The rise in digital purchases has created both opportunities and challenges for retailers. Today, nearly two-thirds of adult consumers globally use digital payments, and by 2027, digital revenue is predicted to exceed $14.9 trillion. But this growth also has made retailers’ digital payment processes a target for credit card fraud, online payment fraud, identity theft and account takeovers. In fact, chargeback requests are expected to reach $41 billion by 2027.
Economic uncertainty and inflation have exacerbated the problem, creating environments ripe for sophisticated fraud schemes, calling retailers to take a more vigilant approach to fraud prevention. But it is a delicate balance. Retailers must embrace fraud prevention strategies that are effective, yet nearly frictionless for real customers, to avoid churn. Building trust is crucial, and customers shouldn’t feel overwhelmed by overly complex security measures. Successful retailers have found that 80% of value creation comes from existing customers, achieved by consistently providing a unique and seamless customer experience.
Trust-building involves not just transactional security but also respectful, transparent and positive interactions with technology, where security measures and the user experience complement each other rather than compete. Effective fraud prevention safeguards both the consumer and the retailer’s financial assets and enhances the customer journey with interactions that are safe and secure, ultimately deepening trust in the brand.
Advancement in Fraud Technologies with Limitations
Among the first lines of defense against digital fraud are fraud management and authentication. These tools have developed from password-based systems to complex multi-layered strategies that combine biometrics, two-factor authentication and behavioral analytics with more conventional methods like passwords and PINs. These techniques aim to positively identify a person with high assurance while avoiding needless friction in the user experience.
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Fraud management systems have grown increasingly complex, utilizing AI and machine learning to identify and stop fraudulent activity. They can anticipate and neutralize risks before they arise, while minimizing false positives that could interrupt transactions by analyzing massive volumes of data to discover patterns indicative of fraud. However, there are limitations on how effective these methods can be. Tighter authentication policies can disrupt a smooth user experience, causing a drop in participation and increasing abandonment rates. Simple security controls can leave systems open to fraud, especially on online platforms where users must have easy access without sacrificing security.
Integrating fraud prevention seamlessly into the customer journey enhances protection without causing disruptions. Advanced analytics and machine learning algorithms can examine customer behavior patterns, including subtle indicators like email address usage, to detect potential fraud. This is highly effective, especially when considering these seemingly minor yet critical aspects.
A Common Denominator for Fraud Prevention and the Customer Journey
Email-centric fraud prevention, including enhanced verification processes for retailers, has emerged as a critical way to help mitigate fraud while ensuring a frictionless customer experience. Combining first-party data and consumer behavioral insights associated with these email addresses, such as the first activity date, email frequency and popularity, allows retailers and/or third-party merchants the ability to authenticate the user’s identity without disruption.
An enhanced email address verification process also includes a thorough evaluation of email domain authenticity. This goes beyond simply checking if an email address is valid to examining intelligence associated with the email domain’s reputation and security standards. This analysis includes assessing the domain’s history, security features and any associations with fraudulent activities to better gauge its legitimacy.
Another benefit of email-based fraud prevention is through the historical consistency of email addresses. This includes monitoring the longevity and usage patterns of an email address over time. Email addresses that have a consistent legitimate usage history over an extended period are less likely to be linked with fraudulent activities. Alternatively, sporadic or irregularly used email addresses may raise concerns.
Linking email addresses with other identity markers also remains important. This involves cross-referencing email data with other personal information like phone numbers, physical addresses and many other data points. By creating a comprehensive profile of an individual’s online presence, retailers can gain deeper insights into the authenticity of the user’s identity as well as the person associated with the email address.
The integration of fraud prevention and the digital customer experience to enable retail growth is a strategic imperative, and a common denominator is often the inclusion of email address intelligence. In an environment characterized by rising fraud rates and shifting customer expectations, striking a strategic balance is more important than ever. By taking advantage of the latest machine learning and AI fraud prevention solutions, retailers can adapt to different risk levels and consumer profiles. Taking a proactive approach, these systems should prioritize predictive models over reactive ones, anticipating potential fraud and guaranteeing a smooth client journey.
For 20+ years, AtData VP of Fraud and Data Strategy Diarmuid Thoma has specialized in developing fraud prevention strategies and platforms for the world’s largest companies. He was a founding member of Trustev, a global fraud prevention platform that was acquired by TransUnion in 2013.
