Page 26 - 1Proactive Policing

Pro-Active Policing

A preliminary report from the FBI indicates that during the first half of 2013, violent crime dropped
5.4% in the United States relative to the same period in 2012. The drop was consistent for cities

both small and large — from under 10,000 inhabitants to more than 1 million — and across the
four U.S. geographic regions. The reduction was smaller than those for 2008-2009 (-6.1%), 2009-
2010 (-6.2%) and 2010-2011 (-6.4%), but it is a substantial improvement over the 1.9% increase

in violent crimes from 2011 to 2012.

Predictive policing systems typically rely, at a minimum, on historical data held by the
police — records of crimes reported by the community, and of those identified by police on
patrol, for example. Some systems seek to enhance their predictions by considering other

factors, like the weather or a location‘s proximity to liquor stores.

It should come as no surprise that the man who introduced computer-driven performance
management — known originally as Comp Stat — to policing, is generally credited with
envisioning how predictive policing could help fight crime. New York City‘s once and current

Police Chief William Bratton saw predictive analytics as a way to anticipate gang violence,
burglaries and thefts when he was chief of police in Los Angeles back in 2008. In 2011, the L.A.
police used predictive analysis to cut property crime by 12 percent in one neighborhood. Bratton

suggested that predictive policing could have a real impact when used in conjunction with existing
policing techniques, such as community policing.

Crime prevention has always been to some extent about prediction. Law enforcement officers
know by experience and by their street sense they can expect certain types of crimes in certain

areas of their jurisdictions at certain times. For example, it doesn't take the world's greatest crime
analyst to predict that auto burglaries will soar in shopping malls during the Christmas season or
that muggings will increase in working class neighborhoods around payday.

 Predicting the success of a movie based on its online ratings

 Many universities, sometimes in partnership with other firms use predictive analytics to
provide course recommendations to students, track student performance, personalize
curriculum to individual students and foster networking between students.

 Predictive Analysis of Corporate Bond Indices Returns

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