Adverse Consumer Outcome

An adverse consumer outcome is a negative result for a policyholder or applicant that flows from an insurance decision. Common examples include a coverage denial, a premium increase, a claim underpayment or denial, a benefit reduction, or a delay in care authorization.

Regulators use the concept to prioritize AI oversight. Systems that can produce adverse consumer outcomes are usually classified as high-risk. The NAIC Model Bulletin requires insurers to identify and manage risks that could lead to adverse outcomes, and to maintain records showing how those risks are controlled.

The practical test is whether a wrong AI output would harm a real consumer. If yes, the system needs stronger governance, human oversight, and documented testing. See our analyses of AI in health insurance and agentic AI in claims.