How do you catch a crime gang that operates across 36 states, is constantly on the move, and operates by recruiting locals to carry out the dirty work while the ringleaders hide out in motels and safe houses?
This is the challenge facing the task force set up to tackle what has become known as the Felony Lane Gang. A highly organized network of transient criminals which has been operating for at least five years and is responsible for hundreds of petty thefts totaling tens of millions of dollars.
Although the gang had been operating for years, no one in law enforcement had even realized that they were dealing with organized crime, until they started to look at the bigger picture.
Cooperation between inter-state as well as between local law enforcement agencies is often difficult, but it does happen. So when detectives at inter-agency conferences began to realize the startling similarities of the petty crime waves they were attempting to stem, the scale of the operation started to become clear. And it was also clear that they would need a new approach to tackling it.
Also at one such conference was Craig Richardson, CEO of Wynyard Group, which he had set up with the specific focus on Big Data-based crime fighting analytics. Members of his team were former crime fighters themselves, including Senior Advisor and member of the board of directors, Louis Grever – a 25-year veteran of the FBI who held senior posts at the agency’s Science and Technology Branch. “Cops – God love ‘em – but they’re not technologists!” says Grever.
“With the decentralized model of policing we have, federal agencies, sheriff’s departments, local police departments – they do try to cooperate, but cooperating across a state border or beyond is very difficult. The gangs know this and take full advantage. They move around to avoid anyone joining the dots together and realizing they are dealing with an organized group. They change their identities, cars and cell phones so unless someone is looking at it on a national level they are going to stay hidden.”
And stay hidden they had. Numerous people – mainly women recruited locally to carry out petty crime – had been arrested. But the ringleaders of the gang, which was named for its habit of using the lane furthest from the surveillance cameras while cashing stolen checks at drive-through bank tellers, remained elusive.
In order to tackle this problem with advanced crime analytics, Wynyard joined the working group set up to bring down the Felony Lane Gang – initially by the Marion County Sheriff’s office, but now expanded to over 140 agencies.
The gang often strikes where their victims, mainly women, are likely to leave belongings unattended – theme parks, gyms, shopping malls – and makes full use of their takings, by cashing stolen cheques, credit card fraud and misusing stolen identity documents.
When local law enforcement agencies identified that these criminals were on the move they realized that there was a need to aggregate all the disparate data that was being collected across all of these agencies. The data operation against the Felony Lane Gang involved automating the collection and filing of every crime report which fits the gang’s profile. This involved going through records dating back up to a decade, but was made easier by the use of textual analysis routines developed by Basis.
Once this was underway, patterns quickly began to emerge, and it became clear that the group’s movements could be followed by tracking the movement of petty crime matching the Felony Lane modus operandi as it moved from county to county and state to state.
Even more critically, networks between people began to emerge, too – like secret messages written in lemon juice and held to a flame. The software was able to recognize names, and build connections between them based on locations and times. It was also able to estimate suspects’ positions in the gang’s internal hierarchy, by analyzing who was connected with who, and the number of other people in the chain between two particular individuals. As well as incident reports, data came in from police interviews with the low-level local recruits who were frequently picked up.
By: Bernard Marr, Contributor, Forbes
Originally published at www.forbes.com
This excerpt is from the Forbes.
To view the whole article click here.
 |
 |
 |
