A new study from Juniper Research has found that merchant losses to online payment fraud will exceed $206 billion cumulatively for the period between 2021 and 2025. This figure, equivalent to almost 10 times Amazon’s net income in the 2020 financial year, demonstrates why merchants must make combatting fraud, through the use of machine learning-based fraud prevention platforms, an immediate priority.
The research identified that the pandemic has led to a surge in synthetic identity and account takeover fraud, which threaten the security of entire accounts, alongside associated payment data. The research recommends payment fraud detection vendors focus on partnering on data agreements now, to maximise the data available to machine learning algorithms; boosting chances of identifying fraudulent transactions.
Remote physical goods are leading fraud area of concern
The new research, Online Payment Fraud: Emerging Threats, Segment Analysis & Market Forecasts 2021-2025, found that remote physical goods purchases are the leading cause of online payment fraud; accounting for over 47% of fraud losses in 2021. The research urges payment fraud prevention vendors to offer services based on digital identity verification, to boost security and combat the surge in account takeover fraud.
Research co-author Nick Maynard explains: ‘Given the large amounts of online payment transactions globally, it is essential that this transactional data is leveraged to continually detect fraudulent transactions. Payment providers who can use this data to identify new fraud sources and tactics will be those who prove to be the most resilient to this significant market loss.’
Unprecedented Fraud Risks Leading to Increased Detection Spending
The research also found that spending on fraud detection and prevention platform services will exceed $11.8 billion globally in 2025, from $9.3 billion in 2021. Accordingly, the research recommends that fraud detection and prevention vendors focus on building platforms that can cover all the emerging channels of payment traffic, including new areas such as open banking payments, supported by data partnerships, and backed by large-scale machine learning, to achieve the best outcomes.
