Every year, millions of gift cards are purchased and redeemed, making them prime targets for fraudsters. According to Capital One shopping research, gift card fraud is the most common form of fraud, with 26.6% of victims reporting they lost money while using or reloading gift cards.
The US Department of Homeland Security Investigations (HSI) unit reports that gift card fraud, often perpetrated by Chinese and other organized retail theft rings, has led to losses in the hundreds of millions of dollars globally. This type of fraud is used to fund other illicit activities, including drug and human trafficking.
The Federal Bureau of Investigation (FBI) recommends that retailers implement procedures to mitigate these attacks.
Fraudsters are becoming increasingly sophisticated, employing tactics such as barcode theft, phishing scams, and AI-driven cyberattacks. Organized crime networks have also entered the fray, leading to significant financial losses and a loss of consumer trust for many brands.
In response, retailers are leveraging AI-enabled open-source intelligence (OSINT) and publicly available information (PAI) with data analytics to identify fraud patterns, block scam-related transactions, and protect brand integrity. These data insights are equipping loss prevention professionals with new tools to detect emerging threats and uncover hidden connections.
Common Gift Card Fraud Tactics and Ways to Combat Them
Gift card fraud occurs both in-store and online, with criminals continually adapting their tactics to exploit vulnerabilities and avoid detection.
- Return Fraud: One common in-store scheme involves purchasing merchandise with stolen credit cards and then returning the items for store credit or gift cards. While many retailers have strict return policies to prevent abuse, fraudsters often use fake tracking ID (FTID) tactics to evade identification checks, allowing them to return stolen goods or manipulate refund policies. Once they have gift cards, criminals can either sell them or use them for purchases, effectively converting stolen merchandise or fraudulent returns into untraceable funds.
Retailers can use OSINT tools to monitor transaction data across various stores and online platforms. For instance, they can cross-reference purchase data with known fraud databases to determine if a returned item was purchased using stolen credit card information. This helps to flag suspicious returns in real time.
- Barcode Theft: Another tactic involves draining funds from a gift card by obtaining its barcode, Card Verification Value (CVV), PIN, or activation code by tampering with the packaging. After obtaining these details, criminals reseal the card packages and place them back on store racks. They then monitor online activity, waiting for unsuspecting consumers to purchase and load funds onto the cards. Once activated, the criminals quickly drain the card balances before legitimate buyers can use them.
To combat barcode theft, some retailers have moved store-branded gift cards behind the checkout counter, distributing them only after purchase. This adds a layer of security, although it requires additional store resources (such as employee involvement) and could potentially slow transactions at the point of sale.
- Phishing Scams: Phishing scams are not just for stealing personal information; they also target consumers’ financial assets by convincing them to purchase gift cards or provide sensitive payment details. Once criminals have convinced consumers to purchase gift cards, they gather the card details and use them to drain the funds. The scammers often instruct victims on which gift cards to buy and where to purchase them, frequently directing them to load the cards for an online store, streaming service, or specific retailer. Many of these scammers are part of organized crime networks, working together to drain the cards and convert the stolen funds.
OSINT tools can help retailers analyze connections between individuals and networks involved in phishing scams. By cross-referencing PAI—such as social media profiles, IP addresses, and transaction histories—OSINT can reveal relationships between scam actors and assist in identifying larger fraud rings.
Supporting Crucial Collaboration
OSINT can support collaboration among retail security managers, loss prevention directors, fraud investigators, and other professionals to spot and deter gift card fraud. AI in particular can be used to detect patterns and anomalies, helping fraud specialists identify potential fraud and members of ORC rings by uncovering hidden connections among seemingly unrelated individuals and transactions.
Additionally, OSINT provides loss prevention teams with resources to collaborate with law enforcement and organizations crucial to combating scams industry-wide, such as the Federal Trade Commission (FTC). Sharing intelligence and developing data-first strategies are key components of prosecuting fraudsters.
HSI urges retailers to report gift card crimes to local law enforcement and to refer incidents to HSI under Project Red Hook. While not all gift card fraud cases will be attributed to organized crime groups, the agency advises that reporting suspicious activity helps HSI gather data for further analysis.
Using data insights to detect emerging threats and identify hidden connections is vital for safeguarding the integrity of gift card programs. As fraudsters refine their tactics, loss prevention professionals can use OSINT and AI for rapid data processing and actionable insights that exceed human capabilities.
This enables loss prevention teams to make more accurate, timely decisions at scale, leading to improved fraud detection and prevention. Most importantly, it allows these teams to respond quickly, mitigating potential losses.
Jen Snell is chief marketing officer at Babel Street, a company that empowers decision advantage for identity, threat, and operations intelligence by providing advanced AI, data, and analytics solutions that enhance decision-making confidence.