1. ‘Predictive Policing’, ‘Preventative Policing’
or ‘Intelligence Led Policing’. What is the
future?
Joe Newbold FCCA
MBA Student
Consultancy project submitted in assessment for Warwick MBA programme

2. Table of Contents
I. Executive Summary................................................................................................1
II. Introduction........................................................................................................... 3
What is Predictive Policing?...............................................................................................................................3
III. Objective and method ........................................................................................... 5
IV. History of crime..................................................................................................... 6
V. Policing in 2015...................................................................................................... 7
Demand on policing............................................................................................................................................9
‘Crime mapping’.................................................................................................................................................10
‘Optimal Forager and Repeat Victimisation’.................................................................................................12
‘Recency, Frequency and Gravity (RFG)’......................................................................................................14
Sensor Network – Dutch National Police.....................................................................................................16
VI. The future of policing...........................................................................................17
How will policing change and when? .............................................................................................................17
Child Sexual Exploitation.................................................................................................................................18
Serious and Organised Crime ..........................................................................................................................20
Cyber crime.........................................................................................................................................................21
Natural Language Processing...........................................................................................................................23
Evolution of existing methods ........................................................................................................................25
VII. Displacement and diffusion of crime.................................................................. 27
VIII. Summary and conclusion.................................................................................... 29
IX. Glossary ................................................................................................................31
X. Acknowledgements ............................................................................................. 32
XI. Bibliography ........................................................................................................ 33

3. 1
Executive Summary
There is no evidence to suggest predictive policing is completely ineffective, it has generated the following results from
the methods used and the trails conducted:
 An increase in predictive accuracy of 60% (Kent Police: PredPol)
 Crime hit rates rose from 5% to 11-19% (Kent Police: PredPol)
 42% drop in crime in City of Lancaster, USA (IBM SPSS modeller)
 26.6% reduction in burglaries (Greater Manchester Police: Optimal Forager)
 Reduction of domestic violence reoffenders increased from 35-37% to 62-65% (Strathclyde Police: RFG)
 Reduction in harm score of 27% in relation to domestic violence (Essex Police: RFG)
There are other methods in use across the UK market but specific data was not available for these during the preparation
of this report. Cheshire, the MET, Avon & Somerset to name a few are working on various evaluations, the results of
these have either not been public or accessible; therefore this data is not included in this report.
This report is split into two distinct sections; the here-and-now and the future. The here-and-now utilises information
gathered first hand, traditional academic theories and proven results to bring together the current efforts being made to
explore predictive policing and modelling by UK police forces. The future is very different, it attempts to guess the
evolution of local policing demand, takes ideas and conceptualises the use of technology and data to enable police forces
to focus on increasing crime prevention, helping victims and provided a first class and improved service to those they are
committed to serve.
The original title of this report was “Is ‘Predictive Policing’ a practical, viable and effective tool for 21st century crime
prevention?”, however, upon further reflection throughout the course of my research it seemed more appropriate to
change it to match the flow of the information, research and theories presented. Hence the change to “’Predictive Policing’,
‘Preventative Policing’ or ‘Intelligence Led Policing’. What is the future?”
Predictive Policing is defined in the introduction of this report and is a wide and complex area commonly misused to
imply an advanced level of analytics to age old techniques such as crime-mapping, which are in essence a mobile, easily
accessible and simple form that helps in the visualisation of crime.
During the course of the discussions and interviews with UK police forces, one posed the question of “Are there any
predictive policing methods that you can say do not work?” the answer is no. From the evidence gathered and presented
in this report there is no absolute evidence that would suggest any form of predictive policing does not work. However,
the natural evolution to this question would be “Which one is most effective?” this is where the answer is totally dependent
on a number of factors that include but not limited to:
 Technological capabilities/hardware infrastructure
 Advancement in culture towards data-driven policing
 Access to mobile information provided to/and gathered from officers
 Operational or societal objective of chosen solution
 The continued enthusiasm of officers and the integration of modelling into force of National SOP’s
 Is the focus on improving crime statistics or understanding root causes/supply & demand of crime?

4. 2
Underlying the strapline ‘predictive policing’ is the need to understand the demand of crime, the influential factors creating
it and the situational awareness of the efforts police forces are carrying out. The current approaches are not truly predictive,
despite the evidence that has been published which supports this. They are data driven intelligence led methods that do
create efficiencies within policing, links in data and easily accessible visualisations. All-in-all enabling the police to have the
time to carry out the activities that not only best serve their communities but impact on their security and quality of life.
True predictive policing would require more than a few data sets, as some models currently utilise. What is really required
is something akin to that proposed by the Dutch National Police (as described in Section V).
When reading this report a continued focus should be on the use of data and technology in relation to assisting officers in
doing their job not replacing them. I propose that predictive policing in its current form is a toolbox of
strategies/techniques that naturally evolve into effective preventative measures that enable police to make an invaluable
contribution towards the safeguarding of potential victims and their communities.
A theory that alters the thinking towards the use of intelligence led policing is this:
“Criminals are altering the environment in which they operate by two means, direct and indirect. Direct (opportunistic); the
observation of their surrounding environment including monitoring the police and acting accordingly, Indirect (economical);
the shift towards the environment in which they have no control but chose to adapt their methods to fit with economic,
social and technological changes, the shift towards internet crime and sophisticated wire fraud is an example of this”
This is theorised in more detail in the displacement and diffusion section of this report.

5. 3
Introduction
What is policing? What do the police do? What should the police do? It has been the subject of an ongoing debate among
victims, offenders, the general public, the judiciary and the media for many years. Depending on who you ask, you’ll get a
number of different answers. To name a small number of their responsibilities, the police;
 Gather, monitor and analyse information and to prepare strategies that prevent crime occurring in the first
instance
 Support victims of crime and offer support,
 Provide support to the elderly and vulnerable,
 Attend community meetings,
 Monitor and manage safety at public events,
 Provide a reassuring presence in communities,
 Prepare crime reports, case files and attend/give evidence in court where appropriate; and
 Solve crimes
 Record and investigate crime
 Arrest offenders and prepare for court attendances
Police forces and the Commissioners in charge have a significant number of considerations; for the communities they
support it is vital the implementation of policing methods or techniques demonstrate a reduction in crime figures, to the
media they are a news story with any statistic forming the basis of a headline. Finally to the officers and staff they employ
there is a duty of care, development and work-life balance to consider.
What is Predictive Policing?
Predictive Policing has been used for a number of years, the term was probably first used by William Bratton of the Los
Angeles Police Department in 2008 (Perry, McInnis, Price, Smith, & Hollywood, 2010). “Predictive policing is defined as
the science that calculates risks in relation to a crime using (computer) models and relevant (police) data. The aim of
predictive policing is to explicitly relate the future to criminal behaviour or its generators, based on technology and models.
In addition, predictive policing also tries to predict intervention success and to fill in missing elements of criminal processes
(Rienks, 2015).
Predictive policing has seen reports and news articles citing it as ‘the minority report’1 2, given the technology, information
sharing and operational deployment of data techniques, this is simply not possible. It is unrealistic to expect an algorithm
to predict random events as depicted in the film and in fact the methods used behind the predictive policing across the
UK are far simpler than many may be led to believe.
In practice it is often the use of historic crime figures and relevant influential factors such as type, time and place. This is
not predictive policing, it is a visualisation or modelling of crime forecasting; a technique that has been around for many
years. There are examples of using modelling to streamline the utilisation of police workforces using factors such as football
matches, pay dates, lunar cycles, weather and school holidays, this is arguably a better use of data and could lead to more
accurate results within a predictive policing solution.
1 http://www.telegraph.co.uk/news/uknews/law-and-order/10059121/Minority-Report-policing-comes-to-the-UK.html
2 http://www.dailymail.co.uk/news/article-2437206/Police-tackle-burglars-muggers-using-Minority-Report-style-technology-tackle-
future-crime.html

6. 4
Predictive policing can become less effective than hoped when:
1. There is no clear expectation of predictive accuracy
2. There is not easy, remote and secure access to information
3. The effects of limited data access in relation to commercial solutions are not understood (e.g. prison releases)
4. There is no clear Return on Investment criteria in terms of financial, operational and societal objectives –
something that is now an essential tick box
There may never be a consensus on what predictive policing is given the number of different uses it has across policing
but the methods used and developed will inevitably be transferable between operational requirements and forces.

7. 5
Objective and method
The purpose of this review is to better understand the use of predictive policing across UK police forces, firstly by
understanding what those using it believe it to be. Then, by understanding the methods used for prediction, the areas in
which predictive policing is used and the results it is producing. This research will not conclude with a new definition,
model or approach but will conceptualise the use of data and technology in relation to prediction and prevention of crime.
During this review considerations will be given to other academic studies and influential factors that have a relevance and
impact on predictive policing, these will include displacement and diffusion of crime, variations in police perception by
the public, effectiveness of crime prevention techniques (stop-and-search), and Multi Agency Safeguarding Hubs
(MASH’s).
Conventional policing techniques will be explained alongside any predictive methods to understand the collective effect
on crime, while controlled studies have been carried out to establish the effectiveness of predictive policing, the basics
such as target hardening, cocooning and community guardianship play a fundamental part in the reduction of crime figures.
The review will be conducted using first-hand information gathered by interviewing experts in the field of predictive data
analytics, data mining & interpretation and data integration. All Police Forces in the UK have been given the opportunity
to provide information in relation to this review; from those contacted first hand evidence was provided by 21 forces.
Some specific information may not be contained in this report due to confidentiality
reasons but where possible all efforts will be made to provide the users of the report with
enough information to interpret any statements made. The slides in Appendices 5-6 went
sent out after initial contact had been made with relevant individuals in each force, these
were designed to visualise the concepts appropriate to the initial thoughts around this
report, some of which are no longer relevant but others are still relevant in relation to the
report as whole.
A search and review of relevant academic studies (including those references found within the references in this report),
commercial documents and associated information was carried out in order to provide relevant support or explanations
where required.

8. 6
History of crime
Since the early 1980’s policing in the UK has evolved to what is now unrecognisable to the institution and culture of that
period. But also – from 1981 acquisitive crime rose steadily to its peak in 1995 (table 1).
All crime steadily rose from 1990 to an overall peak in 2003/04 but has since reduced by 36%, however it should be noted
that upon further analysis we can see trends in theft and criminal damage tend to follow the overall trend of crime between
1990 and 2015 but other areas have increased in their prolificacy and exposure to the public.
With emerging issues during the 80’s being repeat victimisation , domestic violence, black and ethnic group experiences,
‘research conducted in the 70’s, 80’s and early 90’s, indicated that racism and racial prejudice in police culture were more
widespread than in wider society’ (Bowling & Phillips, 2003). In the 90’s however these trends definitely moved towards
anti-social behaviour (ASB), interpersonal crime, confidence in the justice system and drug abuse in younger groups.
(Jansson, 2007).
One area that needs careful consideration is the understanding of repeat victimisation. The British Crime Survey (BCS)
has been influential in highlighting the need to target crimes that are prone to repeat victimisation3 such as domestic
violence and vandalism (Gottfredson, 1984). Walby and Allen (2004) concluded that inter-personal violence is frequently
marked by very high rates of repeat victimisation, this report will also review methods that are pertinent to predicting and
anlysing crime and repeats of violence and sexual offences.
Is there a correlation between crime statistics, emerging issues, public perception and the technology/focus of police
forces? Is this due to the evolution and wider adoption of Predictive Policing that has been mainly focussed on acquisitive
crime? Is there an element of displacement and altering the trend of criminal behaviour; contrary to theories such as
Optimal Foraging?
Cybercrime has been in existence as long as the internet was created but its publicity and impact has changed considerably
in recent years. With trends of cybercrime continuing to increase in number, cost to police and cost to victims the demand
on local policing has inevitably changed and will continue to do so. Is this an example of criminals altering their
environment without any police intervention; contrary to the conventional theories (discussed later in the report).
3 Repeat victimisation is defined as being a victim of the same type of crime more than once in the last year where the perpetrator is
likely to have been the same and the incident of a similar nature

9. 7
Policing in 2015
In 2014/15:
 Acquisitive crime is at its lowest since 2002/03 reducing by 49%
 Violence against the person offences rose by 23% compared with the previous year, however this is thought to
reflect changes in recording practices
 Sexual offences increased by 37%, the highest since 2002/03. However this is thought to be due to the increased
willingness of victims to come forward
A uniform concern across policing are the estimates citing there to be 17,0004 to 22,0005 fewer officers by 2020. While
this is only a media report based on a report published by Her Majesty’s Inspectorate of Constabulary (HMIC) in July
2011, the estimated number of fewer officers during the period to 2015 was estimated to be roughly 34,100, only 3,257
fewer than the actual figure. Thus providing evidence that estimates made can be reliable and should be noted with due
attention. One saving grace given during the spending review, delivered in Autumn 2015, by George Osborne was that
police funding would be protected in line with inflation, until 2019-20206.
According to figures from the Office of National Statistics (ONS), total police workforces have decreased from a peak of
244,497 in 2010 to 207,140 in 20157. The reductions split by rank over this period are as follows:
Chief Officers 9.72%
Superintendents 22.95%
Chief inspectors 16.04%
Inspectors 21.45%
Sergeants 17.14%
Constables 9.77%
Police staff 19.95%
PCSO’s 27.11%
The Crime Survey for England and Wales (CSEW), since 1981, has asked the public a series of questions to obtain an
understanding of their perception of the police. The results of this survey were generally promising with an increase in the
percentage of individuals rating the police as good or excellent, the number of individuals having overall confidence in
local policing and the number of victims being very or fairly satisfied with the way their case was handled8
One statistic that may not be surprising is the percentage of people who reported seeing police officers or PCSOs on foot
patrol, 32%, down from the peak of 39% in 2010/11. Possible reasons for this are 1) the reduction in police workforce
has resulted in less foot patrols or; 2) the actual reduction in crime has resulted in the requirement for less foot patrols or;
3) the type of crime has changed whereby the requirement for foot patrols has decreased. Either way there are obvious
considerations at every turn for the commissioners of forces and the implementation of technology could assist with these.
How should police now prevent crime? Should they use a combination of technology and traditional policing to assist
them? The traditional approaches used in the prevention of crime, are tactics such as ‘stop and search’, increasing ‘dosage’
in problem areas (discussed later) and the issuing of Anti-social behaviour orders, but as crime evolves these may not have
the levels of impact they once had.
4 http://www.independent.co.uk/news/uk/politics/generalelection/general-election-2015-further-planned-cuts-to-police-budgets-
under-tories-says-theresa-may-10208096.html
5 http://www.theguardian.com/uk-news/2015/aug/31/police-force-new-spending-cuts-22000-jobs
6 https://www.gov.uk/government/news/spending-review-and-autumn-statement-2015-key-announcements
7 https://www.gov.uk/government/statistics/police-workforce-england-and-wales-31-march-2015-data-tables
8 http://www.ons.gov.uk/ons/dcp171776_399828.pdf

10. 8
There are operational, political and economic issues associated with all methods of crime prevention but in particular stop-
and-search tactics have always been subject to debate.
There has been no evidence to date to suggest that stop-and-search tactics have a direct link with either burglary or personal
crimes. The Scarman report concluded that the 1981 riots were as a result of an overzealous stop-and-search known as
Operation Swamp9. Since a peak in 08/09 of 1,519,561, stop-and-searches has reduced by 42% to 886,564, increasing
these may lead to a further reduction in trust between forces and those subject to stop-and-search tactics10 11.
Technological and data driven tactics, blended to work with current operating procedures, could prevent the issues forces
are facing. Any ‘target’ based cultures, that once led to an unethical policing12 incident could be condemned to the history
books should operational practices evolve and data driven policing work seamlessly.
9 http://news.bbc.co.uk/1/hi/uk/4854556.stm
10 http://www.bbc.co.uk/news/uk-england-london-33025853
11 http://www.theguardian.com/commentisfree/2015/oct/19/stop-and-search-riots-2011-section-60-knife-crime-police-chiefs
12 http://www.theguardian.com/uk/2012/nov/15/kent-police-arrested-statistics-irregularities

11. 9
Demand on policing
The demand on policing has changed and will continue to do so; a report by the College
of Policing13 has detailed the responsibilities and duties officers carry out. It has
become obvious that the increased transparency of policing has made it difficult to
compare certain crimes on a long-term basis and the increasing granularity at which
crimes get broken down does alter with emerging trends and demand, making historical
numbers non-comparable, thus giving the perception that certain crimes are increasing.
In order to put into concept the relevance and benefit of current and future data led or
intelligence led policing initiatives it is key to understand how crime trends and
demands have changed in the last 5 years; thereafter attempting to identify future trends.
To that extent a summary of the College’s report is as follows:
 Costs of crime for the police have not fallen as much as overall crime numbers
 Several crime types have increased since 2010; violence against the person up 17%, sexual offences up 64%, fraud
and forgery up 218%, public disorder has decreased since 2010 but jumped from 2013/14 to 2014/15 by 19%
 There were close to 1 million convicted non-notifiable crimes to 31 December 2013, these figures are not
represented in the national recorded crime statistics
 The average cost of crime increased by 25% between 03/04 and 13/14
 Rape offences have increased by 36% over the last 10 years; contribution to total ‘cost’ of crime increased from
6% to 12%14
 There is an indication in the complexity of cases; supported only by anecdotal information about an increased
number of offences
 201,035 fraud cases, up by 34% compared with year ending September 2013
 In the last two years the number of reported child sex offences has increased by 40%
 The number of CSE cases increased in the forces that provided information from 33% to 224%15
 In 2012/13 there were 19.6m recorded by the police
o 2.3m of these were anti-social behaviour related
o Just over 1m were for domestic abuse16
 Non-crime related incidents accounted for 83% of all Command and Control calls
Using this information it is obvious to see the requirement for efficient and effective crime prevention and vulnerability
prevention. During the remainder of this section current predictive policing methods used, trialled and evaluated across
UK forces will be reviewed.
13 http://www.college.police.uk/News/College-news/Pages/First-analysis-of-national-demand.aspx
14 An estimate of the cost of rape has been calculated using the ratio of serious violence to all violence costs
15 Period from 1 April 2013 - 30 September 2013 compared to same period in 2014
16 (HMIC, 2014) Everyone’s business: Improving the Police Response to Domestic Abuse

12. 10
‘Crime mapping’
Crime mapping is used by analysts in law enforcement to provide a visual representation of crime incident patterns. Using
a Geographic Information System (GIS) a system is designed to capture, and analyse types of spatial or geographical data.
Crime analysts can use GIS’s and overlay other datasets such as census demographics, schools, shops etc to better
understand any influential factors that may affect crime.
Crime mapping uses no academic theories and relies completely on the approach of intelligence led policing. Using
incidence patterns as the predominant form of intelligence restricts this method to the use of historic data. Without
knowing the specifics of individual crime mapping, techniques could vary in terms of the number of datasets used as part
of the visualisation process, as an example it could be limited to type, place and time of crime, arguably limiting the ability
to ‘predict’ crime and acting more as a resourcing tool for the efficient utilisation of a police workforce.
Bowers, Johnson and Pease (2004) stated that they believe there was latent predictive power in the approach which remains
to be explored. Even if the approach taken proves inferior at the area level, it would remain useful for deployment decisions
within hot spots designated by other means.
One software capability, exploring the predictive power of crime mapping is ‘PredPol’,
which claims to only use type of crime, place of crime and time of crime17; explicitly
excluding the use of any personal data. This software has claims of reducing burglaries by
15-50%, robberies by 27% and vehicle theft by 34%18, albeit within a controlled trial in
the USA.
Within the UK, Kent police were one of the pioneering forces to carry out predictive policing using PredPol, with success.
PredPol was first trialled in Kent in 2012, with full rollout being decided on April 29, 2013. The initial report19 has a
number of interesting results none more so than the obvious comparison against the incumbent analysts within Kent
police.
To begin, PredPol was loaded with 5 years of data but utilised 3 years for the purpose of its predictive
modelling. The hit scores for both Kent and PredPol were documented with PredPol coming out
more accurate at 8.47% vs 5.31%, a significant increase of 60% in the likelihood to predict crime
over traditional boxes, leading to an overall reduction in crime of 4%. It should be noted that a ‘hit
score’ is not defined in the report but I would define it as follows:
PREDICTED INCIDENT
ACTUAL
INCIDENT
No Yes
No NULL3 Miss1
Yes Miss2 HIT
1. Classified as a miss on the basis that police resources are wasted to prevent an incident that did not occur
2. Classified as a miss on the basis an actual crime happened due to the absence of a capable guardian
3. Classified as Null on the basis that it is a positive confirmation on a non-entity event, therefore not relevant
Hit is therefore ∑HIT/(∑HIT+∑MISS).
17 http://www.predpol.com/ company literature states only 3 data sets used for prediction
18 http://www.predpol.com/results/
19 http://www.statewatch.org/docbin/uk-2013-11-kent-police-pp-report.pdf

13. 11
As part of the analysis of PredPol the term ‘dosage’ was coined to determine the number of visits compiled with the length
of time spent in boxes. Continuing the years of skill built up by analysts and the ‘coppers nose’ developed by front line
officers PredPol was used an operational tool to default to when not attending an incident or emergency call. Initial results
found the interest in PredPol was high, its usability factor made it appealing to officers, but that interest waned after the
7th/8th month of usage, the results of PredPol were proven in the initial trials and rollout so this came as an unexpected
and unexplained trend.
One could argue whether a hit rate of 8.47% is suitable for the level of investment required for implementation and roll-
out. However I would argue that, from my interviews with Kent police there are unquantifiable benefits beyond merely
statistics that could be criticised. PredPol was allowed to grow organically and pitched as ‘21st century crime technology
meets traditional policing’ by the Chief Constable, PredPol wasn’t about the ability to reduce workforce numbers or
improve statistics but about a culture change; focussing on rebuilding trust and visible presence, while refining the working
practices of a force ready for intelligence led policing.
The initial report states that any presence or dosage was only effective for a period of 2 weeks,
thereafter crime rose back to original levels in the categories of violence, criminal damage and
ASB. What is interesting to note here is that during interviews with UK forces there was an interest
in acquisitive crime but a uniform drive to focus on moving towards vulnerability; PredPol was
most prevalent in non-acquisitive crime but there are suggestions it may have had an effect on
burglary.
Since the initial report a further operational review20 was carried out and the findings were as follows:
1. The average crime hit rate rose to 11% with the highest being 19%, with Kent hit rates remaining at 5%
2. Reductions in ASB, criminal damage and violence were sustained for 3 weeks without further intervention above
and beyond normal PredPol activity
3. PredPol generates 520 boxes per day; of which 16% are visited. During the North Kent trial 25% of boxes were
visited
The report concludes that PredPol does reduce crime and ASB when used, but results do not show an overall drop in
crime for Kent in the year under review. Given the cost of £100,000 per annum it would require an overall drop in crime
of 0.35% to match costs in financial terms; however the direct ROI of PredPol should be considered in relation to the
cost on society of the areas in which it focuses namely violence, criminal damage and ASB.
It is unquestionable that crime mapping works and has predictive possibilities as initially suggested by Bowers et al in 2004.
I propose that success lies in the operational implementation of any such system into everyday working practices. There
needs to be a predefined operational or societal objective (Appendix 1) that drives the correct engagement of crime
mapping given its simplicity and demonstrated propensity for long-term disengagement.
One important area to consider is how much relevance the reported crime drops in the USA can be replicated in the UK.
IBM have reported a drop in crime of 42% in the City of Lancaster21 with the initial starting point of 449.4 crimes per
10,000 residents. Using the Office of National Statistics estimate of UK population 64.6M22 and the reported crime figures
of 3,811,268, we have a crime rate of 590 crimes per 10,000 residents. Does this mean the UK is more crime prone than
the US?
No, the UK has one of the best recognised crime reporting criteria that expands and improves year on year. Currently
there is no substantial evidence to suggest the UK will or will not have the same results as the USA when using systems
like PredPol and IBM SPSS Predictive Analytics.
20 http://www.statewatch.org/docbin/uk-2014-kent-police-predpol-op-review.pdf
21 http://www-01.ibm.com/software/analytics/infographics/predictive-analytics/crime-prediction_750.jpg
22 http://www.ons.gov.uk/ons/rel/pop-estimate/population-estimates-for-uk--england-and-wales--scotland-and-northern-
ireland/mid-2014/index.html

14. 12
‘Optimal Forager and Repeat Victimisation’
The optimal forager theory originates from the observation of animals in the wild, the theory suggests that when animals
hunt they apply temporal constraints23 , energetic constraints24 and cognitive constraints25 to establish the level of
profitability from hunting (Sinervo, 1997-2006).
This theory was applied to the activity of burglars by Bowers & Johnson (2004), suggesting that they maximise their
revenue by establishing neighbourhoods and dwellings that require little effort to enter, contain high value items and where
the perceived chance of apprehension is low. On that basis a technique was developed in conjunction with Greater
Manchester Police (‘GMP’) and the UCL Jill Dando Institute of Security and Crime Science (‘UCL JDi’), to establish the
likelihood of repeat crime within a given target area, and implement preventative measures accordingly.
Taking into account the work of repeat victimisation (RV) and near repeat victimisation (NRV), the core values of
preventing these as a strategy of crime control are as follows (Pease, Repeat Victimisation: Taking Stock, 1998):
1. Focussing on repeats automatically concentrates efforts on areas of highest crime without the need for
supplementary deployment decisions
2. Focussing on repeats automatically concentrates on individuals at greatest risk of future victimisation
3. The time course of repeats suggests that resources can be focussed temporally as well as spatially
4. It fuses the roles of victim support and crime prevention which have been historically separated
5. Insofar as repeated offences against the same target are the work of the same perpetrator(s), clearance of a series
of crimes and linked property recovery are made more likely than was the case when events were independent
6. Provisional evidence indicates that repeated crimes are the result of prolific offenders, therefore prevention and
detection of repeated attempts is an uncontentious way of targeting prolific offenders
Repeat victims are targets that are victimised multiple times, near-repeat victims are targets that are situated in close
proximity to an original target, and that get victimised soon after the original target (Chainey, 2012). To understand repeat
victimisation in more detail I will use the explanation provided by Farrell and Pease (1993) referring to prevalence26 (counts
victims), incidence27 (counts crime) and concentration28 (counts crimes per victim). The common mistake as frequently
demonstrated by the media is the focus on incidence alone, the police forces have a far wider duty of care than to just
reduce the overall crime figure; repeat victimisation in that respect needs to be understood in detail using traditional
academic theories and computer methods such as that developed by GMP and UCL JDi29.
It is crucial to understand the links between these theories; RV and NRV by definition are a demonstration of optimal
foraging and further solidify the theories based around the cognitive processes of offenders.
Ross and Pease (2007) proposed the following;
“In domestic burglary, for example, the danger of a further crime is greatest at the home of the original victim and spreads
out to some 400 metres, but disappears over six weeks to two months … instead of mapping past events in the
conventional way we should map the risk they generate for nearby homes, with the map being dynamic to reflect how the
risk declines over time.”
23 Temporal constraints are defined as the time it takes to find and process reward
24 Energetic constraints are defined in terms of the metabolic cost of each foraging activity
25 Cognitive constraints are questioned in terms of how much learning and evolution can an animal undergo
26 Prevalence is the percentage of the population at risk who are victims at a given time period
27 Incidence refers to the average number of victimisations per head of the population at risk of victimisation
28 Concentration is the average number of victimisations per victim
29 http://www.ucl.ac.uk/jdi/events/int-CIA-conf/Abstracts/ICIAC11_Stream5

15. 13
Using this theory the trial by GMP achieved a 26.6%30 decrease in burglaries across the
period under review; but how much of this was down to the predictive method alone?
Further analysis shows ‘target hardening’ and ‘cocooning’ were also implemented, with 250
addresses hardened and 416 properties contacted face-to-face.
The study carried out by Newton et al (2008), researched the benefit of target hardening on properties that were either
repeat victims or first time victims. The results of their study show that there is an imperfect alignment of target hardening
resources to burglary risk: the challenges of implementing this intervention in the private sector; the prioritisation of certain
localities as a condition of funding; and the broader non crime-specific objectives of target hardening.
No one would disagree that target hardening is a costly and time consuming exercise. Doing it
effectively would outweigh this cost given the estimate of £3,925 per household for a dwelling
burglary by the Home Office31. But using the results of the study by Newton et al, there was a
distinct lack of directing target hardening towards those that were repeat victims. They provide a
number of reasons for this: the range of priorities beyond burglary reduction, funding for such
activity has distinct geographical locations and a wider remit than burglary; and there was no clear
and systematic approach for allocating target hardening based on a number of key risk factors
such including the vulnerability of occupants.
The GMP trial was focussed on a specific area so we should assume the issues raised by Newton et al are not applicable,
but they are something that should be considered when looking at target hardening activity in relation to preventing crime
across a wider area. That said looking at Table 2 (crime statistics for Greater Manchester Police) it is possible to see that
overall burglaries have been at a constant level since Dec 2010. There are a number of views that could be taken on this:
1. That the trial in Trafford and the results produced were not representative of the continued trend of burglaries
2. That the use of any ‘predictive policing’ was done well and the areas of highest risk were focussed on to achieve
maximum return on investment
3. Crime from Trafford was merely displaced to other areas, therefore overall burglaries never decreased on a long
term basis thus suggesting;
4. The same approach should be rolled out across all of Manchester to provide a consistent level of service to the
community
As briefly touched on in my introduction I believe criminals can and are altering the environment in response to any action
taken in respect of predictive policing, leading to a cat and mouse situation. Much of the original research into optimal
foraging by Sinverno (1997-2006) points towards a constrained ability to adapt and that foraging is determined by genes,
environment or culture, if this was the case evolution wouldn’t exist. Studies of displacement may suggest that the
‘constraint’ argument is not clear cut and in fact offenders are more apt than initially thought.
An interesting development of the optimal forager and RV theories applied to crime mapping capabilities is that as carried
out by the MET. The MET has developed an in-house-product (IHP) that uses these two theories but applies a temporal
weighting on the events that occurred most recently, meaning more recent crimes had a greater impact on the algorithms
that are applied to the data.
To summarise I can’t help but feel that target hardening and cocooning had a major part to play in the success, and the
effective operational implementation and community engagement by GMP meant that the trail in Trafford was a success,
the information around these traditional methods used alongside the MET’s use of an intelligence led solution was not
available for this report. I feel there needs to be more understanding of the displacement and diffusion of crime in relation
to these techniques.
30 http://www.ucl.ac.uk/jdi/events/int-CIA-conf/ICIAC11_Slides/ICIAC11_5A_VJones
31 https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/118042/IOM-phase2-costs-multipliers.pdf

16. 14
‘Recency, Frequency and Gravity (RFG)’
RFG was originally developed by Strathclyde police; a data mining technique that assesses offenders and victims on three
criteria. The basic premise is that throughout large quantities of data the most important or impactive entries are noticed
and correlated. Detective Chief Inspector John Patterson (2012-13), stated that if you are an offender who is currently
active in crime, prolific and engage in more serious types of crime then you are likely to appear on an RFG listing.
The RFG approach has taken a line of focus towards domestic violence and vulnerability, opposed to the two previous
approaches of acquisitive crime, ASB and criminal damage; it is based on the scientific data development of the known
facts of police from many years of dealing with vulnerable individuals and offenders.
Strathclyde police have reduced rates of reoffenders to 35-37% from 62-65%, during
a targeted approach of 450 individuals using the RFG data method32. Other forces
such as Essex33 and Northumbria34 are using this model, the specific results with
regards to reductions in domestic violence and violent crime have not been available
for this report. One evolution of the original model proposed by Strathclyde is the
introduction of ‘L’ (location) by Essex after a report by Allan Brimicombe 35
identified this as a key factor in repeat domestic violence in Essex: it was perceived
important “in terms of ambient deprivation, life chances, life style, stress and accepted norms of behaviour.”
In Strathclyde, since 2010, RFG has been applied to the full spectrum of the violence, disorder and antisocial behaviour
portfolio, including domestic abuse, problematic licensed premises, knife crime, robbery, gang violence, street drinking,
noisy party dwellings, youth disorder and vulnerable complainers. RFG listings are not exhaustive and only represent what
has been reported and formally recorded onto force systems, therefore representing a problem with the methodology that
can only be overcome with the confidence of victims to report crime.
“RFG offers the ability to measure complex problems through an easy-to-follow scoring system” (Paterson, 2012-13).
From the evidence and information gathered on RFG the main advantage is the ability to apply this model to all entities
whether these are offenders, victims, complainers, premises or neighbourhoods. Given the majority of crimes should have
all of this information recorded then it is simply a case of selecting the relevant entity as the primary reporting dataset.
Within Essex, Operation Shield is a dedicated team responsible for identifying and tackling repeat and high risk
perpetrators. This initiative has been in place since May 2014, using the RFG data mining technique to identify the most
“impactive, important or problematic” entities within its data sets (‘PROtect’). The process allows Shield to produce a risk
assessed cohort aimed at both victims and perpetrators; thereafter publishing them across the force.
An example of where this technique could have made a difference if that of Hollie Gazzard that led to the criticism of
Gloucestershire Police, rightly or wrongly, over the lack of suitable intervention. The IPCC investigation (2014) found a
number of failings but succinctly put there were inadequate policies and guidelines. In the IPCC report (p.43), it refers to
a ‘handover spreadsheet’ VOLT (Victim Offender Location Time) used by Gloucestershire Police, this shows
Gloucestershire tracked relevant incidents using a proven method of victim and offender tracking but the failing was
around an automated data analytical tool that removed any room for human error, time lapses and inconsistency in
reporting.
This example is not to highlight failings of any one police force but to demonstrate where the RFG approach may prove
successful and propose it as a proven solution for the protection of vulnerable individuals.
32 http://www.heraldscotland.com/news/13057017.Police_target_abusers_with_new_system/
33 https://www.ucl.ac.uk/jdi/events/int-CIA-conf/icia-15/ICIAC15_6A_PWraight.pdf
34 http://www.northumbria.police.uk/news_and_events/news/details.asp?id=106181
35 “Analysis of Domestic Violence Data in Essex”

17. 15
The automated process at Essex gets run once a week initially identifying 120 perpetrators, however with intervention this
has now decreased to approximately 85. Using the Hollie Gazzard case as an example; 3 days before the perpetrator
threatened an acid attack, this would have been visible and displayed on the output of the RFG analysis.
The RFG approach allows the Shield team to focus on providing on-going support to victims and engage in the proactive
intervention of high impact domestic abuse perpetrators, not forgetting the added benefit of being able to readily identify
repeat victimisation from a victim and perpetrator perspective. Shield take responsibility for the higher risk offenders and
develop comprehensive intelligence packages, risk assessments and action plans, paired with a bespoke toolkit aimed at
the relevant perpetrator or crime type.
The success of RFG approach at Essex is measured by the reduction of a harm score; the score is based around the
number of offenders within the RFG cohort and the reduction of these offenders week by week. The RFG model ranks
recency, frequency and gravity from 0-100, in the specific example of Essex as follows:
RECENCY FREQUENCY SEVERITY (GRAVITY)
Average recency of
incidents (days)
Score
Incidents in
past 365 days
Score Severity Score
Gravity
grading
Gravity
Score
0-14 100 10+ 200 9 to 12 High 100
15-30 75 9 150 5 to 8 Medium 75
31-60 50 8 150 1 to 4 Standard 50
61-90 30 7 150
91-120 20 6 150
121-150 10 5 150
151-180 5 4 100
3 75
2 50
1 1
Using the example slides in Appendices 2-4 we can see that with successful intervention and a tactical plan any offender
is capable of moving down the list based on a reduction in either of the RFG criteria.
The future of this approach is to develop a framework for Child Sexual Exploitation and Domestic
Homocide; which should incorporate information from other agencies such as education,
pharmacies, local GP’s etc. Earlier in this section the ‘L’ bought into the equation by Essex was
mentioned and although it does not feature specifically when calculating perpetrators it features highly
in respect of repeat victimisation, focussing on the situational context of victims.
RFG may not provide a visible drop in crime figures. Increases in crime figures can be related to the changes in reporting
requirements and victim confidence is portraying these crime types as an increase year on year. RFG has its own identifiable
set of success criteria, based in the data between June 2014-2015, Essex have seen a reduction in harm score of 27%36.
To summarise the IPCC report stated “it is impossible to determine whether a different response by officers would have
prevented Hollie’s death”37, while that is coldly factual in the context of the ‘Butterfly Effect’. The RFG approach may
not have prevented this tragic incident but it does provides officers with a vital intelligence led tool in the prevention of
repeat domestic violence victims.
36 http://www.essex.pcc.police.uk/wp-content/uploads/2015/08/Essex-Police-Performance-Update-to-Sept-20151.pdf
37
https://www.ipcc.gov.uk/sites/default/files/Documents/investigation_commissioner_reports/Hollie_Gazzard_Independent_Invest
igation_Report_.pdf

18. 16
Sensor Network – Dutch National Police
The Dutch National Police (KLDP) may have been nominated, and won, the Big Brother Award 2015 but for very good
reasons which are entirely relevant and pertinent for an intelligent led policing strategy that encompasses big data in a
machine learning approach.
The ambition of the Dutch national police is to create a nation-wide sensor network that collects and analyses data from
the physical and digital environments. This sensor network may include intelligent lamp posts that have cameras and sound
sensors, local networks such as though used by the military or private security companies, internet monitoring, online
market place purchasing, and situational awareness from events. The idea behind such a sensor network is that it will
increase the perceptive capabilities of the police.
To that extent the police have stated that they will be committed to four types of observations38
1) The recognition of identity
2) Identification of relationships
3) Recognising behaviours
4) The interception of communications
The aim of this project is:
1) To offer real-time automatic analysis of potential situations and detection of important events and;
2) Give support in these situations to first responders to guarantee the safety of the general public as well as the
responding authorities.
In order for this ambition to be realised there are a number of areas listed by KLDP that would need further research; a
solution to cheap intelligent cameras, facial recognition, anomaly detection in sound sensing, ad-hoc networking between
smartphones, optimisation of Optimised Link State Routing (OLSR) protocol, optimisation of routing, protocols for delay
torrent networking. There are technical and scientific difficulties that accompany this overwhelming amount of sensor
data:
1) Semantics: How to understand the relationships between signifiers
2) Noise: How to eliminate a correlation by chance from that of a meaningful sign to action
3) Speed: How to analyse data in real-time to ensure any police response is relevant
4) Scalability: How to create a system where new and existing technologies can be integrated and work together
5) Dissemination: How to use the network itself to distribute information and also how to distribute information
from the network to those needed to use it
6) Sustainability: How will the system face up to economic, cultural, political and technological issues to provide
continuity of use
Putting aside all of the technical, legal and scientific issues regarding such an product, the most enlightening comment is
one made by KLDP (2011);
“The obvious position of the police is not the role of developer, but that of the end user and adopter, building blocks of
other’s combined information”.
This comment could be unique in nature by implying that police should take a different view on their use of intelligence
led strategies and work with commercial companies in providing products and solutions with them as the user rather than
the lead in any development.
Finally, there are two other studies that specifically refer to the KLDP approach (Schakel, Rienks, & Ruissen, 2013) and
(van der Veer, Roos MSc, & van der Zanden MSc, 2009).
38 https://freedominc.nl/files/20110600-klpd-visie-op-sensing-binnen-de-politie_redacted.pdf

19. 17
The future of policing
How will policing change and when?
A report by the College of Policing has stated there is limited national data available to provide robust estimates of
emerging crime problems, however, there is reported to be some indication that there are new contexts in which crimes
are committed albeit in low numbers compared to ‘conventional crime’39, as these are associated with vulnerability, public
protection and safeguarding they are presumed to have a higher cost of crime.
In another publication by the Government, last updated 8 May 2015, it states that ‘police will be given far greater freedom
to do their jobs, and the public more power to hold them to account’40. The latter contributes to the uncertainty of future
demand in that, local power to influence policing demand could be driven by the visibility rather than severity of certain
crimes, whether this is through outlets such as the media or within victim’s neighbourhoods. But it does mean that police
may have to respond if they are being held to account, potentially having difficult decisions to make between prevalence
and severity.
It could be argued that an effective predictive, preventative policing or intelligence led strategy driven by factors that affect
demand on local forces is the future of policing; thereby proactively preventing a detrimental impact on societal or
operational objectives.
Within the UK there is believed to be 6 drivers of crime; Alcohol, Drugs, Character, Opportunity, the Effectiveness of
the CJS and Profit, some of these have good evidence linking them to crime, others not so much41. These 6 factors have
been around for some time and perhaps there needs to be a differing approach to the way we look at these and whether
they are still appropriate for the future of crime. Without a doubt the majority of the population are compliant but
Opportunity and Character could arguable be the underlying drivers that underlie the other drivers meaning that in fact
policing may always continue to alter in line with social trends and technological factors that create and present
opportunities e.g. Self-Service checkouts.
It is not possible to discuss every eventuality or predict the direction in which crime may evolve in the future but the
remainder of this report will focus on using technology and data to create solutions to a select number of crimes.
39 ‘conventional crime’ is not defined explicitly in the report by The College of Policing
40 https://www.gov.uk/government/publications/2010-to-2015-government-policy-crime-prevention/2010-to-2015-government-
policy-crime-prevention
41 https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/398865/Opportunity_security_final_v2.pdf

20. 18
Child Sexual Exploitation
Child Exploitation and Online Protection Centre (CEOP)
The Child Exploitation and Online Protection Centre (CEOP) report42 there are 4 key threats with some significant areas
of focus within each one.
1. The proliferation of indecent images of children (IIOC)
2. Online child sexual exploitation (OCSE)
3. Transnational child sexual abuse (TCSA)
4. Contact child sexual abuse (CCSA)
These threats will have varying effects on future policing demand, however, the line between responsibilities of Regional
Organised Crime Units (ROCUs) and local police may not be clear. With the prevalence of these crimes increasing and
being recorded on a local basis is this an area that needs to be assessed with some urgency in relation to an intelligence or
technology led solution?
The visibility and transparency of CSE as an overall has increased following Operation Yewtree43, and the number of
historic victims now coming forward has contributed towards the increase in crime figures along with a change in reporting
criteria. Taking the area of OCSE & IIOC and the specific category within these of ‘Self-Generated Indecent Imagery’
(SGII), the remainder of this section will conceptualise how the use of technology and defined responsibilities could
eliminate future police demand.
The prevalence of SGII’s increased when such issues as ‘revenge porn’ and ‘sexting’ became a cultural norm. In a letter
sent to school officials across Nottinghamshire, Det Insp Martin Hillier gave his grave concerns that the number of daily
referrals in relation to naked images being sent between teenagers via social networking, text or mobile applications44.
During September 2015 is was publicised that a 14 year old boy had distributed an indecent image of himself to a girl at
school and in turn could have his name stored on the Police National Database (PND) for a period of 10 years and may
be flagged on a DBS check45; a simple innocent mistake that could result in a genuine problem for life.
The laws relating to indecent images of children and the internet are dealt with directly in 1) The Protection of Children
Act 1978, 2) The Criminal Justice Act 1988 and 3) The Sexual Offences Act 2003 (that changed the definition of a child
from 16 to 18 effective from 1 May 2004). The unique element to SGII is that it crosses all subsets and classes of society,
all social-demographic factors are covered, it in theory only excludes those that do not have readily available access to
either a smartphone or PC. Traditionally in could be assumed that there is a certain percentage of the population that is
compliant and upstanding, the issue of SGII does not necessarily apply in this instance the pressures on children have
changed since the laws were written in 1978, 1988 and 2003 respectively (albeit they do get updated); the production and
distribution of images by children across society is evidently becoming more apparent, and will continue to do so.
The model below (figure 1) can be used to visualise the possible flow of demand on local policing. The responsibility of
the intervention proposed below is the contentious point; unfortunately there are decisions that need to be made around
who, where and when police forces use their resources to help. In simple terms if a crime has not yet been committed
then the prevention of SGII is not a priority with the volume of already committed CSE crimes and ‘violence against the
person’ crimes.
42 (CEOP, 2013) Threat Assessment of Child Sexual Exploitation and Abuse
43 Operation Yewtree is the investigation into sexual abuse mainly against Jimmy Saville but also others, led by the MET
44 http://www.theguardian.com/media/2014/jul/22/teenagers-share-sexts-face-prosecution-police
45 http://www.bbc.co.uk/news/uk-34136388

21. 19
Figure 1.
The proposed preventative measure illustrated above is as follows:
‘a concerned parent would have the availability of a drop-in centre whereby they can have the contents of their child’s
phone examined, by a specialist under controlled conditions, to check for indecent images. Should any images be found,
a Family Liaison Officer (FLO) or charity could act as an advice service to educate the family on the dangers and laws
regarding indecent images’
Obviously there are a number of issues with this proposed preventative measure and a number of assumptions I have
made in simplifying it to a level where it would be possible to provide such a preventative measure:
1. Any laws regarding personal data, data privacy or otherwise are dealt with
2. It makes the assumption that ‘responsibility’ for the prevention of SGII is agreed between the police, local
charities and from a national level, meaning the service is uniform and coordinated across the UK
3. The technology is already in place for 1) the forensic extraction of mobile data46, 2) the fast, accurate analysis of
a large number of images and 3) proving which device has taken any image in question.
The scale and size of CSE is far larger than this one very niche example selected and the laws and legislation may mean a
solution like this is not possible, but imagine the culture towards SGII altered and it became social unacceptable to send
them? This could mean that only images generated by organised crime and prolific offenders were in distribution, thereby
allowing the NCA and CEOP to focus efforts on the wider, more prolific, organised offences.
46http://digitalforensicsmagazine.com/blogs/wp-content/uploads/2010/07/Cell-Phone-Evidence-Extraction-Process-Development-
1.8.pdf Since the date of this report there will be other technology available but the pre-eminent providers still remain in the market

22. 20
Serious and Organised Crime
Serious and Organised Crime (SOC) costs the UK at least £24bn each year47, it includes crimes such as drugs trafficking,
human trafficking, organised illegal immigration, organised acquisitive crimes and cybercrime.
While these may currently fall under the remit of the Security Agencies, National Crime Agency (NCA) and the Regional
Organised Crime Units (ROCUs), there needs to be consideration to the effect the undetected or unresolved organised
crime has on the local communities.
Most, but not all, serious or organised crime is aimed at making money. This money is often reinvested into other illegal
activities to generate further funds or fund lavish lifestyles. Serious and organised crime is unique in that it often involves
a number of professionals; why these professionals are motivated or recruited into commit organised crime is not so well
known. But these professionals will have a detrimental impact on local society.
As at 31 December 2013 it was estimated that some 36,000 organised criminals made up 5,300 groups currently operating
in ways that directly affect the UK48.
In the National Strategic Assessment of Serious and Organised Crime (2015) the key threats are highlighted as CSE,
firearms, organised immigration crime, human trafficking & modern slavery, cybercrime, money laundering, drugs and
economic crime. While there have been no specific academic studies to assess the demand on local policing it undoubtedly
has an effect; to that extent the demand on the NSA and NCA are, in theory, a good indication of how demand in local
policing may be affected.
It may not be the responsibility of police forces to consider the intervention of SOC but Shane Roberts, DCI SOCU,
Bedfordshire Police quoted…
“Organised crime is commonly viewed within partner agencies as being in the stratosphere of offending; the preserve of
the Police and tackled by highly specialist police teams. The community safety partnerships in Bedfordshire realise that
the impact of serious and organised crime is felt both directly and indirectly locally. Now, previously considered low level
nuisance activity is tested for links to other more serious or organised criminality. For example, cycling on pavements has
been attributed to drug dealing networks and street prostitution influenced by organised immigration crime. Information
sharing and the production of serious and organised crime local profiles have helped improve this understanding.”49
…demonstrating that perpetrators and victims of organised crime always fall within the remit of local policing. It is the
use of data analytical techniques that will enable police forces to strategically analyse the links between local crime and
organised crime that will lead to focussed, efficient and targeted preventative policing measures.
47 http://www.nationalcrimeagency.gov.uk/publications/560-national-strategic-assessment-of-serious-and-organised-crime-2015/file
48
https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/248645/Serious_and_Organised_Crime_Strategy.
pdf
49 http://www.local.gov.uk/documents/10180/6869714/L15-376+Tackling+Serious+%26+Organised+crime_04.pdf/0005d382-
139d-4695-b828-1ea987c2d957

23. 21
Cyber crime
The National Cyber Crime Unit (NCCU) leads the UK’s response to cybercrime, supports partners with specialist
capabilities and coordinates response to the most serious of cybercrime threats. It works closely with the ROCUs, the
Metropolitan Police Cyber Crime Unit (MPCCU), industry partners, Government and International Law Enforcement,
the NCCU has the capability to respond rapidly to changing threats50.
At the highest level, foreign industrial espionage could have a significant effect on the UK economy but for the purposes
of this report and identifying the local policing demand it is pertinent to focus on the lower levels of cybercrime. These
would mainly consist of individuals or small groups of opportunistic criminals51 that will tend to target UK citizens and
vulnerable organisations.
It is a fact that whether a government organisation, multi-national business or individual is targeted the data or money
stolen will inevitably effect a member of the public and therefore, by default, will fall within the geography of a local police
force. Using the lower level cybercrime as an example it has recently become visible, via the media, there have been a
number of individuals have become victims through Social Engineering, which includes Phishing and False bank calls.
It is estimated that the cost to UK citizens alone, not the UK economy, is £3.1bn per annum52. In previous topics discussed
in this paper there are many techniques used in traditional acquisitive crime to prevent and help victims; target-hardening,
cocooning etc but how many techniques are there available to local police to provide this type of personal preventative
policing to cybercrime victims?
The majority of press stories, give the impression that the victim has been left alone to deal with the bank to prove
themselves innocent and therefore be compensated. It seems counter intuitive that in traditional crimes you are innocent
until proven guilty yet in the case of cybercrime only 62% of victims were reimbursed in full53, implying 38% were
somehow complicit in their victimisation. If cybercrime and Social Engineering are the ‘future’ acquisitive crime then, with
the increased power of the public to hold forces to account, there could be an overwhelming demand to provide post
victim support. I have no doubt that the vulnerable or those who lose significant amounts of money54 receive support
from local police in making sure they have suitable safeguards to prevent repeat victimisation.
What happens to the individuals who may only lose a few thousand pounds from skimming or a bank hack? Are these
individuals left to deal with the bank without full knowledge of the law or guidelines? Will their shock or distress at the
time cause them to inadvertently incriminate themselves? Unfortunately I don’t have the answer to these questions; I also
don’t have the answer to how much this had an effect on the local economy in which a victim resides. Does it lead them
to think about committing a lower level crime in order to repatriate themselves; something such as a bicycle theft to earn
a few hundred pounds?
The focus of the above is mainly on ‘cybercrime with a purpose’; a desired outcome for the gain of profit. But there is also
a level of cybercrime that is committed without the intention of a financial gain. Using the example of Mustafa Al-Bassam
(Tflow), ex-LulzSec member, he was 10 when he first started to creatively explore and realise how many mistakes
programmers had made, leading to security loopholes. As stated by Charlie McCurdie “Their crime was an unusual
campaign in that it was more about promoting their own criminal behaviour than a form of personal financial profit”.
50 http://www.nationalcrimeagency.gov.uk/about-us/what-we-do/national-cyber-crime-unit
51 For example, see ‘Hackers Invade iTunes: Cybercriminals are opportunistic’, Peter Chubb, August 2010.
52 https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/60943/the-cost-of-cyber-crime-full-report.pdf
53 http://www.ons.gov.uk/ons/rel/crime-stats/crime-statistics/year-ending-june-2015/index.html
54 ‘significant’ is relative depending on the wealth and perception of the individual victim

24. 22
They wanted to show people they were the best at what they did, no different to our investment bankers competing with
each other. The difference being there was no legal outlet for these highly talented individuals until recently. Jennifer
Arcuri, ethical hacking guru said, government and corporates should work together to ensure these skills are put to good.
On a grassroots level cybercrime initiatives such as the National Cipher Challenge and the Cyber Security Challenge UK
are aimed at finding talented individuals that can be recruited and trained for use in cyber security.
Using these initiatives, it is important to remember that there could be accompanied by a list of social indicators that may
help parents or local education identify these talented individuals. These factors could help differentiate these children
from others in a positive way, there shouldn’t need to be reliance per se on the NCA or ROCUs to monitor the purchase
of a ‘cheap’ tool such as the Blackshades Remote Access Tool. Albeit this was seen as a strong precursor to the potential
to commit crime, it is a very limited view in considering ‘qualifiers’ for a future cyber-criminal.
The Economist (2015) has suggested hacking is about to get ‘3D’, while this sounds slightly grandiose, the implication is
that criminals will start to take control of physical items such as cars, smart-devices and hard drives in exchange for ransom;
thus the tactics spoke of earlier in this section may be quickly surpassed in favour of a more guaranteed revenue stream.
Ultimately these criminal gangs are well versed organisations with capabilities and intellect aimed at generating revenues.
Will the ‘virtual’ seizing of physical attributes create a demand for local policing when victims have nowhere else to turn?
Only time will tell.
A report published by PA Consulting (2015) has the findings of how differing generations believe cybercrime will affect
them. There is an interesting dynamic in the findings of this report in that the younger generations feel least concerned
about cybercrime, yet they are the most vulnerable and are more likely to be victims due the breadth and depth of usage;
43% of this younger generation want more emphasis placed on cybercrime than real world crime.
On page 18 of PA Consulting’s report it states the percentages of the public that feel the police have better capabilities
than cyber criminals is 59%, however there is no clear definition on whether ‘police’ includes the secret service and NCA.
This is imperative to understand as the level of capabilities between the NCA and a local force could be very different.
This is pertinent in relation to page 15 of the report whereby it is thought, by the public, that local police should deal with
abusive/threatening language and child abuse images.
To summarise this section, cybercrime has and will continue to move very quickly. The under reporting of cybercrime is
a key issue (page 12/13 of PA Consulting’s report) with only 30% reporting cybercrime, a shift in willingness to report
and a change in reporting requirements could have a considerable impact on local demand. A report by PA Consulting
(2014) details the types of cybercrime and highlighted at the time that only 5% of police analysts claim to have considerable
knowledge in relation to it; somewhat contradictory to how the public feel the police are equipped in the 2015 report.
There may be no easy preventative measure in relation to cybercrime, but the use of data and technology is going to be
ever more important in the future.

25. 23
Natural Language Processing
Natural Language Processing (NLP) is a field of computer science, artificial intelligence and computer linguistics concerned
with the interactions between computers and human linguistics. The history of NLP started in the1950’s with Alan Turing,
commonly known as the’ Turing Test’ by which computers are assessed on whether they can fool a human into thinking
they are talking to another human.
NLP has moved on a lot since the 1950’s. With the development of Artificial Intelligence (AI)/Cognitive Computing and
the increase in computing power available, the analysis of text, historic or real-time has become a possibility to mainstream
policing.
A study in 2012 (Chon, Preotiuc-Pietro, Samangooei, Gibbins, & Niranjan) looking at the analysis of real-time social media
text demonstrated the awareness and the requirement to assess the threat as well as the potential for the accurate analysis
of this data.
NLP has a number of real world applications in relation to crime prevention including the analysis of social media for use
in organised demonstrations or public protests (e.g. London Riots) but also in hate crime, online trolling, cyber-harassment
or industrial espionage. In order for NLP to be effective and used in a way to prevent crime it is essential to understand
the building blocks of social media, how they impact on one another and the implications of each block. Kietzmann,
Hermkens, McCarthy & Silvestre (2011) have theorised the building blocks as follows and in their report they go further
in analysing the most important blocks across varying social media platforms.
NLP has a series of steps that must be taken in order for a language to be artificially analysed and provide a user with an
output relevant and meaningful for the purpose that it is intended. The steps in NLP; morphological segmentation, parsing,
discourse analysis, named entity recognition, natural language understanding, relationship extraction, topic segmentation
and word sense disambiguation, are not going to be explained in detail in this report. There are many scholarly articles and
books that can do this such as (Chowdhury, 2005), (Manning & Schutze, 1999).

26. 24
From the perspective of understanding how these impact the linguistics of a language, accompanied with the building
blocks one can begin to think about the obstacles this approach may have to analysing real-time social media. The prolific
use of slang, the abbreviation of words into a small number of letters and numbers and the obvious grammatical errors
across the English language mean that AI/Cognitive Computing is the only way to make this feasible.
There are a number of options available for complex linguistic analysis; some are open source and others are available
commercially. The majority of these are focussed on the spoken language and appear on our smartphone devices, more
commonly known as Siri, Cortana or Ask Google. However Chowdhury (2005, p. 69), cites a number of software packages
available for the purpose under review in this section, given the year of publication IBM Watson and General Architecture
for Text Engineering (GATE) were not mentioned.
NLP still needs to progress in certain areas such as short text analysis (twitter) and the simple summarisation of input text
from large documents but there is no doubt that as part of an overall intelligence led solution it can play a part for real-
time data analysis.

27. 25
Evolution of existing methods
Crime mapping with CCTV
Earlier in this report the use of crime mapping was analysed in relation to data analysis and the visualisation of ‘hot-spots’
in order to facilitate the effective policing of a given area.
CCTV is invaluable in solving crime, with 95% of murder cases investigated by Scotland Yard using CCTV footage55, but
how much is CCTV used in preventing crime is undetermined. Dyfed-Powys Police commissioned a review in 2014 into
the provision of CCTV within the area56. The key findings of this review were focussed on the provision of a long term
solution in relation to CCTV given impending budget cuts.
A report by The College of Policing (2013), concluded that CCTV has a modest but desirable effect on crime, is most
effective when used in relation to vehicle crime and that CCTV schemes have been found to be most effective when
combined with other interventions such as improved lighting or increased security guards. The successful use of CCTV
depends on clearly identifying the crime problem of a location and developing a rationale for the installation of CCTV;
overlaying a crime map can provide this rationale. The contribution of CCTV in ensuring criminals are caught and
convicted was not specifically assessed in the report and the impact on violent crime was considered to be lower than that
of vehicle crime.
CCTV is there to view what is happening, but upon further thought there are a number of factors that affect the benefit
to local police. Are images being recorded? Are CCTV cameras permanently monitored? Are the cameras operational? Is
the view of the CCTV camera fixed? What is the purpose of the camera?
A British Security Industry Association (BSIA) report (2013: Form No. 195) estimates there to be between 4M and 5.9M
CCTV cameras in the UK. Big Brother Watch established there were a total of 59,753 CCTV cameras controlled by 418
local authorities in Britain (figures for 2009)57. The question is then whether or not police or local authorities have access
to the remainder in relation to crime prevention. If the remainder are privately controlled what affect do these have in
serving as a capable guardian?
Budgets cuts are forcing police forces to either turn off CCTV or reduce monitoring; Cornwall reduced their CCTV budget
by £350,000, Denbigshire by £200,000, Birmingham’s 250 CCTV cameras will no longer be monitored around the clock
and Thames Valley Police could reduce its budget by 78% to £50,000 by 2018 58. Using a crime map overlaid with the
position of CCTV will provide information on which cameras to monitor and when.
A trial of facial recognition software by Leicestershire police has also opened up another efficient and technology driven
solution to policing and budget cuts. Leicestershire trialled NeoFace from April 201459, successfully used it at the
‘Download Festival’ in 2015 and received praise from an independent ethics committee on 5 December 201560. In a
Freedom of Information Act request Leicestershire Police have stated that the evidence gathered by the software cannot
be used in, but significantly speeds up, investigations and has identified the suspects in 45% of cases. Leicestershire have
also demonstrated this software to Lancashire, North Wales, Northants, the MET, Kent and Essex61.
Technology is constantly evolving and the use of real-time facial recognition to track persons of interest; creating heat
maps of routes and places visited could be a solution to using CCTV in a modern policing environment, driven by
technology.
55 http://www.telegraph.co.uk/news/uknews/law-and-order/4060443/Seven-of-ten-murders-solved-by-CCTV.html
56 http://www.dyfedpowys-pcc.org.uk/wp-content/uploads/2015/04/Instrom-CCTV-report-14-DPP-1413.Reduced.B.pdf
57 “Big Brother is Watching”, Big Brother Watch, London, 2010
58 http://www.bbc.co.uk/news/magazine-30793614
59 https://www.whatdotheyknow.com/request/240739/response/605917/attach/2/8302%2014.pdf
60 http://www.leics.pcc.police.uk/News-and-Events/Latest-News/2015/Ethics-watchdog-praises-force-innovative-facial-
recognition-database.aspx
61 https://www.whatdotheyknow.com/request/leicestershire_police_using_biom

28. 26
Offender/Victim profiling – Multi Agency Approach
Researchers in the US (Rosellini, et al., 2016) carried out a study in an attempt to develop an actuarial model using machine
learning methods to predict future violent crimes among US Army soldiers.
In the initial stages of this model development, very similar in the way current modelling techniques work, historic data
from 2004-2009 for all 975,057 soldiers was assessed, alongside crimes committed (5,771 committed their first major
physical offense during the period). Administrative records measuring socio-demographic data, army career, criminal
justice, medical/pharmacy, and contextual variables were used to build a model for these crimes separately among men
and women. The model was then validated in an independent 2011-2013 sample.
There are obvious moral, ethical and legal barriers to implementing such a model in the UK but considering the findings
in the US where 50.5% of all crimes were committed by 5% of soldiers in the 2011-2013 validation sample, it should be
considered whether or not data sources that may traditionally feed into Multi-Agency Safeguarding Hub’s (MASH) could
be used in such a way in the UK.
A report by the Home Office (2014) identified a
spectrum of multi-agency working within the 37
areas assessed.
Specifically in this report it was claimed MASH’s
have led to the following improvements:
1. More accurate assessment of risk and need
2. More thorough and driven management of
cases
3. Better understanding between professions
4. Greater efficiencies
The report by the Home Office analyses in more detail
the core features and barriers to an effective MASH setup, in particular the Data Protection implications combined with
the Children Act 1989.
The benefits of a MASH are obvious; the ideology proposed is that when accompanied with work similar to that carried
out by the US Army, a MASH can act as an invaluable source for collecting relevant data and by using the correct data
analytical methods could be used to act as a preventative measure in relation to those that are likely to become offenders
and victims.
It is important to remember that data products or technological advances are not designed to replace humans. Humans
are critical in the support of victim support and any intelligence led solutions need to be designed around this element,
enabling those providing support to have more time to do so.

29. 27
Displacement and diffusion of crime
Displacement is defined as the action of moving something from its place or position, or the transfer of an emotion from
its original focus to another object, person, or situation. There are six types of crime displacement; the relocation of crime
from one place to another, time, target, offence, tactic or offender; the most commonly recognised of these is spacial
displacement (Eck, 1993).
Diffusion is defined as the movement of something from an area of high concentration to a region of low concentration.
Clarke & Weisburd (1994) expressed diffusion as the effect on areas that are not directly policed, but are in close proximity
to those that are, and therefore policing has the effect of reducing crime outside of directly targeted areas.
Crime prevention and displacement theories date back to the 1970’s, with many studies having been carried out since then;
‘Crime Prevention and the Displacement Phenomenon’ (Reppetto, 1976), ‘Crime Placement, Displacement and Deflection’
(Barr & Pease, 1990), ‘Measuring the Geographical Displacement and Diffusion of Benefit Effects of Crime Prevention
Activity’ (Bowers & Johnson, 2003), Displacement: An Old Problem in New Perspective (Clarke R. V., 1994), Crime
Specialisation, Crime Displacement and Rational Choice Theory (Cornish & Clarke, 1989), to name but a few. Collectively
they have put the theory of displacement through its paces taking into account the modern policing environments.
Clarke & Weisburd (1994) suggested two methods of diffusion; deterrence and discouragement. While Bowers, Johnson
and Guerette (2014) concluded that successful crime reduction interventions often have a positive impact on crime that
extends beyond the direct recipients of a particular project. However, the current understanding of crime displacement
and how benefits might diffuse remain incomplete. The study by Bowers, Johnson & Guerette (2014) encompasses
approaches and theories talked about in this paper; target hardening, the restraints imposed on a perpetrator in accordance
with the ‘optimal forager’ theory and the routine activity theory, thus providing an overall view of displacement.
Displacement and diffusion of crime are not completely understood and there are still grey areas around how policing
initiatives affect displacement and therefore counteract the effects of geographically focussed policing efforts. Bowers et
al (2010) (2011) have carried out two extensive reviews in the fields of crime displacement and how policing initiatives
affect these.
In the introduction I mentioned two distinct groups of influences on criminal behaviour that would encourage them to
alter the environment in which they operate; direct and indirect. I propose that displacement and diffusion of crime need
to look more broadly in relation to the direct or indirect alteration of the environment; thus changing the thought process
behind 21st century crime solving and the root causes or motivators.
I am suggesting that Eck’s (1993), 6 types of crime displacement are most appropriate when looking at the actions of the
police; therefore direct environment alteration, and just as much consideration should be taken in looking at the indirect
altering of an environment; while arguably similar the slight differences are significant when looking at policing strategies
and interventions

30. 28
Below is a model to show the possible differences in displacement between a typical acquisitive theft and cybercrime.
Time – Capacity: The displacement of time no longer becomes an issue when looking at virtual crimes a crime can be
committed at any time of day and may not be displaced due to traditional intervention methods. The capacity restraint on
the number you can commit, or the cognitive capacity of the perpetrator is now more appropriate to assess.
Target – Reward: The changing of target may no longer be applicable, 21st century crimes may not be based on a target
but more so a reward. Those cybercrimes carried out for money will target a mass audience, with little consideration for
the constraints in theories such as optimal forager or routine activity theory.
In summary displacement and diffusion of crime are yet to be fully understood, I suspect many studies focussed on
traditional displacement ideas may be surpassed by the time they are completed, by the speed at which criminals evolve
and change the way they work using technology.

31. 29
Summary and conclusion
This report sought to bring together the existing methods, theories and knowledge regarding predictive policing or
intelligence led policing (ILP). In doing so the beginning of this report draws on the first hand evidence from interviews
carried out with various UK police forces along with academic theories and studies as referenced accordingly.
The second half of this reported aimed to analyse the changes in
crime over time and theorise the effect these may have on local
policing demand, with solutions where possible. The overall
intention of this ‘future’ section is to initiate the ideology of an
intelligence led policing culture, not replacing humans but to think
as data as a means of efficiency and support for the work carried
out by analysts and officers alike.
Data analysis tools and an internetwork of technologies does not necessarily result in a data-driven or data-appreciative
culture. IT systems within some forces are not yet capable of adopting this approach; software and hardware capabilities
have unfortunately not been the focal point of investment with the severity of budget cuts. The MET published an IT
strategy for 2014-2017 which is intended to put an end to spending 80% of the IT budget on maintenance62. This example
may not be representative of the other UK police forces but does demonstrate that when required, flexible, technology
led solutions can save significant costs and time. The MET have stated the equivalent of an additional 900 officers in time
will be saved51; but this saved time needs to be used effectively.
It is my opinion that police forces
cannot look at software, hardware or
technology solutions in isolation from
one another. The creation of ‘a product
for all areas of the organisation that
both use and produce data’, focussed
on the semantics and deeper
understanding of the complexities of
supply and demand in relation to
crime, rather than the focus on crime
types and the reported reduction in
crime figures. This fits with the
operational/societal needs matrix that
should drive any decisions made in
order to change policing for the future.
The move towards ‘software as a service’ (SaaS) seems to be getting closer; the ability to develop and respond to changing
trends in crime, technological usage and infrastructure requirements mean that traditional in-house solutions may no longer
be appropriate.
Figure 2 above visualises some of the methods and models discussed in this paper and where they may sit on a spectrum
of predictive, preventative or intelligence led techniques. All of these have produced good results in the areas in which
they are used but that is not to say they will continue to do so. The evolution of these methods needs to continue but the
evolution of policing infrastructure and culture will be the defining moment for real success.
62 http://content.met.police.uk/News/Total-Technology-strategy-201417/1400022464491/1257246741786
Figure 2

32. 30
Before providing my recommendation on the future I would like to address the difficulties experienced in obtaining
published results of trials and therein, ‘publication bias’. Publication bias refers to the information that is published, against
the information that is available in relation to any research carried out. My main issue was the difficulty in obtaining
relevant information in relation to the results of trials or commercial partnerships that have delivered results in policing
that could be shared across forces. From a verbal conversation with one force I know that predictive policing software
similar to that discussed in this paper was discontinued after an independent university study found it ineffective; obtaining
the paper in relation to this conclusion would have been useful for this report and also insightful for other forces thinking
about implementing a similar method.
In 2015/16 the police innovation fund awarded £50m to forces for new approaches to tackle anti-social behaviour and
rural crime; a project to help young runaways; and work to improve the way the police interact with people with mental
health problems63. Looking at the awards in more detail there are many awards for what would seem like similar themes
or solutions64.
I am not questioning the validity of these awards nor the effectiveness they have had in the communities but the lack of
resources available to compare and contrast the effectiveness of the approaches is potentially leading to a segregated and
environment whereby only positive results are published. Failure should not be something to be hidden, it is essential on
the course to success, and in my opinion it is equally as important to publish these as well as the positive results of studies,
trials or innovations.
In the executive summary I asked the question “What is the future?” I don’t feel the answer to this has to be complicated
but the implementation is infinitely more so. I see the future as follows:
 View police forces as a user of technology and not the developer or maintainer
 View intelligence, data, prevention and prediction as synonymous products not
segregated and distinct solutions
 Create strategic alliances with safeguarding partnerships to share data and
understand who can use what and how
 Create commercial partnerships with flexibility to utilise SaaS and IT to benefit from
a wide range of specialisms not held within the police
 Refer back to operational and societal objectives when considering change within the organisation
 Begin to view forces as a business from an operational perspective; albeit the businesses objectives will be
incomparable to that of any traditional business
 Maintain a level of professional scepticism towards research and publications; why and how things may differ
from one force to another and what results weren’t published
 Transparency and willingness to publish all results of innovation funding for 2016 onwards65, and all other
policing initiates that will benefit other forces from the positive results and lessons learnt
63 https://www.gov.uk/government/news/home-office-rewards-police-innovation-with-50-million
64
https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/417628/2015_03_25_Successful_bids_to_the_20
1516_PIF_PRESS.pdf
65 https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/470122/HARD_LAUNCH_20151020_-
_PIF_2016-17_on_a_Page.pdf

33. 31
Glossary
‘Target hardening’ is referring to the process of strengthening the security of a building or installation in order to protect
it in the event of attack or reduce the risk of theft. It is believed that a strong and visible defence will deter or delay an
attack.
‘Cocooning’ is the act of making homeowners in areas where burglaries have happened aware that a crime has taken place
to ensure they have taken all measures to be certain their homes and possessions are secure. It must be noted that
cocooning is a reactive strategy in response to crime, and should be carried out within a limited time frame after the event
to have an effective impact.
‘Guardianship’ is one of the three pillars of the routine activity theory (RAT) that focusses on situations of crimes. RAT
proposes that a crime won’t occur unless there is an absence of a capable guardian. The capable guardian is not necessarily
a police officer; it can be a member of the public, a homeowner, a postman or in fact anyone that may disturb an offender.
‘Machine learning’ is a subfield of computer science that evolved from the study of pattern recognition and computational
learning theory in artificial intelligence. Machine learning explores the study and construction of algorithms that can learn
from and make predictions on data. When employed in industrial contexts, machine learning methods may be referred to
as predictive analytics or predictive modelling. It is also used in nearly all Natural Language Processing66
‘Social Engineering’, in the context of information security, refers to psychological manipulation of people into performing
actions or divulging confidential information. A type of confidence trick for the purpose of information gathering, fraud,
or system access, it differs from a ‘traditional con’ in that it is often one of many steps in a more complex fraud scheme67.
66 https://en.wikipedia.org/wiki/Machine_learning
67 https://en.wikipedia.org/wiki/Social_engineering_(security)

34. 32
Acknowledgements
I would like to thank that all the individuals that gave up their time to talk to me and entertain my questions in the early
stages of research, the exemplary attitude and open approach shown by all of the police forces in responding to my initial
solicitation back in August 2015 made it an enjoyable experience. The acknowledgement and support by the Home Office
and the College of Policing gave me the confidence to pursue the level of detail required for a balanced case.
My sincere appreciation goes to those that took the time to review this report in its various stages and provided guidance
and recommendations to develop this report into what is has become.

35. 33
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