Identifying Terrorists using Banking Data

Abstract

The fight against terrorism requires identifying potential terrorists before they have the opportunity to act. In this paper, we investigate the extent to which retail banking data – which as far as we know are not currently used by anti-terror intelligence agencies in any systematic manner – are a useful tool in identifying terrorists. Using detailed administrative records of a large British bank, we demonstrate that a number of variables in the data are strongly correlated with terrorism-related activities. Having both an Islamic given name and surname, not surprisingly, are among the strongest of these predictors, but a wide range of other demographic characteristics and behaviors observed in the data are also correlated strongly with terrorist involvement. The real key to our method, however, rests on the identification of one particular pattern of banking behavior (what we call “Variable Z”) which dramatically improves our ability to identify terrorists. Our model is demonstrated to have substantial power to identify terrorists both within sample and out of sample.