What is the role of data and analytics in evolving claims practice, especially pre-claim?

• A. They replace all adjusters in the field with automated systems.
• B. They have no effect on the claims handling process.
• C. They enable proactive risk assessment and pricing, and improve claim handling by anticipating trends.
• D. They are only used for regulatory reporting.

Answer: (C)

Data and analytics give insurers foresight in claims practice, especially before a loss occurs. By combining internal information (policy terms, exposure, past claims) with external data (weather patterns, location risk, telematics, economic factors), predictive models can produce risk scores and predicted loss trajectories. This enables proactive risk assessment and pricing—setting premiums and terms that reflect expected costs—and it supports proactive loss prevention and resource planning. It also sharpens claim handling by spotting emerging trends early, enabling proactive outreach, faster triage, and targeted investigations or interventions when a claim does occur. In short, analytics turn data into actionable insights that help prevent losses, price more accurately, and manage claims more efficiently. These insights aren’t about replacing adjusters or only for regulatory reporting; they enhance decision-making across the pre-claim and claim lifecycle.