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Targeting Factors that Predict Clearance of Non-domestic Assaults

  • Tom OlphinEmail author
  • Katrin Mueller-Johnson
Chapter
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Abstract

The research described in this chapter identifies solvability factors for non-domestic violent offences and then develops this research by building an algorithmic prediction model for the solvability of violent crime before testing it against an existing experiential model. It is based on a complete population of 29,105 violent offences reported to the UK’s West Midlands Police between 1 March 2012 and 31 December 2013. The data set was split in half, with one half being used to build the model and the other to test its accuracy. Twenty-five solvability factors were identified, along with thirteen case-limiting factors, which allowed a logit model to be built to predict the solvability of cases. Despite the cut-off point for inclusion being adjusted to minimise the impact of incorrectly filed reports, and additional opt-in factors being included to reduce damage to public confidence, the new algorithmic model was 22.16% more accurate than the existing experiential crime-screening model used by West Midlands Police.

Keywords

Clearance Solvability Violent crime Prediction Algorithmic prediction Experiential prediction Predictive accuracy 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Institute of Criminology, University of CambridgeCambridgeUK

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