ERP News

Big data in the UK Police Force

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Of the 43 territorial forces in England and Wales, there are examples of individual forces that have recently piloted big data technology, with promising results

‘Police forces are facing a range of challenges today and are making the best of the current situation. Unisys has a wealth of industry expertise and a deep understanding of analytics, and we believe our experience can address some of these challenges. It’s about identifying the unknown, unknowns’

Launched at The Royal United Services Institute (RUSI) in Whitehall and commissioned by Unisys, the ‘Big Data and Policing: An Assessment of Law Enforcement Requirements, Expectations and Priorities’ report looks at the state of policing today and the opportunities for applying big data and analytical technologies in reducing crime in the UK.

 Interviewing current serving police officers and staff, the report found that local forces are utilising more advanced uses of analytics to improve policing, compared to national policing strategies relating to data.

Big data technology has revolutionised many industries, including the retail, healthcare and transportation sectors. ‘However, the use of big data technology for policing has so far been limited, particularly in the UK,’ says the report.

‘This is despite the police collecting a vast amount of digital data on a daily basis. There is a lack of research exploring the potential uses of big data analytics for UK policing.’

The research from the report identified a number of limitations in the UK police’s current use of data – the fragmentation of databases and software applications is a significant impediment to the efficiency of police forces, as police data is managed across multiple separate systems that are not mutually compatible, according to the report.

Application

Among the numerous ways in which big data technology could be applied to UK policing, four are identified as key priorities by the report.

Predictive crime mapping: his ‘could be used to identify areas where crime is most likely to occur, allowing limited resources to be targeted most efficiently.’

Predictive analytics: this ‘could also be used to identify the risks associated with particular individuals. This includes identifying individuals who are at increased risk of reoffending, as well as those at risk of going missing or becoming the victims of crime.’

Advanced analytics: this ‘could enable the police to harness the full potential of data collected through visual surveillance, such as CCTV images and automatic number plate recognition (ANPR) data.’

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