Holiday Spending AND Fraud Booming: Nearly 1 in 5 Transactions During The 2022 Thanksgiving Shopping Period May Have Been Fraudulent

During 2022’s five-day holiday shopping period from Thanksgiving through Cyber Monday, a record 196 million US consumers spent $35.27 billion on consumer products, up a strong 10% over 2021.

While this record spending shows continued strength in the US consumer, new data from TransUnion indicates that up to 18%, or $6.35 billion, of these transactions were potentially fraudulent: leaving consumers, retailers, and financial institutions on the hook for record breaking holiday transactional fraud losses.

The facts are startling. In the US alone, fraudulent transactions on Cyber Monday, Nov. 28th, were estimated by TransUnion to be 127% greater than any other day in 2022. Globally, fraudulent transactions on Cyber Monday were estimated to be 82% greater than any other day this year.

Cecilia Seiden, VP of retail business at TransUnion said, “The Cyber 5 is a very active time for consumers to shop, but it’s also an active time for fraudsters to take advantage and hide among the millions of transactions. What sticks out to me is how much higher the daily attempts to fraud there are during this time.”

TransUnion broke down the five-day shopping period, showing the percentage of potentially fraudulent transactions as follows:

Thanksgiving Day: 12%
Black Friday: 26%
Saturday: 22%
Sunday: 16%
Cyber Monday: 24%

Overall, nearly one in every five transactions were potentially fraudulent. Unfortunately, this record-breaking fraud may lead to record breaking fraud losses as retailers, financial institutions, and card issuers can expect a tsunami of chargeback requests well into 2023.

Unfortunately, the current securities and antifraud measures utilized by card issuers, banks, and credit unions, for both card present and card not present (CNP) online transactions with credit and debit cards have proven too little, too late.

The issue with card processing as a solution:

Whether or not transactions are completed depends on the presence of ID markers. For physical credit/debit card transactions, one such marker is the EMV chip. For CNP transactions, it may be details like the card number or the CVV/CVC code.

While the intermediary model, under which card processors operate, works on paper, it’s clearly not a complete solution to fraud. Based on the widespread availability of card data and PII on the dark web, rising fraud claims, and the recent $6.35 billion (18% of all transactions) in potentially fraudulent holiday activity, the solution only seems to work for those made aware of fraudulent activities with their accounts, then subsequently report the fraud to an institution or request chargebacks.

Its why new, cutting-edge fraud prevention measures should be adopted at card issuers and financial institutions, before losses grow worse.

A more total-solution approach to card and transactional fraud prevention:  

Both card present and CNP transactions, must leverage two technologies to better prevent fraud. The first being real-time data aggregation.

Real-time aggregation allows data from all institutions involved in a transaction to be consolidated in one place. This makes fraud detection quick, efficient, and less costly. Application programming interfaces (APIs) link the different parties involved in a transaction. The data created by APIs facilitate the data aggregation process. Upon a single transaction, API data is obtained from the card owner, banks, and the card processor.

The transaction data collected forms one data point which can be efficiently analyzed. The resulting data point is change-sensitive, meaning that any attempt to intercept a transaction could alert users of the ToolCASE fraud detection and prevention system, nearly instantly. As a result, fraudsters will have little to no margin to steal and use card data.

However, real-time analytics and data aggregation are only one part of the ToolCASE fraud prevention solution. Our fraud prevention system, powered by RembrandtAi, a continually learning, real-time operating artificial intelligence, can allow banks, credit unions and card issuers to detect a wide array of transactional frauds live, as they’re occurring; alerting fraud teams to the threat and allowing them to instantly halt a transaction for further review.

Keep in mind, RembrandtAi is not simply a “batched data” analysis tool. It analyzes millions of data points live and alerts of suspicious activity, live. Additionally, RembrandtAi can be automated, freeing up fraud teams to investigate earlier potential frauds, while automatically halting transactions of potentially new frauds, as they’re occurring.

With RembrandtAi, detection may occur far faster than fraudsters can complete an illicit transaction. With immediate detection comes immediate intervention. The speed at which our AI integrations detect discrepancies in API-generated transactional data clearly trumps that of batch analysis systems.

On top of real-time detection, our multi-level AI systems maintain a record of findings via its write-back feature. With this feature, the details of a potential fraud are stored and incorporated into a detection algorithm for future use. With ever evolving algorithms at our disposal, our AI renders future threats more predictable, ensuring even faster card fraud detection and prevention.

How ToolCASE affects card fraud:

We have a real-time interface and read the pre-authorization stream of data when the card is swiped or used CNP. Further, we have the ability to combine the pre-authorization data stream with all related financial institution account data on the card holder.

Unfortunately, card processors generally don’t recognize any deeper, encompassing data on the card holder outside of the immediate card transactions. Therefore, processor fraud decisions are made strictly on the immediate card data, and not on a massive array of data that may indicate a transaction is legitimate, or not.

The ToolCASE RembrandtAi solution has all account related information on the card holder. We combine that data and the pre-authorization data, so the level of insight is much greater.

For example, we can tell if the card holder was just in a branch or made another transaction outside of the card data that processors can see. This empowers the analysts and the AI to make more concise decisions. Far more concise and precise than the capabilities of processors.

All in all, RembrandtAi provides a multi-layer, real-time solution to card fraud prevention and detection; for both card present and CNP transactions.

Most importantly, RembrandtAi can reduce more than fraud losses, it can reduce the friction between card holders, merchants, and issuers. Potentially making fraud and subsequent chargebacks a thing of the past.

With a record-breaking number of chargeback requests likely on the horizon, and potentially billions of dollars in fraud losses already booked, your future of transactional fraud detection and prevention lies with ToolCASE’s RembrandtAi.

How much money could your institutions save by cutting its fraud losses in half?

Request a full demonstration of RembrandtAi, how it can detect and halt fraud live, how it can be automated to do so, and how your institution can better protect itself and its customers/members from fraud, HERE

Or, call 1-888-TOOLCASE to schedule a demo today.