Retail fraud is more than a persistent challenge—it’s a growing threat that’s evolving alongside the rapid rise of eCommerce. In 2024, online retailers faced a whopping 140% surge in credit card fraud in the US, while online payment fraud losses are expected to exceed $343 billion globally by 2027, underscoring the critical need for smarter, stronger defenses against digital fraud.
As shoppers increasingly embrace online retail, businesses must stay ahead of fraudsters to protect profits and maintain customer trust. This article explores the many faces of retail fraud and offers proven strategies to combat it and secure the digital marketplace.
What Is Retail Fraud?
Retail fraud encompasses a variety of deceptive practices aimed at unlawfully obtaining goods, services or financial benefits from retailers. It affects both brick-and-mortar stores and eCommerce platforms, posing significant challenges to businesses across the retail landscape. As online shopping grows in popularity, the focus on digital retail fraud has intensified, with fraudsters employing increasingly sophisticated tactics to exploit vulnerabilities in online transactions.
Retail fraud results in financial losses for retailers, damages their reputation and erodes customer trust. Understanding the various forms of retail fraud is crucial for businesses looking to implement effective prevention strategies and protect their bottom line.
The Impact of Technology on Retail Fraud
Fraudsters increasingly leverage sophisticated tools such as automated bots, deepfake technology and dark web marketplaces to execute their schemes. Technological advancements enable them to mimic legitimate customer behavior, exploit system vulnerabilities and engage in organized fraud activities that are challenging for traditional detection methods to identify.
On the other hand, retailers are turning to AI and machine learning to enhance their fraud detection and prevention capabilities. These technologies allow for real-time monitoring of transactions, adaptive learning from historical data and the identification of suspicious patterns indicative of fraudulent behavior. By employing these strategies, eCommerce businesses can proactively mitigate risks and protect their operations while maintaining customer trust by ensuring a secure shopping environment.
Different Types of Retail Fraud
Understanding the various types of retail fraud is essential for implementing effective prevention strategies. Here are some of its most common forms:
1. Payment fraud: Involves unauthorized credit card use, such as stolen or counterfeit card details, often used to make fraudulent purchases. Card testing is a common method, where fraudsters run small transactions to validate stolen cards before making larger purchases. Chargeback fraud (or friendly fraud) occurs when customers falsely dispute legitimate transactions to get a refund while keeping the item.
2. Identity fraud: Fraudsters use synthetic identities—fake profiles created with real and fabricated information—or take over legitimate customer accounts (account takeover) to make purchases or exploit stored payment details. These methods are particularly damaging because they often go undetected until significant losses occur.
3. Return and refund fraud: Exploits retailers’ return policies. Examples include wardrobing (returning used items as new), using fake or stolen receipts for refunds, or claiming that a delivered package was empty or incorrect to secure a refund without returning anything.
4. Coupon and promotion abuse: Customers misuse promo codes, discounts or special offers. Bots are often deployed to generate multiple discounts or exploit codes repeatedly, eroding profits and undermining marketing efforts.
5. Gift card fraud: Involves stealing, cloning or exploiting gift cards by guessing codes or hacking systems. Fraudsters may drain card balances or sell compromised gift cards to unsuspecting buyers.
6. Triangulation fraud: This involves fraudsters creating fake online storefronts to collect payments. They fulfill orders using stolen credit cards, leaving the retailer to deal with chargebacks and customers frustrated by unfulfilled orders.
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How to Combat Retail Fraud
One of the most effective strategies for fraud detection in the retail industry is real-time transaction monitoring. By analyzing millions of transaction patterns using machine learning, retailers can quickly identify and respond to fraudulent activities. Automated risk scoring categorizes transactions as low, medium or high risk, allowing for immediate action—such as accepting low-risk transactions while blocking high-risk ones.
Another key solution is the application of dynamic friction, which allows businesses to automate responses based on risk levels. For example, retailers can streamline the checkout process for low-risk users while applying additional verification steps for higher-risk transactions. Additionally, implementing customizable risk rules enables retailers to tailor their fraud detection strategies according to specific business needs and industry standards.
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Proactive Measures for Retail Fraud Prevention
Implementing an automated fraud detection system is the cornerstone of proactive retail fraud prevention. These systems continuously monitor all user activities from signups to checkouts and automatically flag unusual behaviors in real time. By using machine learning algorithms, merchants can develop predictive models that adapt to new fraud patterns, enhancing their ability to prevent fraudulent transactions before they occur. For example, if certain purchasing behaviors are correlated with fraudulent activity—such as purchasing high-end products shortly after account creation—the system can adapt its risk scoring in real time to flag similar future transactions.
Transaction monitoring is also crucial for detecting unusual activities during the purchase process. Retailers can implement velocity rules that monitor the frequency of transactions from a single account within a short timeframe. If a customer attempts to make multiple purchases in rapid succession—especially high-value items—this behavior can trigger alerts for potential fraud. The system can then automatically block these transactions or require additional verification.
Incorporating digital footprint analysis during signup and account creation helps create a detailed profile of each user based on their online behavior with information already at hand (email, IP address, phone number, etc.), making it easier to identify potential fraudsters early in the user journey. For instance, if several accounts are registered from a single IP address with similar purchasing patterns, this could indicate a coordinated fraud attempt. By flagging these accounts for further review, retailers can prevent fraudulent transactions before they occur.
Finally, integrating anti-money laundering (AML) tools ensures ongoing compliance and risk management by continuously monitoring transactions against global sanctions and crime lists. By embracing these automated solutions, retailers can significantly strengthen their defenses against retail fraud while maintaining a seamless customer experience.
How SEON Helps
SEON provides easily integrated solutions that automate fraud prevention and detection, allowing retailers to focus on growing their business without extensive manual oversight. With features like real-time digital footprinting and automated transaction monitoring, SEON quickly identifies and mitigates fraudulent activities, ensuring a secure shopping experience for customers.
The platform’s industry-preset and customizable AI-driven rules allow retailers to tailor their fraud detection strategies to specific needs, all while maintaining seamless integration with existing systems. Additionally, SEON’s AML capabilities enhance compliance efforts by automating screening against critical watchlists, such as sanctions and Politically Exposed Persons (PEP) lists. This comprehensive approach minimizes the risk of money laundering while simplifying regulatory compliance.
By combining advanced fraud detection, AML monitoring and AI-driven insights, SEON empowers retailers to protect their eCommerce platforms effectively without disrupting the shopper experience. This means that businesses can safeguard their operations while concentrating on expansion and innovation, all while keeping their systems secure from evolving fraud threats.
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