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#3510NAMIC's Insurance Uncovered59.0 / 100Get badge
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GeneralNEW this period

NAMIC's Insurance Uncovered

Hosted by NAMIC

NAMIC's new podcast, Insurance Uncovered, will cover various topics that affect the property/casualty insurance industry. This podcast will also feature an interview segment called "Unscripted" that will include interviews with inside industry experts and staff on a variety of topics.

196 episodes · publishes fortnightly · latest 2026-06-19 · ~23 min/episode

Rank

#3510

Substance

59.0

/ 100

Breakdown

Scored 2026-07
Updated monthly

General rank

#178 of 267

Across the index

#3510 of 6183

Substance

Top 57%

outscores 43% of the index

Why it scores where it does

NAMIC's Insurance Uncovered ranks #3510 on The B2B Podcast Index with a substance score of 59.0 out of 100, scored across 1 recent episode. It scores highest on specificity & evidence and guest caliber. The episode earns credit for naming specific bills (AB 2930, Senate Bill 2, Texas RAIGA, HB 710), states, regulatory documents (NY Circular Letter 7, NAIC Model Bulletin), named individuals (Senator Maroney, Bower Khan, Rachel Drade Rice from Next Insurance), and a concrete milestone (21 state departments adopting the NAIC bulletin); it loses points for zero quantitative data or metrics on actual AI impact.

The five-dimension breakdown

Averaged across 1 recently scored episode, with cited evidence.

Insight Density

12.0 / 20

The episode provides a moderately useful regulatory overview structured around a three-era framework, with some substantive detail on specific regulatory actions. However, the content is largely descriptive policy tracking with limited novel analytical claims; the most interesting material (five misconceptions about AI and insurance pricing) is only teased as a forthcoming white paper rather than explored here.

“I like to think of that advancement as having three distinct eras that have tended to coincide with advancement in technology generally”

“these bills prohibit any resulting algorithmic discrimination, which to generalize is often defined very similarly to disparate impact”

Originality

10.0 / 20

The three-era framework is a modest organizational device but not a genuinely fresh take; the core argument that bias/disparate impact standards conflict with risk-based pricing is a standard industry position. The episode is primarily a regulatory update rather than a source of counterintuitive or first-principles thinking.

“AI as a technology and as a concept has been around since the 1950s, but generative AI was a turning point in both advancement and availability”

“it kind of makes me long for an old fashioned credit scoring debate, um, that we used to have 20 years ago”

Guest Caliber

13.0 / 20

Lindsay Clarkowski Stefani is a credentialed attorney and VP of AI/Data Science at a major industry trade association with genuine policy expertise, giving the episode more depth than a thought-leader guest; however, she is an advocacy professional, not an operator who has actually built or deployed AI systems in insurance at scale.

“NAMIC has actually hired a, uh, vice president of Artificial Intelligence and Data Science and Cyber in the form of Lindsay Clarkowski. Lindsay is an attorney”

“Our AI Working group is, um, a working group that I lead here at namec. And it is comprised of many, many, many of our members who generously devote their time once a month with me”

Specificity & Evidence

15.0 / 20

The episode earns credit for naming specific bills (AB 2930, Senate Bill 2, Texas RAIGA, HB 710), states, regulatory documents (NY Circular Letter 7, NAIC Model Bulletin), named individuals (Senator Maroney, Bower Khan, Rachel Drade Rice from Next Insurance), and a concrete milestone (21 state departments adopting the NAIC bulletin); it loses points for zero quantitative data or metrics on actual AI impact.

“in 2024, we saw 21 state insurance departments adopt the NAIC Model Bulletin on the use of AI and insurance”

“treasury issued a request for information on UM risks and opportunities of AI in services”

Conversational Craft

9.0 / 20

The host functions almost entirely as a prompter, offering no pushback, no probing follow-ups, and no challenge to any of Lindsay's framing; the conversation is a politely structured presentation with soft affirmations rather than a genuine interview with productive tension.

“Yeah, not much really, but a little bit”

“Yeah, no doubt. And that raises all sorts of challenges for us as an industry”

Standout episodes

  • Revisiting Early Misconceptions About Artificial Intelligence

    2026-06-19

    59

Rank over time

First period on the Index - history builds from here.

Episodes

1 scored on substance · 60 tracked in total.

  • Revisiting Early Misconceptions About Artificial Intelligence

    2026-06-19 · 23 min

    59 / 100

Frequently asked

What is NAMIC's Insurance Uncovered's substance score?
NAMIC's Insurance Uncovered scores 59.0 out of 100 for substance and ranks #3510 on The B2B Podcast Index. That puts it ahead of 43% of the B2B podcasts we rank and #178 of 267 in General. The score reflects insight density, originality, guest caliber, specificity and conversational craft across recent episodes - not downloads.
Is NAMIC's Insurance Uncovered worth listening to?
NAMIC's Insurance Uncovered is ranked on The B2B Podcast Index with a substance score of 59.0/100. See the five-dimension breakdown above to judge whether it fits what you're after.
Who hosts NAMIC's Insurance Uncovered?
NAMIC's Insurance Uncovered is hosted by NAMIC.
How often does NAMIC's Insurance Uncovered publish?
NAMIC's Insurance Uncovered publishes fortnightly, has 196 episodes, released its most recent episode on 2026-06-19.
Which NAMIC's Insurance Uncovered episode should I start with?
Our highest-scoring recent episode is "Revisiting Early Misconceptions About Artificial Intelligence" (59/100) - a good place to start.

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Guests who've appeared

Lindsey Clarkowski Stefani

Topics this show covers

The themes that come up most across this show's episodes.

ChatGPTgenerative AIRisk-based pricingDisparate impactAlgorithmic biasBig dataHigh-risk AI legislationNAIC AI Model BulletinProxy discriminationColorado high-risk AI law

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