FlagThis

Abstract

**:** Quantifying the Return on Investment (ROI) of Cyber Threat Intelligence (CTI) poses a measurement problem: successful prevention produces non-events that leave no observable financial signal, which makes CTI spending resistant to traditional cost-benefit analysis. CTIs indirect contribution through downstream controls further complicates causal attribution and the investment boundary. We develop a framework with two main contributions: (i) the Threat Intelligence Effectiveness Index (TIEI), a weighted geometric maturity measure spanning intelligence quality, enrichment, integration, and operational impact that penalizes weak links; and (ii) a breakeven-first financial method that treats the annual probability of a scope-matched material event and CTI-attributable mitigation as unknowns and characterizes the combinations required for positive ROI. The financial boundary includes core CTI ownership and the incremental downstream costs required to operationalize intelligence. Applied to illustrative finance and healthcare scenarios, the method demonstrates how organizations can derive scope-matched breakeven requirements without treating broad sector prevalence as an event probability. A TIEI-conditioned PERT simulation illustrates how uncertainty can be propagated after an organization supplies a defensible event probability, while operational and qualitative indicators support attribution where avoided events cannot be observed. By linking operational maturity to an auditable financial boundary, the framework provides a reproducible basis for CTI investment decisions.