BI Applications For Crime Intelligence :
Data Mining & Predictive Modeling
Dr. Rado Kotorov
Technical Director Strategic Product Mgt.
Forward Looking BI with Predictive Analytics
Future
Events
Predictive
Modeling
Past Events
Reporting &
Analysis
Re-active Actions
Pro-active Actions
• Events have occurred
• Analyze cause
• Adjust processes to
• Events have not occurred
• Expect when & where
• Allocate resources to
prevent
prevent
What is the best that can happen?
Predictive Modeling
What will happen next?
Forecasting/Extrapolation What of these trends continue?
Statistical Analysis
Why is this happening?
KPIs/Alerts
What actions are needed?
Query/Drill Down
Where exactly is the problem?
Ad Hoc Reports
How many, how often, where?
Standard Reports
What happened?
Rear View
Optimization
Forward View
Forward Looking BI: Answer a Different Set of Questions
Degree of Intelligence
Note: Adapted from “Competing on Analytics”
How Does Predictive Analytics Help You Make Better
Decisions: Issue 1
65000
 Situation: Large
Issue: How do
you determine
what the right
pattern is
55000
Income Level
volumes of
historical data
y = 1414.5x + 25798
R² = 0.8378
60000
50000
45000
40000
35000
30000
25000
20000
0
5
10
15
20
25
Crimes
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How Does Predictive Analytics Help You Make Better
Decisions: Issue 2
 Situation: Large
number of variables for
analysis
 Issue: How do you
determine which
variables are more
important.
Not all factors have
equal weights
The more factors the
harder to determine
their weights
Crime
Number of
Crimes
Number of
Officers
Community
Events
Unknown
Weather
Conditions
Economic
Factors
Demographics
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Predictive Modeling and Scoring Applications
Predictive Modeling: Predictive modeling is a process that: (1)
takes as input historical data, (2) evaluates it statistically to detect
hidden patterns in it, and (3) derives a formula or set of rules that
describe the uncovered patterns, referred to also as a model.
-- A pattern can be a relationship or an outcome
Scoring Application: A scoring application automates the use of
the model on new records in order to predict relationships and
outcome probabilities.
-- Relationship: higher unemployment rates increase crimes
in lower income areas
-- Outcome: There is a high probability of aggravated
assault occurring in dispatch zone X
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When Is a Scoring Application Useful?
 It is useful where operational users have to make
decisions that involve uncertainty and risk.

It estimates the probabilities associated with the
expected events, i.e., the likelihood that the event
will occur.
 The probability estimates help managers make
better decisions than guessing.
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Everyone Makes Decisions Abut the Future
When?
Dispatch
Patrol
Cars
Where?
Correlated
Events?
Gut feeling or
science?
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Predicting Crime
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Possible Use & Value of Predictive Policing
From 1st Annual NIJ Predictive Policing Symposium
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Time and location of future incidence in a crime pattern or series
Identify individuals who are likely to reoffend
Inmate radicalization risk assessment (i.e., identify inmates who are in danger)
Drug market displacement (i.e., where next open air drug market will pop up)
Disorder and environmental variables
Likely impact of specific operations.
Disruption of criminal organization (criminal leadership)
Prediction of criminal adaptation (not only law enforcement efforts but also media, etc.)
Data analysis and support of crime suppression analysis
Patrol staffing and resources allocation
Localized crime spikes
Identify juveniles likely to be involved in violent crime
Risk assessment of sex offending in juveniles
Early identifications of career criminals
Identify victims of unreported crimes
Evaluation of interventions
Impact of drug enforcement on markets and allied crimes
Identification and analysis of crime-prone events and locations
Individual-specific analysis
Travel of serial offenders
Copyright 2007, Information Builders. Slide 10
Possible Use & Value of Predictive Policing
From 1st Annual NIJ Predictive Policing Symposium
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Analysis of predatory patterns
Correlation of environmental factors outside of crime like weather
Threat and vulnerability assessment
Prioritization of sources
Unstructured data extraction (police reports, blogs, incident reports and social networks)
Predicting acts of terror
Predicting riots
Social network analysis
Video analytics (including behavioralistics)
Use of NIBRS to help prediction
Wide-area surveillance for video fusion
Precursors and leading indicators to crime (including non-obvious predictors)
City/neighborhood planning
Design of spaces; economic development; security resource allocation; infrastructure protection
Offender monitoring, predicting behavior, endpoint sentencing
Traffic management, crowd control
Management of police personnel
Professional development, recruitment
Risk for excessive use-of-force, discipline
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Process For Building And Deploying Predictive
Applications
CRISP-DM Process Model ( http://www.crisp-dm.org )
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RStat: Differentiators & Benefits
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Based on R-Project
 Open Source
 Maintained by world wide consortium of universities, scientists,
government funded research organizations, statisticians.
 Over 2000 packages
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RStat is a GUI to R
 Intuitive guided approach to modeling
 Simple model evaluation
 Intended both for business analysts and advanced modelers
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Single BI and Predictive Modeling Environment
 Re-use metadata and queries
 Perform data manipulation and sampling
 Build scoring applications
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Unique Deployment Method for Scoring Solutions
 Scoring models are built directly into WF metadata
 Deployment on any platform and operating system - Windows, Unix,
Linux, Z/OS, and i Series.
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Thank you
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