Case Study

Case Studies: Big Data Analytics

Money Laundering

Objective:

To find the criminal group involved in money laundering

Problem Statement:

A high profile national security agency wanted to keep a track on all the illegal transactions involving huge amounts of money occurring in the banks. Their main focus was on the locations where the crime rate is too high.

Solution:

Bank account data is huge, keeping track of each account and its transaction manually is too time consuming and hectic for the national security agency. In manual tracking, chances of errors are too high. However, by installing the crime analytics software that is integrated with big data analytics, each activity of every suspected account was monitored precisely. With the help of this software, they could keep a track by analyzing the huge bank data with the in-built tools of the software like statistical methods, computation intelligence, mathematical optimization, neural networks and methods based on statistics, probability and economics. Once a refined data was achieved from the symmetric transactions and crime locations, it helped in tracking down the criminal group by identifying its approximate location and identity.


Criminal Activity

Objective:

To find the suspects of a terrorist activity

Problem Statement:

A national security agency investigated a bomb blast case at a shopping centre. While collecting the investigating parameters, it was found that the CCTV footage of a day prior to the blast was missing.

Solution:

As part of investigation all the data of the employees working at the shopping centre, CCTV footages, showrooms’ and customers’ data were collected. CCTV footage of a day prior to the bomb blast was missing, which raised a lot of questions. With the help of the big data analytics software, all the collected data was analysed. The background details of the employees and owners were also tracked by the in-built text mining tool in the software. Anomaly detection techniques of the software helped in digging out the contact details, movement details of employees and owners. The software being capable of managing any type of data analysed and highlighted few suspects. This software connected all dots and showed suspect’s identity and approximate location of the suspect in just 36 hours. Agency caught the suspect with the help of location provided by the software and now further investigation is going on.


Cyber-crime - Identity theft

Objective:

To identify the people and motive behind an Identity-theft cyber-crime

Problem Statement:

The complainant received threat calls from the recovery department of a reputed bank asking him to clear off the debts of around rupees 10 lakhs. Six similar cases were also reported. Out of the seven cases registered, only one had an account in that bank and two were only using the credit card of that bank.

Solution:

Initial investigation done by police revealed that the complainants have a personal loan running under their name of Rs. 10 lakhs each with a reputed bank. Further investigation revealed that the complainants had never really taken a loan from that bank. All the complaints lodged in the police automation software somewhere connected the dots and demanded a deep investigation. The police then collected the background details of the complainants as well as the bank employees with the help of big data software. All contact details, movements, online activities etc. were tracked and data was analysed with the in-built text mining, anomaly detection, prediction and rules engine tool of the software. It was revealed that all the seven complainants had bought their phones from the same showroom around two years back. This was the only common connection between them. Further investigation was done on the showroom and also on the employees of the bank. One of the employees had an unexplainable amount of money in his account. The owner of the showroom and that employee were related to each other. It was revealed that the owner collected the personal data of his customers and used to dig out IDs online. He then took loans on their behalf from the bank and the employee involved would easily pass him loan. It is a case of cyber-crime as there was identity theft involved, also it became a huge financial scam. The suspects were arrested and appropriate action was taken by the police.


Fraud Case

Objective:

To identify the idea and track the suspect

Problem Statement:

A complaint was filed against a reputed builder stating that he took 80% of the amount for a house at a prime location. However, the builder allotted a different house to the complainant after four years of project completion.

Solution:

After the first round of investigation, it was revealed that there were other similar complaints as well. All the data of these complaints was collected and fed to the big data analytics software. The report showed that a lot of NRIs were also involved with the builder. The anomaly detection tool in the software helped in fetching the data of these NRIs, again this data was analysed to see the relation between the builder and the NRIs. Within 6 hours all the dots were connected and was found that those NRIs worked for the builder. They were converting the builder’s black money into white by booking fake houses and taking loan from banks. It was revealed that it is a case of fraud. Further investigation was done to catch hold of other fraudsters.


Human Trafficking

Objective:

To find the criminal and groups involved in human trafficking

Problem Statement:

A complaint was lodged at the local police station of the city by hospital authorities. A 12 years old boy had been beaten up with bats and rods, he also had a few burn marks on his body.

Solution:

The first round of investigation revealed that the boy had come from Bangladesh to find work here. He was working with a motel from the past 3 months. With the help of the big data analytics software, all the details about the motel, like the address, financial details, employees’ and owner’s data were collected. After analysing all the data and forming a relation between all the entities, it was found that one of the staff members used to supply young children to work at the motel as well as various other locations. The owner was also involved in the case and was found guilty of trafficking young kids and making them work at minimum wages. The software further analysed more data and revealed that there were many more children who went missing from a small village in Bangladesh. A few more children were rescued and united with their families.


Trading of illegal weapons & child labour

Objective:

To find out the criminal group involved in illegal weapons trade, child trafficking and child labour

Problem Statement:

A child was shot dead in a small village near the border. The other children with whom he got involved in a fight were carrying pistols with them.

Solution:

Police started investigation and found out that all the children involved in the fight and the one who was shot, worked in a gun factory located near the village. The victim had run away from the factory and was killed by his co-workers. With the help of the software, identity details of the workers, their families and owner were revealed. The software tracked the movements of the owner of the factory as well as the workers. After the first round of analyses, the owner was highlighted as the main suspect. He was involved in illegal trading of weapons. He had also hired young children from across the border by making their fake age certificates. With the face recognition tool, police searched for the families of the workers and sent the children to their families.