1,600 fraudulent websites were blocked in Q3, as initiated by Bank of Russia. Over the third quarter, the regulator detected over 2,100 fraudulent web resources. Criminals stole nearly US$ 16.3 million or 1.2 billion rubles from individuals making online purchases.
Overall, fraudsters carried out 180,000 operations from July to September 2020 that were not authorized by customers. These operations totaled US$ 34 million or 2.5 billion rubles.
According to the Bank of Russia, one of the reasons behind the growth of this figure (+32% year-on-year) is an increase in the amount of transactions using electronic payment instruments.
The number of fraudulent telephone numbers revealed by banks rose more than twofold: 10,700 in 2020 Q3 against 5,200 last year.
Since online payments are seeing their rapid growth globally, the concerns raises towards remote payment fraud.
The recent study from Juniper Research has found that businesses in ecommerce, airline ticketing, money transfer and banking services, will cumulatively lose over US$200 billion to online payment fraud between 2020 and 2024; driven by the increased sophistication of fraud attempts and the rising number of attack vectors.
The new research, Online Payment Fraud: Emerging Threats, Segment Analysis & Market Forecasts 2020-2024, found the increasing ubiquity of digital payments provides an ever-increasing attack surface for fraudsters. The research recommends that payments industry stakeholders focus on an omnichannel fraud approach to mitigate these challenges. This approach must encompass both strict cybersecurity at access points, as well as analytics such as machine learning, to identify fraudulent behavioural patterns.
Pursuant to the study, the machine learning has become a crucial tool in the fraud detection and prevention arsenal, as it enables payments industry stakeholders to analyze transaction flows in a holistic way, unlocking hidden insights on fraudulent behaviours. The incorporation of machine learning into fraud detection and prevention software will drive spending forward, reaching $10 billion in 2024, a 15% increase on 2020.
Research co-author Nick Maynard explained: “The rapidly evolving nature of payment fraud and increased sophistication in attack methods requires machine learning adoption at scale, in order to minimise risk. Constant innovation in analytics and data models is increasingly essential to constraining fraudulent behaviours in payments”.
The research also found that digital money transfer is a growing area for payment fraud, with losses growing by 130% from 2020 to 2024. Digital money transfer fraud is particularly strong in emerging markets, with payments vulnerable to SIM swapping fraud and synthetic identities, with less robust security measures in place. The research therefore recommends that ongoing KYC (Know Your Customer) verification, including events-based re-verification following onboarding, are elements that are essential to secure the rising levels of digital transactions.
