Data Governance Priority

Insurance boards discuss technology investment frequently. Data governance -- the policies, processes, and accountability structures that determine the quality and integrity of data -- rarely makes the agenda until something has gone wrong.

The consequences of poor data governance in insurance are slow-building and then sudden. Pricing models built on unreliable data produce loss ratios that surprise. Regulatory reports filed with inconsistent data produce examination findings. AI models trained on ungoverned data produce recommendations that are difficult to defend.

The carriers building durable data capabilities have elevated data governance to the same organizational status as financial controls -- not as a technology initiative but as a management discipline with executive ownership and board visibility.

The investment required is not primarily in technology. It is in process: defining what good data looks like, who is accountable for producing it, and what happens when it does not meet standard.