In the past decade, the mantra that “data is the new oil” has become the central maxim of much of the economy. Not only is data a valuable commodity in its own right, but it also enables and accelerates existing businesses. This isn’t only true of digital storefronts — in which every aspect of every transaction can be measured and optimized — but also of brick-and-mortar retail. In the era of omnichannel experiences, data can be linked across digital and physical spaces to build a full picture of each consumer, allowing you to better understand and engage with them.

The problem comes when fraud, theft and other types of malfeasance not only rob companies of goods, but of data, leaving them unable to better serve customers. There is also the matter of how much time and effort needs to be put into combatting retail fraud that could be better spent elsewhere. Therefore, it’s important to look at retail fraud, how it relates to “big data”, and how retailers — online and offline — can use data to combat criminal and “friendly” fraud and increase sales.

The Varieties of Retail Fraud

Although organized shoplifting is a major problem for retailers, retail fraud is a source of lost revenue that many merchants report is their leading concern. When the barrier between digital and physical commerce is becoming blurred, it is easy for bad actors to use the efficiency of digital in physical spaces.

While shoplifting entails direct theft from retailers, retail fraud is often more intricate, attracting criminals seeking higher returns who are more skilled and organized. Its expansion is evident, with increasingly sophisticated methods aimed at exploiting opportunities to pilfer data as well as merchandise. For instance, skimming devices and RFID readers clandestinely capture card information for unauthorized transactions. Additionally, the surge in gift card fraud poses a significant concern for retailers and consumers alike.

Criminals employ diverse tactics, such as hacking into retailer databases to steal activation codes or manipulating cards to deplete funds before rightful use. Securing activation codes and purchase processes for gift cards is imperative for retailers, while also educating consumers on the best ways to safeguard against such fraud.

Other examples of retail fraud include price tag swapping or exploiting lenient return policies, often resulting in returns of stolen goods or refunds with counterfeit receipts. Implementing stricter return policies, utilizing unique stickers on receipts, or mandating identification during returns can help mitigate these tactics.

Chargeback fraud, or “friendly fraud,” poses a complex challenge for online retailers, with fraudsters exploiting the process by making false claims about products or services, resulting in unwarranted chargebacks and massive financial losses for retailers. Customers may falsely assert a charge as fraudulent or claim non-receipt of a shipped product to secure a refund while retaining the item. Creative manipulation of the more than 100 reasons customers can use to file chargeback claims, contributes to the growth of this form of retail fraud, which is often conducted without penalties or repercussions. Recent estimates indicate that this type of retail fraud has surged to $65 billion annually, with analysis indicating that more than half of customers who succeed will repeat the practice.

Data and retail fraud

There are obvious direct harms from fraud, and indeed from all theft. It has been shown that the retail industry is suffering from a rise in attempted fraud through e-commerce, as it is far more economical for fraudsters to target dozens or hundreds of stores digitally than to try to pull off receipt scams.

While much of fraud has gone digital, the response is largely “analogue”. Workers are typically given expensive and time-consuming training (an investment which disappears when they leave a high-turnover industry); security cameras and RFID tags are deployed; even new techniques like facial recognition can be stymied by a thief wearing a hat or sunglasses. Merchants should look to take the fight to fraudsters where they are doing their most damage: online. The best weapon to use against would-be scammers is by gathering, analyzing and utilizing “big data” to address fraud trends, gaps in policies, and other avenues in which a company can be exploited.

Chargebacks911 has been using big data to combat and recover fraud for many years, and much of what we have developed to prevent illegitimate chargebacks is applicable to the retail space and can provide lessons on how to deal with non-chargeback retail fraud.

If your company isn’t using a chargeback remediation solution, then now is the time to start. Due to the increasing convergence between digital and physical retail, there is often a lot of digital data on transactions that can be used for machine-learning algorithms to make a decision about whether a particular chargeback claim is legitimate. Similar techniques can review the other transactions taking place in a retail chain to see if there are any patterns that might indicate fraud. Deploying a chargeback (post-transaction) remediation solution in conjunction with pre-transaction monitoring tools is key. Making use of all the data available to you, will drive better decision models, a reduction in losses, and ultimately, better experiences for your customers.

There are a number of ways in which data can enhance a retailer’s operations, and they don’t extend solely to customer experience and marketing. The way in which a company tackles fraud can be impacted greatly. Data and analytics help companies identify threats and trends, thereby better equipping retailers to deal with the modern fraud environment.

Monica Eaton is the founder and CEO of Chargebacks911 and Fi911, as well as chief information officer of Global Risk Technologies.