Graph databases could be the answer to the growing fraud problem
By Emil Eifrem, co-founder and CEO of Neo Technology
Businesses, banks and insurance companies are losing billions of dollars every year due to fraudsters who have developed sophisticated ways of setting up new identities and eluding detection.
According to the Association of Certified Fraud Examiners (ACFA) 2014 Global Fraud study, survey participants estimated that a typical organisation loses 5% of revenues each year to fraud. If applied to the 2013 estimated Gross World Product, this translates to a potential projected global fraud loss of nearly $3.7 trillion.
The mean loss caused by the frauds in the ACFA’s study was $145,000. Additionally, 22% of the cases involved losses of $1 million or more.
Whilst no fraud prevention measure will wipe out fraud altogether, procedures can be put in place that will dramatically cut fraud-related losses. The place to start is individual data points and their connections. These connections are often ignored, when in reality they are the first place to start to look for the clues to any potential fraud being carried out.
Joining the dots and making sense of these connections, however, is more complex than it sounds. It is about looking at data from a new perspective and looking for patterns in it. This powerful technology developed to pull together relationships in data is called a graph database.
An increasing number of businesses, banks and financial institutions are turning to graph database technology in a bid to detect fraudulent behaviour and stopping it in real-time. The technology is also helping develop next-generation fraud detection systems based on connected intelligence.
Types of fraud
There are various types of fraud – insurance fraud, e-commerce fraud and first-party banking fraud etc.. The latter is where fraudsters apply for credit cards, loans, overdrafts and unsecured banking credit lines, with no intention of paying them back.... continued on page two >