Unmanned aerial systems (UAS) are increasingly being used for smuggling, sabotage, espionage, and infrastructure attacks, yet most organizations still have no reliable way to price the risk. This paper offers a practical, attribution-based framework for turning UAS incidents into real economic figures across seven loss categories: human harm, direct property damage, business interruption, security and remediation spending, insurance effects, indirect economic impacts, and environmental costs. Drawing on open-source case evidence from aviation disruptions, prison contraband smuggling, border narcotics trafficking, and attacks on energy infrastructure, we show that indirect costs such as business interruption, remediation, and reputational harm often outweigh the direct damage, especially in aviation, logistics, corrections, and critical infrastructure. The framework pairs event-based loss estimation with scenario analysis to capture how incident types and countermeasure maturity vary, while applying clear attribution rules that separate confirmed losses from speculative claims. This helps address persistent data gaps, including inconsistent incident definitions and fragmented financial disclosures. We walk through worked loss calculations and a cost-benefit comparison to identify where security investments such as detection, access control, and incident response deliver the strongest returns. Ultimately, this gives operations and risk managers a shared, transparent way to prioritize UAS-related security spending, benchmark organizational resilience, and fold drone risk into broader enterprise risk management and insurance strategy.

Keywords

Unmanned aerial systems, Economic loss, Risk management, Security investment, Insurance