In today’s complex world, criminals are everywhere. There is a greater responsibility on law enforcement authorities than ever before to apprehend criminals even before they commit crimes. This idea of arresting people before they commit a crime was first featured in the film ‘Minority Report’ starring Tom Cruise and directed by Steven Spielberg. Today, this pre-crime strategy has gone beyond the movie, and has become a reality to save lives and property.
To identify potential criminals before they commit a crime, law enforcement officials are increasingly turning to big data technologies. Publicly shared information combined with data from local authorities and intelligence information from law enforcement offices help police to spot criminals with higher degree of accuracy before trouble starts. As a result, police officers tend to less reactive, so the possibility for shooting the wrong person is reduced. Moreover, these officers hone in on the crime hotspots to nab criminals as soon as they emerge out of their hiding. Such planned missions based on big data analytics have helped law enforcement officials to reduce crime rates in many major cities worldwide. A case in point is the LAPD that uses big data technology to bring down crime rates in the Los Angeles metropolitan area. The big data model used by the LAPD was developed by Professor George Moher, and so far it has reduced burglaries by 33 percent, violent crimes by 21 percent and property crimes by 12 percent respectively.
Other than city crimes, big data analytics is also coming handy to fight cross-border crime. Many of the leading agencies such as Interpol use big data analytical tools extensively to solve past cases, and to identify the possible future ones. For example, the case of Jill Dando was solved through big data analytics. She was a BBC reporter who was gunned down on the doorstep of her home in 1999. At the time of her murder, she was making an appeal on behalf of the Kosovan-Albanian refugees who were driven out of their homes by the militia groups that backed Milosevic. Her case is an example of cross-border crime that involved many law enforcement agencies across countries. Her case was finally solved in 2012 when the Interpol concluded that she was killed by a Serbian hitman. To prevent such crimes in the future, big data anlytics is essential as it can be used to track the whereabouts of possible hitmen and to know more about the weapons and ammunition that cross borders.
Besides cutting back on violent crimes and robberies, big data is also being used to identify white collar criminals who are involved in financial crimes such as insurance frauds, insider trading, money laundering and healthcare fraud. Prior to the advent of big data, investigators had a hard time finding these criminals because they were analyzing existing documents in a linear fashion that provided little to no clues about the activities of criminals. Today, big data software like Gotham of Palantir brings together structured and unstructured data to analyze it for potential evidence of a crime. More importantly, it also presents the evidence needed for legal counsel to prosecute those criminals who are involved in such money laundering crimes.
The above examples go to show how big data technologies are being used to fight all kinds of crimes. While it has not helped to eliminate crime completely from the society, it has nevertheless given a new perspective to fighting crime. Furthermore, big data has empowered law enforcement authorities with the right tools needed to identify criminals and bring them to light before they commit a crime. Going forward, it is hoped that big data will be used more effectively to make this world a safe people for everyone.
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