New York's Department of Financial Services expects insurers to prove their AI underwriting models are fair, explainable, and governed — not just documented. Regulators want evidence, not policy binders.
Take the AssessmentCircular Letter No. 6 sets clear expectations for insurers using AI and external data in underwriting — with a focus on fairness, transparency, and accountability.
Insurers must test whether AI models and external data sources produce unfairly discriminatory outcomes — even indirectly through proxy variables.
Underwriting decisions driven by AI must be explainable to regulators, consumers, and internal stakeholders in clear, non-technical terms.
Governance of AI underwriting must include board-level accountability with documented oversight structures and escalation paths.
Insurers are responsible for AI outcomes from third-party vendors and data providers — requiring due diligence and ongoing monitoring.
Most insurers cannot explain how their AI models reach underwriting decisions — and regulators are no longer accepting that.
Complex ML models make underwriting decisions that even data science teams struggle to explain — leaving compliance teams without answers for regulators.
External data sources introduce proxy variables for protected classes — creating discrimination risk that traditional testing methods miss entirely.
Pre-deployment model validation doesn't capture what happens in production. Regulators want proof of ongoing governance — not one-time assessments.
NYDFS expects continuous, demonstrable governance over AI underwriting. Most insurers are nowhere close.
Trussed provides the governance infrastructure insurers need to prove compliance — not just claim it. Every AI underwriting decision is governed, logged, and audit-ready.
Every AI underwriting interaction passes through Trussed's control plane — enforcing fairness, explainability, and data governance policies automatically.
Immutable audit trails capture every model decision, data source, and policy action — ready for NYDFS market conduct examinations.
Real-time dashboards track proxy discrimination risk, flag anomalies in underwriting outcomes, and surface issues before they become regulatory findings.
Understand where your organization stands on NYDFS AI underwriting compliance — and what gaps to close before your next examination.
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