WITH the increase in population in both urban and rural areas, crime in Pakistan has taken on a more varied and complex dimension. A paradigm shift in traditional policing methods is the only way to tackle the new and massive law-enforcement challenges. More and more police organisations across the world are adopting modern crime mapping and data analytics to predict, prevent and detect crime.

Maps are display tools and used extensively in research, analysis and presentation. A crime map is the end product of a process which starts with the first-responding officer’s report that is processed and entered into a database, and transformed into a symbol on a computer. It boosts visual thinking which, in turn, leads to the formulation of hypothetical questions and then to visual communication.

Crime mapping involves identification and analysis of patterns and trends in crime and disorder. Such information helps law-enforcement agencies deploy resources more effectively. The analysis of patterns and trends also contributes to devising solutions to crime and formulating crime prevention strategies. Quantitative social science data analysis methods are part of the crime analysis process.

Crime analysis has spawned the ‘80/20 rule’, a concept in which a large majority of incidents occur at a small minority of locations — for example, 80 per cent of incidents at 20pc of locations. Time and space are the basic pillars of this analysis which may vary according to the requirements of both police and community. The more usual categories of crime analysis are divided into demographic analysis, site analysis, use analysis, neighbourhood/user consultation, pathway analysis, season analysis, social activity analysis and socioeconomic class analysis.

Visual data helps formulate strategies to prevent crime.

The customary methods of collecting crime statistics already make use of some of these aspects. One manual technique for collecting crime data is the daily crime diary of a particular policing area. Other methods may include data being shared by the community, media, social media and other government departments. Day-to-day demographic analysis shows that certain areas in cities are more prone to ethnic or sectarian crime. Site analysis can help uncover the extent of vulnerability of an area to street crime. Pathway analysis leads to many crimes which were previously not reported to the police while the large number of house burglaries that take place when people are away to celebrate, say, Eid is an example of social activity analysis. In the rural parts, harvesting time is one when many people are robbed — an instance of season analysis for the police.

A variety of software has been developed for basic crime mapping by identifying crime hotspots. This software is used by police in Pakistan. Safe city projects are working to achieve a similar aim. However, when the population outstrips resources, smart solutions are required. Additionally, the use of software is largely focused on crime detection whereas the same can be deployed for effective prevention and timely prediction of crime.

The mere identification of hotspots thro­ugh GIS technology does not expose organised crime nor does it explain how the proceeds of crime are being recycled to breed more crime. A deeper analysis of the multiple layers of crime shows the intricacy of the problem. Visual crime data provides a cross-sectional perspective of various crimes.

A problem-oriented policing approach all­ows law-enforcement officers to follow the scanning, analysis, response and assessment process to identify, analyse and solve challenges. Once problem-oriented policing is combined with community policing, a sound model of crime mapping and analytics can eme­rge. Community engagement enables the police to not only map crime efficiently but also to prioritise the use of policing resources. Police-public partnerships lead to a better analysis of crime data and consequently better police picketing and patrolling.

Neighbourhood watch and crime watch committees at the police station level help the police in identifying hotspots and pooling resources. They also help in determining where past victims and offenders lived and which neighbourhoods attract offenders and where unknown offenders may reside.

Crime mapping and data analytics are unmistakably the future of predictive and preventive policing. In the US, data analytics and the predictive policing model have pinpointed three areas of success. First, they improved community relations, which increased the community’s willingness to interact with the police and led to better cooperation between the two. Second, the police discovered that the predictions were actionable and that this could prevent crime. Finally, the model improved actionable intelligence which, in turn, improved the skills of analysts for better pattern recognition and more relevant and timely data collection.

The writer is a police officer.

Twitter: @MariaTaimurPSP

Published in Dawn, February 7th, 2022