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Reinsurance CAT Modeling AI
CAT model AI update — reinsurer owns reserve miss
—NYDFS AI guidance + Local Law 144 enforcement
Regulatory exposure — commonly overlooked:
Cedents trust model — cannot reproduce AI assumption chain · Local Law 144 requires annual bias audit — Velaru receipts are continuous audit, not annual snapshot.
Ian / Ida lessons
Model miss = solvency event — AI model change control critical.
Munich Re aiSure
Needs behavioral data Velaru asymmetry feed provides
[New York] Financial capital
NYDFS regulates insurers AND banks — same receipt primitive for both books.
[New York] Hiring audit law
NYC AEDT law is template for other cities — receipt architecture scales municipally.
[Text / Chat] Modality hook
Baseline — all frameworks apply to text decisions.
7 mandate layers (live)
Regulatory Clock
Countdown to operative regulatory deadline — NAIC adoption, GSE mandate, EU transposition.
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Domain Classifier
Industry-specific SAFE/CRISIS/VIOLATION with regulatory framework mapping.
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Exhibit / Filing Pack
Regulator-ready external validation — NAIC Exhibit D, Fannie QC, EU FRIA, FDA Part 11.
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Mandate Registry
Enroll deployers/insureds under vertical-specific governance mandate.
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Bind / Action Gate
ALLOW/BLOCK before consequential action — bind policy, sell loan, deactivate worker.
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Compliance Certificate
Deployer-facing downloadable cert — forward to counsel, auditor, regulator.
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Actuarial / Risk Feed
Anonymized asymmetry signals for pricing, reserving, reinsurance correlation.
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