The property/casualty insurance sector has long operated on a foundation of robust data analytics, with public sector information serving as a cornerstone for risk assessment, premium pricing, and claims management.

Executive Summary

The insurance industry heavily depends on publicly available data but recent White House actions and proposals threaten to discontinue or disrupt governmental data collection. Here, Roots Chaz Perera, Co-Founder and CEO of Roots, outlines six steps for insurers to navigate the new data landscape including investments in agentic AI capabilities and collaborations within the industry and measures to ensure compliance and transparency of data sources and algorithms used to substitute for disappearing public data.

However, recent White House overtures to discontinue or disrupt governmental data collection and reporting have created a significant challenge for insurers relying on these information streams. This evolving landscape requires insurers to take decisive action to maintain operational efficacy and high service standards for policyholders.

The Growing Data Scarcity Challenge

The reduction in publicly available datasets represents a fundamental shift in how insurance companies approach risk assessment. Key areas experiencing data limitations include:

Weather and climate data, critical for P/C insurers assessing natural disaster risks. Public health and mortality statistics, essential for life and health insurance actuarial calculations. Crime statistics, necessary for property insurance risk assessment in various regions. Infrastructure condition reports, vital for commercial property and liability coverage. Workplace safety records, fundamental for workers compensation insurance. Traffic accident data, core to auto insurance pricing models. Demographic and socioeconomic trends, underpinning many insurance risk models. Environmental risk assessments, critical for property insurance in vulnerable areas.

These information gaps create operational challenges for insurers who have built sophisticated models based on continued access to this type and scale of information.

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