As e-commerce spreads globally, so does the threat of fraud against online merchants. Companies lose billions annually due to fraudulent transactions, but more importantly, they lose trust and credibility with their customers. Many online merchants are deploying anti-fraud tools to deal with this issue. But how does e-commerce fraud prevention software work? Let’s go find out!
How Does E-commerce Fraud Prevention Software Work?
Behavioral Analysis
Behavioral analysis is utilized by anti-fraud software for online transactions to identify actions indicative of fraudulent intent. Information such as the time of day, the location, and the number of unsuccessful login attempts can be used for this purpose. The software can flag the transaction as possibly fraudulent and prevent it from being executed if it detects suspicious behavior.
If the software notices many failed login attempts, there may be an attempt to break into a user’s account. Similarly, the software may flag a transaction as suspicious if it is done at an unexpected time or from a location that is inconsistent with the user’s typical activity.
IP Geolocation
The software may ascertain the legitimacy of a transaction by comparing the user’s location with that of the transaction. For instance, if a transaction is made from a country with a reputation for high e-commerce fraud rates, the software may identify the transaction as suspicious.
Similarly, a transaction may be suspicious if the user’s IP address is in a different nation than the shipping location. Furthermore, the tool may check a user’s IP address to see if they hide their actual place behind a proxy or VPN.
Device Fingerprinting
E-commerce fraud prevention software may also employ a device fingerprinting technique. This requires analyzing the user’s device to generate a distinctive identification that may be used to monitor their actions.
The software generates a device-specific fingerprint by inspecting the device’s hardware, operating system, and browser configuration. The software can flag the transaction as suspicious if it detects changes to the device’s fingerprint.
When a person routinely pays with one device but suddenly pays with another, it may be a sign of fraud if the user has recently changed devices. A similar scenario would occur if the user were making the transaction from a high-risk device, such as one linked to fraudulent behavior in the past.
Machine Learning
Machine learning algorithms can analyze historical data to determine if a given transaction is likely fraudulent. The software’s ability to detect fraudulent activity improves as it handles more transactions.
Payment Verification
During the checkout process, the payment information you enter will be checked by anti-fraud software. This involves making sure the credit card or other payment mechanism is legitimate. Invalid payment information or information that does not match the user’s billing address can trigger a fraud alert in some systems.
The software can also detect fraudulent activity if a user enters a credit card number reported as stolen or compromised. Similarly, if the billing address entered does not match the one connected with the credit card, this could be a sign of fraud.
What Features Should You Look for in E-commerce Fraud Prevention Software?
Real-Time Monitoring
Real-time monitoring is an integral part of any e-commerce fraud protection software. It must be able to track transactions in real time and indicate any irregularities before they are finalized. The earlier fraudulent acts are stopped, the less damage they can do to the company.
Customizable Rules
Every company has its own requirements and level of comfort with risk. Businesses need to be able to establish their own fraud detection rules and thresholds within the program’s framework.
For instance, companies should be able to establish policies that identify which transactions call for extra verification and on what basis (transaction amount, location, etc.).
Multi-Layered Verification
Multi-factor authentication, including IP address analysis, device fingerprinting, and user behavior analysis, is essential for e-commerce fraud protection software. These approaches contribute to offering a deeper understanding of the transaction while decreasing the number of false positives.
Chargeback Prevention
A chargeback can have a devastating effect on a company’s bottom line and good name. Because of this, mechanisms for automatically refunding customers or mediating disputes should be included in the e-commerce fraud prevention software. This helps to prevent losses and increases credibility with clients.
Cost-Effectiveness
A good return on investment is expected from the fraud prevention software used in online stores. Businesses should search for a software provider that can provide them with multiple price models, such as transaction-based or subscription-based models. This gives them the flexibility to select a pricing category that best meets their needs.
Conclusion
Understanding this software’s functioning helps organizations protect themselves and their customers against financial loss and reputational damage. E-commerce fraud prevention software is anticipated to become more advanced and efficient as the industry develops.
