An analytic software firm has released an interactive map of European card fraud. It shows that card fraud losses for 19 European countries reached 1.8 billion euros, a new high. The UK saw the highest losses at £618m, a 9 percent rise over 2015, topping the previous peak in card fraud, set in 2008 after the introduction of chip and PIN.
Card not present (CNP) fraud has gone from 50 percent of gross fraud losses in 2008 to 70 percent in 2016. Ten countries saw an increase in fraud losses, while eight saw a decrease. The map is based on data from Euromonitor International, with information from the UK Cards Association.
Martin Warwick, senior consultant for fraud at FICO, said: “The growth in online spending and CNP fraud brings new challenges for banks and retailers, as criminals thwarted by chip and PIN have moved to a less risky channel. Hiding amongst the growth in online purchases is great from a criminal point of view, but finding and stopping fraudulent transactions just gets tougher. Spotting the ‘needle in a haystack’ requires new behavioural analytics and artificial intelligence, combined with enhanced information from outside the traditional data contained within a purchase.”
In 2015 the UK’s card fraud rise was the highest in Europe, but in 2016 two countries saw higher rises — Poland (+10 percent) and Sweden (+18 percent). The UK’s rise from 2015 to 2016 was just half of that from 2014 to 2015.
France had the highest basis points at 8.9 (ratio of fraud losses to sales) among the 19 European countries, compared to 7 basis points for the UK. However, French card spending is half that in UK, making UK losses much greater. Together, the UK and France account for 73 percent of the total loses among the 19 countries in 2016, followed by Germany, Spain, Russia, Italy and Sweden.
FICO says that it’s working with banks to advance the use of machine learning and artificial intelligence to identify fraud faster. The key, Warwick says, is to spot anomalies without putting friction into the transaction.
Scott Zoldi, FICO chief analytics officer, said: “It’s no longer just about identifying patterns that are unusual for the customer — we’re also looking at anomalies at the mobile device, IP address and merchant level. All of these have ‘behaviors’ just as individuals do, and we’re using our 25 years of experience in artificial intelligence to identify those. FICO has developed archetype analytics that taps into the rich source of mobile context such as advanced geolocation, allowing us to use that information in FICO Falcon Fraud manager to make real-time decisions during a transaction. These analytics draw on our patented work with customer behaviour archetypes.”
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Ryan Wilk, director at a fraud mitigation product company, NuData Security, said: “This rise in recorded fraud figures is astounding, and bad news for consumers who often bear the brunt of many direct costs (especially in account takeover and new account fraud). The increasing volume of attacks globally has also been attributed to more fraudsters willing to commit the crime, more data available on the black market, and more financial institutions and merchants that are vulnerable to attacks. It’s incumbent upon companies to secure their customers’ trust by keeping their accounts safe from hackers. They can’t afford to hear their customers say, ‘My account got hacked again.’
“To detect out of character and potentially fraudulent transactions before they can create a financial nightmare for consumers, we must adopt new authentication methods that they can’t deceive. Solutions based on consumer behaviour and interactional signals are leading the way to provide more safety for consumers, and less fraud in the marketplace. There are solutions on the market now that can identify machines from humans, then separate good machines from bad, selects known humans from unknown humans, and finally sorts unknown humans demonstrating low-risk signals from unknown humans demonstrating high-risk signals. This process lets organisations fast track the known and low-risk users for an optimal experience, saving the friction and traditional authentication methods for the highest risk users.”
