Predictive analytics and Policing: Translating cutting-edge academic research into actionable intelligence and developing useable software tools

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SummaryCriminological research has for some time focused on the types of people that commit crime and why they might do so. However, over the last decade, there has been substantial progress in research concerned with the complimentary question of whether there exist regularities in how, where and when crimes are committed. Such research has demonstrated that the risk of crime is not random, but that the risk of crime is greater for some people, in particular neighbourhoods, and at some homes. Similarly, research demonstrates that the risk of crime varies over time. For instance, crime is more likely at certain times of the day and months of the year. These findings have clear implications for operational policing and currently inform the crime reduction strategies adopted by many UK police forces. More recent academic research conducted by the applicants demonstrates that other regularities in crime patterns exist and that their identification can inform police decision-making in such a way so as to lead to the more effective use of police (and other) resources. For example, our research shows that when a burglary occurs at one location, others are more likely to occur at the same location or nearby in the near future. Put another way, the risk of burglary spreads in much the same ways as a communicable disease. Importantly, the identification of such regularities can provide intelligence that can inform what the police might do to prevent or detect crime. Furthermore, based on such findings, it is possible to develop mathematical models to generate predictions regarding the future locations of crime events. Such models have been shown to outperform existing methods of crime mapping. The ability to identify these kinds of regularities and to use them to inform police priorities or tactics is particularly important at a time when police budgets are being cut. However, because the types of analysis noted above are at the cutting edge of academic research, and were generated for research purposes, they cannot be conducted using available software. The aim of the proposed project is to bridge this knowledge-practice gap, identifying the most promising types of analysis and developing usable software packages that would make a real difference to police practice. The collaboration would facilitate a two-way exchange between police practitioners and academics and lead to the translation of cutting edge research into tools that can be used to prevent harm to society. We envisage that the project would also lead to the identification of new research questions that would inform the academic agenda.