How ’Active Insurance’ Uses Real-Time Data to Prevent Cyber and Property Losses

Proactive risk prevention is rapidly reshaping the insurance landscape, particularly in cyber coverage. Coalition’s ‘active insurance’ model exemplifies this shift by leveraging real-time data, AI, and continuous monitoring to detect and defuse threats before they become claims. For insurance claims adjusters, this approach signals a move away from traditional reactive models and toward a dynamic environment where loss mitigation starts well before an incident occurs.

Coalition ingests trillions of data points each month to map internet-connected assets and identify vulnerabilities. Their system sends immediate alerts when malware activates on customer networks, enabling containment before ransomware can spread. They also locate misconfigured industrial systems, offering direct intervention to prevent service disruptions. This level of engagement reduces claim frequency while also creating a more nuanced risk landscape for adjusters to navigate when incidents do occur.

What sets this model apart is the tight alignment of financial incentives between insurer and insured. Since Coalition assumes financial responsibility when prevention fails, they’re motivated to deliver effective tools and insights. This alignment is still rare in cybersecurity and represents a potential model for the broader industry.

For adjusters, these innovations demand familiarity with prevention technologies and their limitations. As property and casualty insurers adopt similar tools—like IoT sensors or wildfire tracking—claims professionals must assess not only the damage but also the context of preventative measures and where they may have broken down. The evolution toward ‘active insurance’ marks a new era of collaborative risk management that is likely to influence claims handling across all sectors.