BI & Predictive Analytics for Government Agencies

1. BI & Predictive Analytics for Government Agencies Prepared for: St. Louis Metropolitan Police Department Nikolay Filipets/Ankit Patel/Melis Yilmaz/Divya Boyana

2. Predicting Crime Why? • To improve operational performance • To turn reactive thinking into proactive decisionmaking • To improve ability to anticipate events and act appropriately • To improve identification of high crime areas • Pattern analysis • Hot Spots • To deter crimes from taking place

3. Predicting Crime Traditional Policing Perspective • Helps to allocate patrols more efficiently • Helpsto reduce response times • Identifies targets and uncover security threats in time to take action

4. Hotspots Analytics Approach • The 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.

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

6. 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 crime • Studies 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.

7. High Level Model Framework * Predictive analytics have the ability to combine a wide variety of data dimensions, types and sourceson an ongoing basis!

8. How Data is Gathered • Static Data- Annually • Resources • Government Records • Publicly Available Records • Dynamic Data- Monthly/Daily • Resources • Police Records • Government Records

17. Decisions & Outcomes Allocation of patrol and police presence Tells criminals that they are being watched byconcentrating police officers in certain areas Identifies targets and uncovers security threats in time to take action Deters crimes from taking place Builds confidence among staff and with the public Helps officers withoutthe experience or intuition in a particular area Reduces operational and IT costs through userself-service reporting and analysis Increases public safety and citizensatisfaction

18. Additional Actions May Be Taken • Education of youth in high schools and promote awareness to report home violence and suspicious activity • Pushing 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

19. Other Possible Applications Cyber crime profiling Traffic risk profiling Suspect vehicle identification Forensics analysis Internal and external terrorist threats Inclusion of citizen feedback

20. Questions