On both sides of the Atlantic, business analytics software has become
the latest hi-tech tool in the fight against crime, helping to assess
the potential likelihood of young offenders or short-term prisoners
On both sides of the Atlantic, business analytics software has become the latest hi-tech tool in the fight against crime, helping to assess the potential likelihood of young offenders or short-term prisoners reoffending.
Predictive analytics has proven to be an extremely effective approach in the identification, characterisation, modelling and prediction of potential threats. Ultimately, these tools enable law enforcement and security professionals the ability to anticipate, prevent, deter and respond in a more effective manner.
In her paper, Actionable Mining and Predictive Analytics for the Applied Public Safety and Security Community*, Dr Colleen McCue who pioneered the use of data mining and predictive analytics in crime analysis in the US while programme manager at Richmond Police Department explains that the benefits of using predictive analytics in the applied public safety and security setting are twofold.
First, the early identification and characterisation of a potential threat presents more options for prevention and deterrence. Targeted prevention strategies also offer a greater return on the public safety investment by supporting the effective allocation of resources. Personnel, in particular, represent an extremely valuable resource in public safety and security. The ability to proactively place personnel resources when and where they are likely to be needed increases their potential efficacy, while minimising redundancy and waste. Moreover, prevention is almost always less expensive than response and recovery, particularly when measured in human terms.
Second, the use of predictive analytics in the applied public safety and security setting supports information-based response planning foreknowledge of a potential threat may not be sufficient to prevent it, but the number of lives saved by targeted response planning can be significant.
The US state of Floridas Department of Juvenile Justice (DJJ) unveiled plans last month to introduce an analytics software platform in a bid to reduce the number of crimes committed by young offenders. It comes as Floridas juvenile crime rate continues to decrease to the lowest levels across the state since records began tracking the statistic in 1990.
By deploying the analytics platform from IBM SPSS, the department aims to reduce this figure approximately 85,000 individuals each year by better understanding and properly adding rehabilitation programmes to young offenders.
The predictive analytics software will allow Floridas DJJ to analyse predictors (such as past offence history, home life environment, gang affiliation and peer associations) to better understand and predict which youths have a higher likelihood to reoffend.
The deployment in Florida comes just weeks after the UK Ministry of Justice (MoJ) announced that the predictive analytics platform was now being used to assess the potential likelihood of prisoners reoffending after their release.
Mark Greenwald, chief of research and planning at the Floridas DJJ, explained: The state of Florida believes that if youths are rehabilitated with effective prevention, intervention and treatment services early in life, juveniles will not enter the adult corrections system.
Our goal is to ensure juveniles do not return to the system. Predictive analytics will allow our organisation to refine our current practice and better intervene in juvenile lives earlier to help them become and stay law-abiding citizens.
Deepak Advani, vice president of predictive analytics at IBM, explained that predictive analytics gives government organisations worldwide a highly-sophisticated and intelligent source to create safer communities by identifying, predicting, responding to and preventing criminal activities.
It gives the criminal justice system the ability to draw upon the wealth of data available to det