The Reinsurance Podcast

There's a reliable way to spot a boom in insurance: count the conferences. Cyber got its own, then AI, and now MGA events have taken over the calendar. Tom Spier joins Cordy on The Reinsurance Podcast to work out whether the MGA surge is a real shift in how risk reaches capacity, or just a lot of good underwriters building their own wealth instead of somebody else's.

WHAT YOU'LL LEARN:
Why MGA fortunes track the insurance cycle, and where margin hides when it softens
Why underwriting discipline alone won't win capacity in a soft market, and what actually does
How insurers are getting their arms around a third of the book they didn't underwrite, from the Fidelis split to Axis's $10bn delegated authority ambition
What reinsurers should be asking about an MGA's distribution health instead of reading last year's bordereau
Where AI genuinely speeds up MGA quoting, and where it just makes the inbox louder

EPISODE LINKS:
Tom's LinkedIn: https://www.linkedin.com/in/tomspier/
BindSignal: https://bindsignal.com/

CONNECT WITH US:
Say Hello: ⁠producer@thereinsurancepodcast.com⁠
Website: ⁠https://www.supercede.com⁠ 
LinkedIn: https://www.linkedin.com/company/supercedehq 
X: ⁠https://twitter.com/SupercedeHQ⁠ 
YouTube:⁠ ⁠⁠https://www.youtube.com/@SupercedeHQ⁠ 
RSS Feed: ⁠https://anchor.fm/s/7e741c8c/podcast/rss⁠ 

OUTLINE & TIMESTAMPS:
00:00 Intro
01:32 MGAs in a Softening Market
02:43 How the MGA Model Works
03:59 What Makes an MGA Stand Out?
05:14 Growth, Distribution & Underwriting Discipline
07:22 How Insurers Manage MGA Portfolios
09:45 How MGA Business Flows Into Reinsurance
10:58 Data, Bordereaux & Assessing Performance
12:44 Why Distribution Health Matters
14:12 AI, Submission Ingestion & the Human Bottleneck
16:14 Will the MGA Boom Keep Going?

Every reinsurance office has a spreadsheet only one person understands, and this episode is about why that's the industry's biggest quiet risk. Jerad and Ben start by defending spreadsheets properly, Spreadsheet Olympics included, before turning on the very flexibility that makes them dangerous. It's not really about Excel: it's about what happens the day the person who built it doesn't work there anymore.
WHAT YOU'LL LEARN:
Why the industry's "singular greatest key person risk" isn't a person — it's whoever built the spreadsheet they left behind
How a single overwritten cell can undo months of pricing or placement work, and why "version 9 vs version 10" rarely tells you what actually changed
Why massive spreadsheets grind to a halt, and the workaround actuaries already use to keep them alive
What reinsurance can borrow from software engineering's approach to tracking changes, instead of hoping nobody touches the macro
Why most firms are already auditing which processes are one bus ride away from disaster

CONNECT WITH US:
Say Hello: ⁠producer@thereinsurancepodcast.com⁠
Website: ⁠https://www.supercede.com⁠ 
LinkedIn: https://www.linkedin.com/company/supercedehq 
X: ⁠https://twitter.com/SupercedeHQ⁠ 
YouTube:⁠ ⁠⁠https://www.youtube.com/@SupercedeHQ⁠ 
RSS Feed: ⁠https://anchor.fm/s/7e741c8c/podcast/rss⁠

OUTLINE & TIMESTAMPS:
00:00 Intro01:00 Why Reinsurance Loves Spreadsheets02:19 From Spreadsheet Olympics to Spreadsheet Risk05:14 When Spreadsheet Utility Starts to Break Down08:23 Why Replacing Excel Is So Hard11:30 The Problem with “Utopian” Spreadsheets14:06 Key-Person Dependency & the Bus Factor17:12 Keeping Flexibility, Adding Auditability20:04 Rethinking Data Transformation23:19 What Reinsurance Can Learn from GitHub24:57 What Shouldn’t Live in a Spreadsheet28:37 Spreadsheet Dystopia & Outro

Everyone in reinsurance obsesses over the claims side of the balance sheet: what happens when things go wrong. Maurits Van Joolingen, Managing Director of Climate Scenarios & Sustainability at Ortec Finance, spends his time on the assets insurers actually hold, and whether the models pricing that risk are dangerously optimistic.

WHAT YOU'LL LEARN:
Why the industry-standard NGFS climate scenarios might be underestimating the real risk
How nonlinear warming assumptions change the math on portfolio exposure
What a 25%-uninsurable-housing scenario means for insurers' long-term business models
Why divesting from high-emission sectors might be the wrong move for asset owners
How leading insurers are moving from "raising awareness" to actually changing capital allocation

EPISODE LINKS:
Maurits's LinkedIn: https://www.linkedin.com/in/mauritsvanjoolingen/
Ortec Finance: https://www.ortecfinance.com/

CONNECT WITH US:
Say Hello: ⁠producer@thereinsurancepodcast.com⁠
Website: ⁠https://www.supercede.com⁠ 
LinkedIn: https://www.linkedin.com/company/supercedehq 
X: ⁠https://twitter.com/SupercedeHQ⁠ 
YouTube:⁠ ⁠⁠https://www.youtube.com/@SupercedeHQ⁠ 
RSS Feed: ⁠https://anchor.fm/s/7e741c8c/podcast/rss⁠ 

OUTLINE & TIMESTAMPS:00:00 - Intro03:44 - The Two Ways Insurers Model Climate Risk06:10 - Why Ortec Bets on Nonlinear Climate Risk08:00 - From Awareness to Decisions: Where Scenarios Fell Short08:57 - Why 25% of Housing Could Become Uninsurable by 205010:47 - Why You Can't Just Pull Out of a High-Risk Region11:45 - Should Governments Backstop Climate Risk for Insurers?13:15 - What Should Risk Officers Be Doing Right Now?15:37 - Are Clients Waking Up to the NGFS's Blind Spots?16:51 - Regulators, Governance, and the Case for Scenario Planning18:08 - What's Next: Blending Top-Down and Bottom-Up Models20:44 - Closing Thoughts

Better cat modelling isn't just about avoiding bad risk, it's about finding and writing the good risk your competitors are mispricing. James Rendell, CEO of BirdsEyeView, saw that gap and convinced the European Space Agency to back him, and built something that the big vendors hadn't properly tackled. WHAT YOU'LL LEARN:- Why secondary perils like wildfire and severe convective storms are fundamentally harder to model than hurricanes — and how to tackle that properly- How year-old fuel data makes most wildfire models quietly unreliable, and what it means for your next renewal- Why a higher-resolution cat model is a revenue tool, not just a risk-avoidance one — and how soft market conditions make this more urgent- The meaningful difference between physics-based machine learning models and LLMs when you need to explain your risk view to an actuary- How an ESA-backed startup went from contingency market niche to a cat modelling platform used across Lloyd's syndicates, Australian cover holders, US MGAs and beyondTIMESTAMPS:00:00 James Rendell: from broker to insurtech founder01:54 BirdsEyeView and the ESA05:34 The cat modelling landscape07:00 The contingency market gap09:30 Why secondary perils are harder to model12:35 Wildfire, SCS, and building better models14:10 Physics, machine learning, and satellite data16:06 The fuel data problem18:00 AI and the future of cat modelling21:50 Soft market advantage: write more premium

Jerad and Ben skip the small talk and jump straight to 2030, asking the one question worth asking about AI and reinsurance: what actually changes, and what's just getting a shinier coat of paint. They cover cat models, capital allocation, contract structuring, dying market standards, and an industry expense ratio that's somehow gone up instead of down. No guest this week — just two hosts making predictions they might regret.

WHAT YOU'LL LEARN:
Why AI-driven cat modeling might be the one part of reinsurance that actually gets faster and better, not just different
Why the relationship-driven, napkin-deal side of the business probably won't look any different in 2030
Why the market's expense ratio has crept up instead of down despite a decade of technology investment, and what that says about how the industry should be valuing tech spend in the first place
Why rigid market standards and clause libraries might not survive contact with natural language processing
Why nobody's handing a nine-figure placement to an autonomous agent any time soon, and where automation actually helps instead

CONNECT WITH US:
Say Hello: ⁠producer@thereinsurancepodcast.com⁠
Website: ⁠https://www.supercede.com⁠ 
LinkedIn: https://www.linkedin.com/company/supercedehq 
X: ⁠https://twitter.com/SupercedeHQ⁠ 
YouTube:⁠ ⁠⁠https://www.youtube.com/@SupercedeHQ⁠ 
RSS Feed: ⁠https://anchor.fm/s/7e741c8c/podcast/rss⁠ 

OUTLINE & TIMESTAMPS:
00:00 Intro
01:09 Has reinsurance actually changed by 2030
02:11 Cat models get the biggest AI upgrade in the industry
04:44 How AI reshapes reinsurer portfolio and capital strategy
05:46 Why brokers couldn't care less whose paper it is
07:21 Alternative capital's coopetition with reinsurers
08:06 Testing five contract structures before lunch
10:48 The expense ratio problem nobody in reinsurance can explain
12:25 What Silicon Valley's AI spend says about return on investment
14:50 Is AI reinsurance's Concorde, or its Metaverse
18:23 Why natural language could kill reinsurance market standards
21:53 Would you hand a $50m placement to an autonomous agent
25:07 The most impactful reinsurance app was never built for reinsurance
26:53 Monte Carlo, quants, and the last of the 2030 predictions