bi & predictive analytics for government agencies

In Search of Insights andBetter Analytics

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BI & Predictive Analytics for Government Agencies

Prepared for: St. Louis Metropolitan Police Department

Nikolay Filipets/Ankit Patel/Melis Yilmaz/Divya Boyana


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Predicting CrimeWhy?

To improve operational performance To turn reactive thinking into proactive decision

makingTo improve ability to anticipate events and act

appropriatelyTo improve identification of high crime areas

Pattern analysisHot Spots

To deter crimes from taking place


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Predicting CrimeTraditional Policing Perspective

Helps to allocate patrols more efficientlyHelps to reduce response timesIdentifies targets and uncover security threats in time

to take action


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Hotspots Analytics ApproachThe most common method of “forecasting” crime in police

departments is simply to assume that the hot spots of yesterday are the hot spots of tomorrow.

Longer Time Period = More Effective A research found that examining past crimes over a one-month period

is not a particularly powerful predictor - hardly better than chance, yet one year of data predicts with 90% accuracy.

Hotspots may flare up and diminish over relatively short time periods, but the flare-ups occur in the same places over time, create long-term trends. So, police patrols must adapt to this dynamic risk.


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Our Hotspots Analytics Approach Common Hotspot Approach + Enabling Factors and Trigger Events

Variables Updated Monthly

• Alcohol Sales• Tourists• Unemployed

Residents• Released Criminals• Social Events• Receiving SS Benefits• Recidivism

Variables Updated Yearly

• Community Centers• Public High Schools• Hospitals• Universities• Public Transportation

Hubs• Liquor Stores• Mentally Ill Residents• Divorces• Impoverished

Residents


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Repeat Victimization “Hot Dots”Hotspots relying on shorter precious time

periods for predictive purposes is less effective.The concept of repeat victimization is a well

established method to track future crimeStudies have found that those individuals or

places that have been victimized once are likely to be victimized again, a few short months time.

Past victimization of individuals addresses, places, and business can be very accurate predictors of future victimizations, especially when relying on short time periods.


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High Level Model Framework

* Predictive analytics have the ability to combine a wide variety of data dimensions, types and sources on an ongoing basis!


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How Data is GatheredStatic Data- Annually

Resources Government Records Publicly Available Records

Dynamic Data- Monthly/Daily Resources

Police Records Government Records


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Decisions & OutcomesAllocation of patrol and police presenceTells criminals that they are being watched by

concentrating police officers in certain areas Identifies targets and uncovers security threats in

time to take actionDeters crimes from taking placeBuilds confidence among staff and with the publicHelps officers without the experience or intuition

in a particular areaReduces operational and IT costs through user

self-service reporting and analysisIncreases public safety and citizen satisfaction


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Additional Actions May Be TakenEducation of youth in high schools and promote

awareness to report home violence and suspicious activityPushing the idea of reporting abused, rape crimes

will help to predict the future more accurately because most of the abused cases go unreported

Involving community members through local newsletter or in monthly meetings

Possibly tying to get every business to have cameras to catch criminals

Tracking of families with family members who have criminal backgrounds


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Other Possible ApplicationsCyber crime profilingTraffic risk profilingSuspect vehicle

identificationForensics analysisInternal and external

terrorist threatsInclusion of citizen

feedback


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Questions

bi & predictive analytics for government agencies

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