“Subramaniam went to great trouble to hide his activity. He seems to have thought that carrying data around on memory sticks and using internet cafes would somehow protect him from scrutiny. He was wrong, says Lemon”
Criminals like Subramaniam are highly-organised and run professional fraud networks, but they are not immune to the power of banks’ analytics and business intelligence. When fraud managers monitor for this type of criminal activity, their strength lies in
the wealth of data they have available, from customers’ transaction records to non-monetary information such as log-in details and demographic information.
This example demonstrates the power that lies in this data. It also shows that not only should fraud departments analyse and mine their own data for financial crime detection, prevention and investigation, but it should also be shared readily with peers
and regulatory authorities such as SOCA (Serious Organised Crime Agency).
Fraud departments have a range of tools and techniques at their disposal from the basics such as transaction monitoring in the relatively simple forms of rules, queries and reporting, to more sophisticated fraud detection methods using artificial intelligence,
such as neural networks, to identify links not readily seen by the human eye.
By taking a high-level view of monetary and non-monetary activities on an account, and utilising advanced fraud detection methods, banks can not only reduce their fraud losses but also improve customer confidence.