Core Functionality of iOPS

Developed with the Metropolitan Police Service.(New Scotland Yard)

Freya Newman, MSc

Centre for Investigative Psychology

The University of Liverpool, UK

www.i-psy.com

Comparative Case Analysis

Q1: Can I link undetected crimes together?

Q2: I have an offender with a particular offending style. What other crimes is he good for?

Q1: Can I link undetected crimes to a common offender?

Burglaries

Structural Analysis of Behaviours

Posed (42)

Behavioural similarity of crimes

Identify crime series

All the same offender

Q2: I have an offender with a particular offending style. What other crimes is he/she good for?

Burglaries

Posed & distraction?

Burglaries

Posed & distraction

Crime series

Suspect Prioritisation Who dunnit?

Geography AND Behaviour to prioritise suspects

Geography Prioritises offenders by the location of

their (home) base(s) iOPS does this with Dragnet

Geographical ‘profiling’ system Developed at CIP Integrated within iOPS

Principles of Dragnet Offenders tend commit crimes close to

home As distance from home to crime

increases Probability of committing the crime decreases

Distance decay

Source, Professor Canter, iOPS presentation, September 2004

Our Example

Known offenders?

Our exampleX = Prioritised offenders

= Known offenders= Crimes in series

Offender ID Address Probability

MO Match

124 Location A 0.28574311864 0

427 Location B 0.27038233898 0

427 Location C 0.26035169492 0

226 Location D 0.25577861017 0

48 Location E 0.23282991525 0

124 Location F 0.22445984746 0.3

124 Location G 0.21932662712 0

Prioritisation table

Our exampleX = Prioritised offenders

= Known offenders= Crimes in series

MO Matching

Behaviours in crimes

Behaviours of known offenders

climb sharp smoke defecate

Offender ID Address Probability

MO Match

124 Location A 0.28574311864 0

427 Location B 0.27038233898 0

427 Location C 0.26035169492 0

226 Location D 0.25577861017 0

48 Location E 0.23282991525 0

124 Location F 0.22445984746 0.3

124 Location G 0.21932662712 0

Prioritisation table

Social Network Analysis

Offender ID Address Probability MO Match124 Location A 0.28574311864 0427 Location B 0.27038233898 0427 Location C 0.26035169492 0226 Location D 0.25577861017 048 Location E 0.23282991525 0124 Location F 0.22445984746 0.3124 Location G 0.21932662712 0