Continuing rise in card use, a higher proportion of online shopping and the growing sophistication of fraudsters are the main cause of this trend. The study was published in conjunction with Featurespace, a global machine learning adaptive behavioural analytics fraud prevention software provider. Its services and products are employed in over 180 countries via a wide range of customers, including TSYS, as well as Vocalink/Zapp, William Hill and Betfair.
In 2015, costs associated with incidents of card fraud increased 34% to USD 21.8 bn and fraud-related costs associated with genuine transactions declined, increased 24% to USD 18.3 bn.
Furthermore, according to Oakhall representatives, 80% of card fraud in the UK happens in “card not present” online or phone transactions where existing systems often trigger higher numbers of genuine transactions declined, resulting in customer dissatisfaction and lost income for the banks.
Using industry data, Oakhall estimates that global financial services companies could save at least USD 15.8bn (2014: USD 12.2 billion) annually by employing adaptive, machine learning fraud prevention software. The estimated savings comprising of USD 5.5bn (2014: USD 4.1bn) reduced fraud and USD 10.3bn (2014: USD 8.1bn) reduced fraud management costs and lost revenue.
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