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Proven Crime Reduction Results

Using only three data points – what, when and where – in making predictions, PredPol’s technology has been helping law enforcement agencies to dramatically reduce crime in jurisdictions of all types and sizes, across the U.S. and overseas. There is a proven track record of crime reduction in communities that have deployed PredPol. Predictions use no personal information about individuals or groups of individuals, eliminating any personal liberties and profiling concerns.

Deputy Chief Steve Clark“We found that the model was just incredibly accurate at predicting the times and locations where these crimes were likely to occur…at that point, we realized we’ve got something here.” Santa Cruz Police Department Deputy Chief Steve Clark (Al Jazeera America, September, 2013)

Recent Examples of Crime Reduction

  • The Los Angeles Police Department’s Foothill Division saw a 20% drop in predicted crimes year over year from January 2013 to January 2014 and experienced a day without crime on February 13, 2014.
  • In Los Angeles’ Foothill Division, crimes were down 13% in the 4 months following the rollout compared to an increase of 0.4% in the rest of the city where the rollout had not happened. Over this time period Foothill Division was a leader in crime rate reduction among LAPD’s divisions. Similar reductions have been seen in other cities that implemented the tool.
  • During Atlanta’s initial launch, aggregate crime decreased by 8% and 9% in the two areas that first deployed PredPol in July 2013. Of the four zones where PredPol was not deployed, crime rates increased by 1 to 8% in three and remained flat in one. Due to these successful results, the Atlanta Police Department decided to implement PredPol citywide in November 2013. Atlanta Police Department has seen aggregate crime drop 19% and attribute much of the sustained reduction to PredPol’s deployment.

  • The Alhambra, CA Police Department reported a 32% drop in burglaries and a 20% drop in vehicle theft since deploying in January 2013. The city reported its lowest month of crime in history in May 2014.
  • The Norcross, GA Police Department has had a 15-30% reduction in burglaries and robberies just four months after deploying in August 2013, and Captain Bill Grogan has stated that predicted crime is down 22.7% when comparing 10 months using PredPol to the same 10 months before using PredPol.
  • The Modesto, CA Police Department recently reported the lowest crime rates in 3 years since deployment in January 2014, including an 18% reduction in residential burglary and a 13% reduction in commercial burglary.
  • The Santa Cruz, CA Police Department saw assaults drop by 9%, burglaries decrease by 11%, and robberies down 27% in its first year using the software (2011-2012). Crime overall dropped 25% in June 2013 and 29% in July 2013 compared with those same months the previous year.

Chief Mark Yokoyama“All PredPol looks at is date, time, location and crime – our car burglaries, our car thefts all went down last year – in fact substantially.” Alhambra, CA Police Chief Mark Yokoyama (NBC Los Angeles, March, 2014)

PredPol is a Force Multiplier for Law Enforcement Agencies

Helping to Reduce Municipal Costs

Reductions in crime from predictive policing save law enforcement, courts, jails, and communities hundreds of thousands to millions of dollars per year. While crime reduction statistics differ from community to community, a jurisdiction that experiences a 20% crime reduction translates to 20% less time filling out reports and 20% less time in court, freeing officers up to spend more time policing on the beat and engaging in their communities.

Proven Buy-In by Officers & Crime Analysts

In 6 month randomized controlled trials, crime analysts who used PredPol technology in addition to their existing tools were twice as effective as experienced crime analysts who did not. Novice or newer police officers have come up the learning curve faster while veterans have added to their institutional knowledge.

1 Comment

  1. Blog #4 – About Artificial Intelligent[AI] – Jihoon's blog
    April 22, 2018

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