A number of factors, including click-and-collect fraud, have been identified as contributing to Juniper Research’s forecast that retailers stand to lose US$71 billion globally from fraudulent card-not-present (CNP) transactions over the next five years.
Part of a new research issued Tuesday, the estimate points to factors such as the U.S. shift to EMV (Europay, MasterCard and Visa) cards, delays in 3DS 2.0 (3D-Secure) and click-and-collect fraud as key drivers behind the rise.
Next year “will herald the arrival of new tools in the fight against fraud”, research author Steffen Sorrell notes in a statement from U.K.-based Juniper Research, a company that specializes in identifying and appraising new high growth market sectors within the digital ecosystem.
“3DS 2.0 will finally begin to roll out and will mark a paradigm shift in terms of merchants and issuers leveraging shared data,” Sorrell concludes in the new research, Online Payment Fraud: Emerging Threats, Key Vertical Strategies & Market Forecasts 2017-2022.
“We also expect passive biometrics, such as the manner in which a device is handled, to become key in the future,” he adds.
Many merchants around the world, the company reports, still perceive fighting fraud as too expensive – contributing to a lack of preparedness against online fraud following the introduction of EMV payment cards in the U.S.
However, Juniper Research’s cost analysis of fraud detection and prevention solutions found that, in most instances, merchants would receive value from their investment.
Forecasting that fraudulent CNP physical goods sales will reach $14.8 billion annually in 2022, findings argue “click-and-collect services were particularly vulnerable given the lack of a residential delivery address.”
The research – which offers an analysis of how the landscape is developing, both in terms of fraudster approaches and service provider strategies – examines key issues, such as the Internet of Things, machine learning and regulatory changes, and how these will impact the industry moving forward.