Analytics In Crime Prevention

Analytical tools have been used by law enforcement agencies across the world historically as a means to react to criminal activity. Modern analytical tools are now capable in preventing crime making the law enforcement agencies proactive rather than only reactive.

Transcript

1. ANALYTICS IN CRIME PREVENTION Ankita Sengupta Christ (Deemed to be University)
2. WHY ANALYTICS IN CRIME PREVENTION • Analysing and using data in some capacity is not a new development in law enforcement. Historically, they have been used as a means of reaction to crimes. • CompStat, refers to the reliance on statistics and automated mapping by the law enforcement agencies to determine high-risk crime areas using the geographical information systems (GIS) to deploy more officers. • However, with the help of modern analytic tools, law enforcements now have means to be proactive rather than being just reactive. • Crime prevention is not just means to prevent crime and victimization but also improves the quality of life of the citizens and leads to a sustainable development of the nation (ECOSOC, UN). • Data science is an influential tool to detect and prevent crimes. • Crime analyses has emerged to be the central point of modern policing.
3. HOW ANALYTICS CAN HELP IN CRIME PREVENTION ❑ CRIMINAL PROFILING Machine learning is used to build models for criminal behavior in significantly less time. This helps in identification of people exhibiting criminal intent and take action accordingly. Airports use criminal profiling as means to prevent criminal activity. ❑ SOCIAL MEDIA POLICING With billions of users manual social media policing is not possible. Modern analytic tools can scan through the plethora of data available online and help in the identification of criminal behavior. ❑ PREDICTIVE POLICING A method used by law enforcement agencies to identify possible criminal activity. PredPol is one of the most well – known predictive policing software developed that can predict where the crime is likely to occur with a 500 square feet precision. ❑ DISCOVERING CRIME PATTERNS Analytics is capable of identifying crime patterns for a wide range of crimes and can aid in identifying specific perpetrators.
4. CASE STUDY I: SHREVEPORT POLICE DEPARTMENT • An experiment, Predictive Intelligence – Led Operational Targeting (PILOT), was conducted to flag potential crime spikes given various types of calls for service, juvenile arrests and seasonal indicators. • Shreveport analysts overlaid a grid of 400 sq. ft. cells on the experimental area and used predictive methods to identify hot spots. • They developed daily maps showing not just the predictions but also key situational awareness data, including information on recent crimes, suspicious activity, field interviews, and where predictive policing units had just visited which was useful in planning where to focus their policing strategies in terms of when and where their activities should be focused. • Preliminary results suggested that major property crimes declined by more than 40 percent in the experimental hot spots though the overall results remained inconclusive owing to the inability to imply causation.
5. CASE STUDY II: MANCHESTER NH POLICE DEPARTMENT • The Manchester PD implemented Ironside’s Predictive Policing platform to improve crime prevention through better understanding the drivers of incident and improving forecasting of future incidents. • Ironside assisted to get an SPSS Modeler implementation that developed predictive models. • focused around the formal methodologies for data science, such as CRISP-DM, and the data preparation, modeling, evaluation, and deployment activities. • This enabled them to test hypotheses and design further crime reduction strategies. • Their models are yielding geographically relevant forecasts that give them the jump on crime and allow them to target precise areas of their jurisdiction. • The PD is already exploring new possibilities to further their crime prevention models.
6. EXAMPLES OF ANALYTICS IN CRIME PREVENTION ❑ INDIAN POLICE FORCE • Delhi police have partnered with ISRO to develop an analytical system called Crime Mapping, Analytics and Predictive System (CMAPS). • It helps the Delhi police to ensure internal security, controlling crime, and maintaining law and order through analysis of data and patterns. • Jharkhand police force is trying to implement an analytical system with the help of IIM Ranchi, to evaluate criminal records, date and time of crime occurrences, and location to predict crime-prone zones. • Bangalore police with the help of IBM is now training officers on the better usage of data analytics software.
7. ❑ CHINESE BIG DATA SURVEILLANCE AND CLOUDWALK • China is building an analytics software platform that will be able to cross-reference information from bank accounts, jobs, hobbies, consumption patterns, and footage from surveillance cameras to identify potential terrorists. • The Chinese facial recognition company, Cloud Walk Technology is trying to actually predict if an individual will commit a crime before it happens. The company plans to us facial recognition and gait analysis technology help the government use advanced AI to find and track individuals. ❑ DURHAM’S HARM ASSESSMENT RISK TOOL (HART) In Durham, UK, AI is being used to improve current system of deciding to release a suspect. The program, HART, was fed five years worth of criminal data. Hart uses that body of data to predict if an individual is a low, medium or high risk.
8. REFERENCES 1. Hayes, W. (2015). Case Studies of Predictive Analysis Applications in Law Enforcement. Thesis. Naval Postgraduate School, Monterey, California. https://calhoun.nps.edu/bitstream/handle/10945/47957/15Dec_Hayes_William.pdf?sequence=1&is Allowed=y 2. Sri, T. (2021). How Can Data Analytics Help us Prevent Crimes? Crime Prevention, Data Analytics; Selerity. https://seleritysas.com/blog/2021/05/18/how-can-data-analytics-help-us-prevent- crimes/#:~:text=Modern%20data%20analytics%20uses%20machine,behaviours%20leading%20up%20to %20crimes 3. Faggelia, D. (2019). AI for Crime Prevention and Detection – 5 Current Applications. Emerj Artificial Intelligence Research. https://emerj.com/ai-sector-overviews/ai-crime-prevention-5- current-applications/ 4. Ironside Group. (2015). Ironside Case Study: Manchester PD’s Predictive Policing Success. https://www.ironsidegroup.com/2015/10/06/ironside-case-study-manchester-pds-predictive- policing-success/ 5. Maydon, T. Using Big Data Analysis To Prevent Crimes The “Minority Report” Way. KDnuggests. https://www.kdnuggets.com/2016/04/using-big-data-analytics-prevent-crimes-minority-report- way.html
9. THANK YOU