In a recent interview with Aryng (http://www.Aryng.com), SCPD crime analyst, Zach Friend described how SCPD was going through a difficult time last year with 20% reduction in staff and 30% increase in calls for service. With less resources available to deal with more, there were called for efficient allocation of their resources, and that they did. SCPD had a significant amount of high quality crime data; with which they contacted Dr George Mohler, Mathematics Professor at Santa Clara University. Professor Mohler along with a research team comprising of criminologist and anthropologist took all of the complex crime data and converted it into simple points that a line-level police officer could use for checks during shifts, even without understanding of algorithms and inputs.
The results: 19% reduction in burglary in last 16 months and 25+ arrests solely because of the tool. LAPD who has also deployed this same tool, has seen 25% reduction in burglaries, saving over $4 Million in costs to the community.
But burglaries are common crimes with higher incidence vs. mass killings. Can Predictive Analytics be used in these scenarios?
Pauline Arrillaga explores how to prevent mass killings like Aurora, citing the work done by forensic clinical psychologist Dewey Cornell, whose team has developed an assessment guideline to identify threatening individuals. These guidelines are being used by most public schools to pre-empt shootouts like Columbine. Such guidelines along with other purported predictors generated with the help of crime experts (like massive purchase of guns by a person who hasn’t owned a gun before) can form the hypothesis to build a predictive model to identify threatening individuals.
Credit industries have long used an individuals’ demographic data married to purchase behavior to predict their credit worthy-ness. This same technique can be used with additional relevant data like gun purchase, crime data etc. to create a “potential threat” score.
Whether, the Predictive Policing model, as it now stands, can predict a crime like the Colorado shootout or not, it is certain that, in the foreseeable future, major police departments and law enforcement agencies would be employing techniques similar to the Predictive Policing model aimed at pre-empting mass crimes and making the world a safer place to live in!
To learn more about the power of analytics, read Aryng’s blog posts and articles on http://www.Aryng.com/blog.
About the Author: Piyanka Jain, President and CEO of Aryng – a premier analytics training and consulting company, is a well-regarded industry thought leader in analytics, keynoting at business and analytics conferences including Predictive Analytics World, Data Science Summit, TDWI Big Data Conference, and regular contributor to publications like Forbes, SAS Knowledge Exchange, B-eye-network, to name a few.
For the original version on PRWeb visit: http://www.prweb.com/releases/prwebAryngAnalyticsNews/PredictingCrime/prweb9736662.htm