrow network covers 80%+ of escrowed homeowner premium and connects it to 300+ carriers, moving premium 11 to 12 days faster than the 12-to-15-day lockbox process.

-Disciplined expansion - Life insurance (AAA Life, Transamerica) and Canada (with Guidewire, which holds 80%+ of Canadian claims administration) came only after the P&C base was solid.

-Career advice from a first-time CRO - Kevin's path from single-digit customers to 300+ came down to experience you cannot skip, mentors, and recognizing product-market fit when you have it.

Notable Quotes

"Fifty plus percent of the payouts in the insurance industry actually go out to third-party participating vendors."

"The cost of a check fully loaded, including service, print, mail, et cetera, is anywhere from six dollars to twenty-five dollars a check."

"We're actually increasing the speed of premiums by sometimes eleven to twelve days."

"The one thing you can't skip in your career is experience. And you've got to find mentors that will help you through that process."

Resources

Guest:

One Inc: https://www.oneinc.com/

Kevin Ostrander on LinkedIn: https://www.linkedin.com/in/kevin-ostrander-6894ba2/

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

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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.

Introduction

Building the model is no longer the hard part of insurance AI. The hard part now is getting underwriters and carriers to actually adopt it. Josh Hollander sits down with Roger Ferrandis, Head of Partnerships at Sixfold, whose AI now runs inside carriers like Zurich, Guardian, and Skyward Specialty, to talk about how trust actually gets built: proof-of-concept by proof-of-concept, underwriter by underwriter, and market by market through partners who already have the relationships.

Guest Bio

Roger Ferrandis is Head of Partnerships at Sixfold, the AI underwriting platform. Originally from Spain, he spent seven years in the UK, where he co-founded WeAnalyze, an underwriting data startup he helped grow to 25 employees, $3 million raised, and clients on three continents before it pivoted to banking. He chose insurance over banking, moved to New York, and now runs Sixfold's global partner strategy across systems integrators, reinsurers, data providers, and cloud marketplaces.

Key Topics

-Adoption is the product problem now - Leadership teams know they need AI, hand it to someone to evaluate, and that person's reference point is ChatGPT making mistakes, so skepticism is the default starting position.

-How trust gets built in a POC - Sixfold runs known submissions through its AI, compares decisions with the underwriters, feeds their reasoning back into the model, and iterates until 90-95% of outcomes match, which is when confidence flips.

-Amplify, not replace - Sixfold is not chasing full automation; the goal is an underwriter handling four submissions in the time one used to take, with clients choosing their own comfort level on straight-through processing.

-The ROI stack - Clients measure 50% time saved per submission, quote-to-bind up 15%, and gross written premium per underwriter up 30%.

-Partnerships as market entry - Munich Re's Realytix platform, Microsoft's Azure marketplace, Adnovum in Switzerland, and Sollers Consulting in Poland each open doors that direct sales cannot, especially across Europe's twenty-plus selling cultures.

-Build versus buy, honestly argued - Sixfold's model has trained on nothing but underwriting for three years, and Roger's warning to carriers building in-house is that the technology shifts faster than an internal build can keep up with.

-Involve the underwriters - His advice to carrier leadership: do not delegate AI evaluation and hope for the best, because if underwriters do not buy in, nothing happens.

Notable Quotes

"We can sell to C-levels. But if underwriters are not happy with our solution, nothing's going to happen."

"With that iteration, we get to a point where at least ninety or ninety-five percent of the outcomes of the brain are the same outcomes the underwriter will have. When they see that level of accuracy, that's when we gain their confidence."

"If an underwriter used to deal with one submission every hour, we want them to be able to deal with four."

"By the time you build something yourself, the whole technology has changed so much that you need to rebuild it."

Resources

Guest:

Sixfold: https://www.sixfold.ai/

Roger Ferrandis on LinkedIn: https://www.linkedin.com/in/rogerferrandis/

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.