Disclosure: I run the Live Events Standards Council, which is working on this problem. Sharing because the data gap itself is genuinely interesting and I’d love input from people who work in this space.
Something I haven’t seen discussed anywhere:
The US ticket refund insurance market is $2.01 billion annually. 13.6% CAGR projected through 2035. Every single policy in this market is currently priced as if every venue carries identical risk — because there is literally no venue-level risk data in existence anywhere.
No public chargeback rates by venue. No cancellation frequency by platform. No loss ratio transparency by ticketing provider. The FTC documented a ~10% chargeback rate in high-fraud ticketing contexts versus 0.6-1% e-commerce baseline — but that data isn’t broken down by venue, platform, or event type. Every underwriter is flying completely blind on risk differentiation.
This matters now because the DOJ-Live Nation settlement just opened a newly competitive market with 14,700+ independent venues and 15+ competing ticketing platforms — none of which have any certification, compliance data, or way for insurers to differentiate between them.
Analogous markets that built certification infrastructure — restaurant health grades, IIHS auto safety ratings, LEED building certification — documented 13-55% reductions in adverse events once a public quality signal existed. The mechanism is consistent: visible certification changes consumer selection behavior and gives operators incentive to comply.
We filed a public-interest submission in the Live Nation federal remedies proceeding making the actuarial case for why venue-level certification matters: https://liveeventscouncil.org/LESC-court-filing/
If anyone here works in insurance data, actuarial modeling, or regulatory datasets in adjacent industries — genuinely would love input on methodology for building the first venue-level risk dataset in this market. Open research volunteer role if anyone’s interested.
submitted by /u/Thatgirltorie
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