While the world of e-commerce has many advantages, one of the most significant disadvantages of doing business online is dealing with credit card fraud. It is a drain on every merchant’s revenue, and preventing it is an ongoing battle. Cardholders are generally well protected from the costs of fraud, particularly in the United States. All they have to do is notify their bank that a purchase was not authorised, and the charge will be reversed at no cost to them unless there is clear evidence that they are lying. Unfortunately, the cost of credit card fraud must be borne by someone, and in most cases, the merchant bears the brunt of the burden.
All merchants must have effective fraud detection measures in place in order to limit the amount of revenue lost due to fraud. This usually entails using a variety of tools, ranging from basic checks on cardholder information to advanced risk scoring algorithms. Let’s look at some of the best practises and tools for detecting online credit card fraud.
What Is the Definition of Credit Card Fraud Detection?
Credit card fraud detection is the process of detecting fraudulent purchase attempts and rejecting them rather than processing the order. There are numerous tools and techniques for detecting fraud, and most merchants use a combination of several of them.
Payment cards are simple to use because they only require a few simple numbers to be transmitted to the bank in order to identify your account and authorise the transaction. Because of their simplicity, they are also vulnerable. It’s difficult to practise strict data security on a few simple numbers that must be shared with the parties with whom you’re transacting.
In the card-present environment, EMV chips have significantly reduced in-person fraud. These chips tokenize account numbers, making them less vulnerable to data theft and more difficult to counterfeit than magnetic stripe cards.
There is no technological solution comparable to the EMV chip in terms of widespread use and effectiveness in the card-not-present transaction environment of e-commerce. There are some potential solutions on the horizon, most notably Click to Pay, but unlike EMV chips, these require customer action to sign up for the service. That means there’s a significant barrier to adoption that can’t be overcome by something akin to the EMV liability shift that ensured EMV chip adoption.
For the time being, merchants must employ a wide range of tools, methods, and operational practises in order to stay ahead of fraudsters.
Credit card fraud costs the global economy over $24 billion per year, and the figures are rising. Smaller merchants bear the brunt of the impact of fraud, which is why having tools and practises in place to detect fraud in its early stages is critical.
What Is the Difference Between Identity Theft and Credit Card Fraud?
When we talk about credit card fraud, we’re referring to situations in which a payment card is used to make a purchase without the cardholder’s knowledge or consent. Instead, identity theft occurs when someone opens new credit cards in the victim’s name.
Credit card fraud can occur in a variety of ways, from a thief stealing a credit card from an unattended purse to sophisticated cyber-attacks stealing thousands of credit card numbers from merchant websites.
Identity theft, on the other hand, usually necessitates access to a person’s extensive personal information. This is frequently obtained through phishing or through a personal relationship with the victim, but malware and data breaches can also be used for identity theft in some cases.
Account takeover is a type of fraud in which a fraudster gains access to another person’s online account, such as one at a bank or an e-commerce store. Account takeover frequently results in credit card fraud because the fraudster may be able to make purchases or steal payment credentials if the account owner stored their credit card information there.
In terms of chargebacks, it’s also worth noting the specific case of “friendly fraud,” in which a customer authorises a purchase and then disputes the charge under false pretences. Friendly fraud chargebacks should always be fought by merchants. You can get them reversed with the right evidence.
Essential Tools for Detecting E-Commerce Fraud
Data security begins with your basic hardware and software. Check that the platforms you use for payment processing and storing customer data are PCI-DSS compliant, which means they are up to date with the most recent industry-standard anti-fraud security measures.
The next step is to use some of your payment processor’s basic anti-fraud tools, such as AVS and CVV verification. In order to complete a transaction, purchasers must enter the correct billing address and CVV number associated with the payment card. While some fraudsters will have access to this information, the vast majority will not.
Merchants are prohibited from storing CVV information, ensuring that fraudsters who hack into a database of customer information will not be able to easily circumvent this simple fraud detection measure.
Unfortunately, phishing has grown in popularity as a method for fraudsters to steal credit card information, as a successful attempt will provide them with the complete payment credentials.
Furthermore, third-party anti-fraud tools such as Bolt, Kount, and Sift can strengthen your defences by detecting fraud using artificial intelligence and machine learning. Merchants can also use solutions like 3-D Secure, which authenticates customers with their bank and, in some cases, requires them to complete an additional authentication step.
How Do Fraud Detection Tools Function?
Merchants can choose from a wide range of fraud detection tools, each with its own set of methods and operations. AI-driven or rules-based risk scoring and velocity checking are two examples of common capabilities.
One of the most common fraud detection methods provided by third-party tools is risk scoring. The merchant creates rules based on known indicators of fraudulent transactions, each of which assigns a positive or negative score to a transaction attempt with rules-based risk scoring. The transaction can be accepted, rejected, or marked for manual review based on the total score.
Other risk scoring tools employ machine learning to analyse previous transaction data and generate a complex set of rules. The algorithm tries to figure out which rules will result in the highest level of fraud detection with the fewest false positives, resulting in a more complicated and effective system than anything a human could devise.
Multiple transactions with one or more pieces of shared information in a short period of time are sought after by velocity checking. While it is not uncommon for a customer to forget something and place a second order shortly after the first, three or four orders in a row are often fraudulent.
What Can Merchants Do Else to Detect Fraud?
Once technological solutions are in place, merchants are left with only their knowledge, experience, and intuition to aid in the detection of fraud — but these can be powerful tools.
When the fraudster has to deal with the merchant face-to-face, it is easier to spot red flags of fraud, so brick-and-mortar merchants have an advantage here as well. However, as you become more familiar with your customers and the flow of your business, you will notice indicators and patterns that indicate fraud.
Certain products in your inventory, for example, may have a high resale value and be purchased frequently by fraudsters.
While some merchants believe they have perfected the art of detecting fraud, it never hurts to supplement with good data science. When you analyse your known true fraud transactions, the data will reveal even more indicators and patterns, confirming or disproving some of your suspicions. The results of your fraud data analysis can also be used to inform your fraud scoring thresholds.
True fraud chargebacks are the most serious and expensive type. They can’t be fought, you’re out the money for both the transaction amount and the product you shipped, and it’s often difficult to pin it down to a single vulnerability or operation error.
With the right tools, training, and experience, you’ll be able to detect subtle signs of fraudsters in the act and prevent them from doing business with you. It is a difficult task, but it is one that every merchant must undertake if they are to protect their customers and revenue from bad actors.
What Sets Off Credit Card Fraud Alerts?
Fraudsters may provide incorrect AVS information, attempt to make large purchases, or ship purchases to addresses other than the one associated with the card.
Can Card Networks Monitor Card Usage?
Yes. Card issuers can track when, where, and for what a card was used.
Is it possible for a fraudster to use a credit card simply by entering a number?
The fraudster may be able to make purchases online or over the phone if they have the card number, CVV, and expiration date.