editorial
The COVID-19 pandemic has led to a surge in scams, causing people to become increasingly anxious about fraud. A new study conducted by AI and analytics firm SAS reveals the scale of the global fraud problem.
The study, titled “Faces of Fraud: Consumer Experiences With Fraud and What It Means for Businesses,” surveyed 13,500 consumers across 16 countries. The results show that fraud is a common experience for most people, with 70% of respondents reporting that they have been victims of fraud at least once. Furthermore, 40% said they had fallen victim to fraud more than once.
The study also found that fraud incidents have increased, with 47% of respondents saying they have experienced more fraud in 2022 compared to previous years. This rise in fraud has made consumers more cautious, with 86% admitting to being more wary of fraud than in the past.
Stu Bradley, Senior Vice President of Risk, Fraud and Compliance at SAS, emphasized the impact of successful fraud exploits on organizations in targeted industries such as banking, insurance, government, retail, and telecommunications. He stressed the need for robust fraud defenses and highlighted that 89% of survey respondents believe organizations should do more to protect against fraud.
However, there is a silver lining for businesses. The majority of consumers are willing to make sacrifices in order to enhance security. Three-quarters of respondents said they would accept delays and additional checks in transactions for better fraud protection. Additionally, eight out of ten people expressed willingness to use biometric methods, such as facial recognition or retinal identification, for payments and transactions. More than half of the respondents (57%) prefer using unique identifiers like biometrics for authentication at the time of transaction instead of relying on passwords.
The study also points out the benefits of AI-enabled fraud detection. It can help organizations detect fraud earlier and more accurately, improving the efficiency of their real-time fraud prevention strategies. Unlike traditional rules that can be easily tested and overcome by fraudsters, machine learning applied in fraud detection allows organizations to identify anomalies in real-time and stay ahead of evolving threats.
The study was conducted by SAS in partnership with 3Gem Research and Insights. The sample size included 13,500 respondents, with an equal split of men and women.
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