We recently released our Q1 2024 Digital Trust & Safety Index, which includes data on recent payment fraud trends and generational divides in consumer spending habits. Below, we ask our resident fraud expert and Trust and Safety Architect Rebecca Alter to share her insights on the findings from the report.
1. How do you explain the notable differences in fraud rates among different digital payment types, such as gift cards, prepaid cards, and digital wallets?
Gift cards and prepaid cards have much higher fraud rates compared to other digital payment methods. We found that gift cards have the highest payment fraud attack rate across the Sift network at 14%, followed by prepaid cards at 5%. This is likely because these reloadable cards can be easily purchased with stolen funds and used to make untraceable purchases.
2. What are the key factors driving the higher susceptibility to fraud among younger generations, particularly Gen Z and millennials?
I believe younger generations like Gen Z and millennials are more susceptible to fraud for a few key reasons. First, they are more likely to personally know someone involved in fraudulent activities or be exposed to offers for fraud schemes online. This is partly because they’re digital natives, so they spend more of their time online than other generations. They also appear more willing to engage in first-party fraud by falsely disputing legitimate purchases. This may be because they view this type of crime as victimless if it’s being committed against big box retailers. Additionally, their reduced trust in traditional financial institutions leads to less credit card usage.
3. Could you discuss the implications of younger generations not only being more susceptible to fraud, but also participating in fraudulent activities at a higher rate?
I think there are two main reasons 1.) They have less economic security so are more susceptible to get rich schemes and/or willing to bend the rules to get free items. 2.) They often view scamming large corporations as a victimless crime.
4. What insights does the report provide regarding the generational divide in preferred payment types and its impact on fraud trends?
There is a clear generational divide in preferred payment methods, with millennials and Gen Z overwhelmingly favoring digital wallets for online purchases compared to older demographics. As adoption of these newer payment types grows among younger consumers, it will likely have an impact on evolving fraud trends.
5. How significant is the adoption of digital wallets among Millennials and Gen Z compared to other generations, and what implications does this have for fraud prevention?
Millennials and Gen Z are rapidly adopting digital wallets, using them around 48% more than other age groups for online transactions. This widespread preference among younger generations creates significant implications that fraud prevention efforts need to address as digital wallet usage increases.
6. Can you explain how AI-fueled fraud is impacting consumer behavior, particularly in terms of online shopping frequency?
AI-fueled fraud could potentially impact consumer behavior and online shopping frequency in a few key ways:
- Erosion of trust: As AI is used to power more sophisticated and believable scams, fraud incidents may become more prevalent. This could shake consumer confidence in the security of online transactions, making people more hesitant to shop online frequently.
- Personalized social engineering: With AI language models able to generate highly personalized and contextual messages, social engineering attacks delivered via email, SMS, messaging apps, etc., may become harder to detect as scams. This could trick more consumers into falling victim, discouraging future online activity.
- Synthetic identity fraud: AI could be leveraged to automatically generate realistic synthetic identities at scale by combining pieces of real data. This new fraud vector makes it easier for bad actors to open accounts, make purchases, and siphon funds while avoiding detection.
- Intelligent account takeover: AI models trained on victim data could help automate the account discovery and credential stuffing process required for account takeover fraud at scale across online retailers.
- Deepfakes and voice cloning: Using AI to generate convincing deepfakes of people’s faces or clone their voice makes it easier to impersonate legitimate individuals and businesses for nefarious purposes like financial fraud.
7. What measures can businesses take to address the cybersecurity threats posed by artificial intelligence and mitigate the impact on consumer confidence?
To mitigate AI-driven cybersecurity risks from impacting consumer confidence, businesses should ramp up machine learning fraud detection, identity verification, and customer education around emerging scam methods.
8. How do payment fraud incidents contribute to brand abandonment, and what strategies can businesses implement to regain consumer trust?
When a consumer falls victim to payment fraud with a particular business, it shatters their trust in that brand’s ability to keep their financial information and transactions secure. This breach of trust often leads customers to take their business elsewhere.
Having to deal with the hassles of disputing fraudulent charges, getting new payment cards issued, and updating billing information creates a poor customer experience that reflects negatively on the brand involved.
If a data breach enabled the payment fraud, customers may fear the brand allowed their personal/financial data to be mishandled or inadequately protected. Payment fraud inevitably gets discussed across social media and review platforms, which can tarnish a brand’s public reputation for security if not handled properly.
9. How do businesses balance the need for robust fraud prevention measures with providing a seamless and frictionless customer experience?
Striking the right balance between strong fraud detection and a smooth customer experience is an ongoing challenge. The key to a seamless checkout is smart friction management that deploys risk-based authentication only when warranted. I also recommend mapping out the entire customer journey so you can access risk further up the funnel to prevent downstream fraud.
10. What advice would you give to businesses looking to stay ahead of the curve in terms of combating payment fraud?
To get ahead of rapidly evolving payment fraud, businesses must continuously monitor new threats, utilize real-time machine learning fraud detection, implement secure customer authentication, establish cross-functional internal anti-fraud teams, and take a comprehensive approach integrating people, processes and technology.
Explore more insights in the Q1 Index report.