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EUROPEAN CARD FRAUD FOR 19 COUNTRIES HIT RECORD €1.8B IN 2016

Interactive map from FICO and Euromonitor International shows UK had highest card fraud losses in 19 countries surveyed

HIGHLIGHTS:

  • Total card fraud losses for 19 European countries studied reached nearly €1.8 billion
  • UK card fraud rose 9 percent in 2016, to £618 million
  • Interactive online map from FICO and Euromonitor International compares fraud loss trends across the region

Analytic software firm FICO today released an interactive map of European card fraud, which shows that card fraud losses for 19 European countries hit approximately €1.8 billion, a new high.The UK saw the highest losses at £618 million, a 9 percent rise over 2015, topping the previous peak in card fraud, set in 2008 after the introduction of chip and PIN.

More information: www.fico.com/europeanfraud

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 additional information from the UK Cards Association.

“The growth in online spending and CNP fraud brings new challenges for banks and retailers, as criminals thwarted by chip & PIN have moved to a less risky channel,” said Martin Warwick, senior consultant for fraud at FICO. “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.

Fighting Back with AI

FICO is 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.

“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,” said Scott Zoldi, FICO chief analytics officer. “All of these have ‘behaviors’ just as individuals do, and we’re using our 25 years of experience in artificial intelligence to identify those.”

Mobile analytics is an important area here, said Zoldi, who developed or co-developed half of the company’s 70 patents in artificial intelligence and machine learning. “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,” Zoldi said. “These analytics draw on our patented work with customer behaviour archetypes.”

Banks and card issuers are also beginning to step up their use of real-timecustomer communication. “Contacting consumers early using automated two-way SMS is a key solution to making sure the transactions are valid,” Warwick said. “If this is fully automated and tied into the fraud solution — as it is with FICO Customer Communication Services and the FICO Falcon Platform — then cases can be closed without human intervention and consumers can be allowed to continue to spend when and where they want.”

The FICO® Falcon® Platform is the leading card fraud management solution worldwide. It protects more than 2.6 billion payment cards from fraud using artificial intelligence analytics.