Abstract

Decision-making processes are increasingly based on intelligence gained from ‘big data’, i.e., extensive but complex datasets. This evolution of analyzing complex data using methods aimed at prediction is also emerging within the field of quantitative criminology. In the context of crime analysis, the large amount of crime data available can be considered an example of big data, which could inform us about current and upcoming crime trends and patterns. A recent development in the analysis of this kind of data is predictive policing, which uses advanced statistical methods to make the most of these data to gain useable new insights and information, allowing police services to predict and anticipate future crime events. This article presents the results of a literature review, supplemented with key informant interviews, to give insight into what predictive policing is, how it can be used and implemented to anticipate crime, and what is known about its effectiveness. It also gives an overview of the currently known applications of predictive policing and their main characteristics.