Assessing Terrorist Risks: Developing an Algorithm-Based Model for Law Enforcement

Assessing the risk posed by terrorist groups has always been a challenge for national security intelligence analysts. The most noticeable obstacles are, on one side, the limited availability of reliable information about violent groups and, on the other side, the absence of objective as well as rigorous assessment methods. This paper aim to outline the basic principles of a risk-based approach to terrorism threat assessment, which integrates algorithm models in order to provide more accurate situational awareness and orient strategic decision-making process. This paper is divided in three sections: first we introduce the readers to the objectives of strategic terrorism risk assessment. Second, we provide a comprehensive critic of existing terrorism threat assessment. Third, we develop an alternative logic model based on several factors related to the threat, vulnerability and uncertainty (error term).Finally, the paper suggest a methodology that takes in account the integration of risk factors drawn from theoretical and “real life” law enforcement