The holidays are a popular time for fraud, but artificial intelligence (AI) is helping to protect customers, banks, card providers, and merchants. Detecting fraud during the holiday shopping season is challenging due to various factors. Consumers purchase things that may be unusual for them and buy from merchants they may not usually use. They are also typically making more purchases than they do in a typical month.
This makes it challenging to distinguish fraudulent transactions and identify them for consumers and banks and card providers. The capabilities of AI and machine learning (ML) enable commerce security to get ahead of fraudsters’ tricks with features that make the holiday season safer for everyone.
Fraud Detection – Helping Merchants and Banks Protect Consumers
When fraud happens, liability tends to fall to the merchant, bank, or credit card provider, depending on the payment method used. Experts have even suggested that AI tools could have prevented commercial breaches like the 2013 Target incident. This hack, which leaked over a hundred million customers’ information, occurred in the middle of December, is no coincidence.
This is a massive problem with purchases made online, often referred to as card-not-present transactions. While consumers may not be aware of it, online purchases are significantly more dangerous because someone committing fraud doesn’t need their physical card to make the transaction, only their number, and details.
The risk of fraud of this nature has become significantly higher over recent years, especially in response to the COVID-19 pandemic, which has led many people to do their holiday shopping exclusively online. Massive online sale events like Amazon Prime Day don’t help, either. To respond to the surging fraud threats, businesses and card providers have begun establishing AI and machine learning operations to boost the strength of their IT units. IT specialists can use AI to help fortify merchants and banks against dishonest card activity.
For example, merchants can use AI to scan cart activity for suspicious behavior, such as shoppers quickly making expensive purchases or using mismatched billing and shipping addresses. Businesses or card providers can also require consumers to use multifactor authentication if a large purchase is detected.
Fraud Detection – Scanning for Suspicious Credit Card Activity
Scanning for suspicious card activity is one of commerce AI’s top talents. The ability to autonomously monitor 24/7 is revolutionizing credit card security. Innovations in AI tech are especially critical for providers and cardholders since credit card fraud is the second most common type. AI can record and analyze every transaction made on a card, including some data types that come in particularly handy during the holiday season.
One pressing challenge of fraud detection during holiday shopping is that consumers’ buying habits can follow the pattern typically used to indicate fraud: buying things that seem out of the ordinary. Credit card companies use data on purchasing habits, such as favorite stores or common purchase types, as a control group to compare suspicious shopping against. Fraudsters take advantage of this during the holiday season because they know people will essentially break the rules and buy many things that diverge from their typical purchasing habits.
Credit card providers counteract this by using AI to take a closer look at the data surrounding purchases. For example, AI can be implemented to continuously analyze the IP address transactions are made from as well as the shipping address used and compare both with the cardholder’s billing address. Any deviation can signal a security notification for the cardholder to verify the transaction before the card provider clears it.
This extra measure works as a sort of loophole around typical purchasing-habit-based fraud detection. This is similar to the methodology already used by some websites to protect fraudulent login attempts with stolen passwords.
Fraud Detection – Performing Intelligent Behavioral Analysis
Fraudsters view the holidays as open season, a time of year highly concentrated with many purchases and transaction variation that is easy to exploit. Fraud detection can be just as frustrating for consumers as it is for fraudsters, though, often triggering false positives that block legitimate purchases. At the same time, card providers and banks can’t correct by relaxing their standards because the risk of fraud is simply too high.
Artificial intelligence and machine learning offer a few features that help IT departments resolve the issue. For example, it isn’t easy to compete with the behavioral analysis skills of machine learning-equipped AI.
During the holiday season, purchasing habits are different than usual but typically not to an extreme degree. For instance, while it might seem odd for a single woman with no children to buy a child’s LEGO set, machine learning could be implemented to analyze the price of the toy and determine that it is not valuable enough to be of worth to a fraudster. It is more likely that she is buying a holiday gift for nieces or nephews.
On the other hand, if that same single woman with no children were to “purchase” a $1,000 luxury men’s watch far outside her typical budget, the ML program could quickly flag the purchase as high-risk. Jewelry and luxury goods like this are among the most common fraudulent purchases due to their high resale value. The rapid data analysis capabilities of AI allow for transactions to be assessed in seconds with a high accuracy rate. This results in fewer false positives and fewer false negatives, where a fraudulent purchase is mistaken for a legitimate one.
Safer Shopping This Holiday Season
As the holiday season approaches, IT departments can help protect their organizations’ networks, data, and customers by implementing robust AI and ML systems. The complexity of AI programs has a high return on investment, offering security as adept as the fraudsters trying to dodge it. With the help of AI fraud detection and prevention, everyone can work and shop safely.