Zenity for Life Insurance
Your claims and underwriting agents are already making decisions regulators will ask about. Can you show your work?
Zenity gives life insurers the visibility, runtime boundaries, and audit trail the NAIC AI Systems Program requires, without slowing the AI investment already underway.
This is already happening.
Life insurers are moving fast: composite AI platforms combining generative, agentic, and classical AI now run claims triage, underwriting support, and group benefits enrollment in production, at multi-billion-dollar investment scale. At the same time, the regulatory floor is rising: the NAIC Model Bulletin is now active in 25 or more states, and a multistate AI Systems Evaluation Tool pilot is examining insurer AI governance through 2026.
Why this is a different risk.
Model risk management tests the model. It doesn't watch what an agent actually does at runtime: which system it touched, what data it pulled, or whether it stayed inside its authorized scope. Three ways it goes wrong:
External
A claimant or bad actor manipulates a life or disability claims agent into an unauthorized payout.
Insider
An underwriting agent inherits more applicant data access than its task needs.
Autonomous
An agent reasons its way into approving or escalating a claim outside its intended authority.
How Zenity secures it.
Surface
Continuous inventory of every claims, underwriting, and enrollment agent.
Enforce
Deterministic boundaries aligned to underwriting and claims policy logic, evaluated in real time.
Protect
Full decision-chain reconstruction for any challenged claim or underwriting decision.
Built for how life insurers are actually deploying AI.
Composite or enterprise AI platforms
Vendor claims-automation partnerships
Homegrown underwriting and claims models
Compliance mapping.
What the NAIC AI Systems Program asks for, mapped directly to what Zenity already provides.
NAIC AI Systems Program requirement | What Zenity provides |
|---|---|
Written, current inventory of all AI systems in use | Surface: continuous agent discovery and exposure mapping |
Risk controls, testing, vendor oversight | Enforce: runtime boundaries applied consistently, including to vendor-embedded agents |
Documentation an examiner can request | Protect: decision-chain reconstruction |
Gartner "Company to Beat" in AI Agent Governance
Existing GDPR, FDIC, PCI, and SOX compliance language already published on Zenity's Financial Services page, extended to insurance-specific regulation
"With Zenity, we identified and managed risks from a huge attack surface containing over-shared resources that had access to sensitive data, DLP bypass routes, and misconfigured AI Agents."
Risk reduction across the tenant containing 150k+ total resources
Growth in agent, app, and automation volume
"With Zenity, we identified and managed risks from a huge attack surface containing over-shared resources that had access to sensitive data, DLP bypass routes, and misconfigured AI Agents."
Risk reduction across the tenant containing 150k+ total resources
Growth in agent, app, and automation volume
"With Zenity, we identified and managed risks from a huge attack surface containing over-shared resources that had access to sensitive data, DLP bypass routes, and misconfigured AI Agents."
Risk reduction across the tenant containing 150k+ total resources
Growth in agent, app, and automation volume
Resources
See your AI Systems Program readiness before an examiner asks for it.
Visibility, runtime boundaries, and an audit trail, mapped to what the NAIC AI Systems Program asks for.