Businesses face ever-growing threats from fraudsters seeking to exploit vulnerabilities and compromise financial stability. To effectively combat fraud and protect your online enterprise, you need advanced fraud detection and monitoring solutions.
At IPS, we’ve worked with state-of-the-art technologies and tools to identify suspicious activities and patterns, ensuring our clients remain one step ahead of potential fraudsters. Here are some common focus areas and why they matter. These strategies can make or break your platform even though they may seem simple.
The Art in Address Matching or Mismatching
Address matching is a crucial element of fraud detection, but it’s not as straightforward as it might seem. Mismatches in billing and shipping addresses are common, and not all address discrepancies signal fraud. However, a fraudster won’t typically ship a stolen item to the cardholder’s address, making shipping mismatches a red flag. Yet, making the right call often requires more than automated algorithms; it demands human intelligence. There could be an identifiable reason for that address mismatch or address swap. Further analysis is needed to “connect the dots.”
Building the Foundation
Who are the good guys and who are the bad guys? This matters right now. And it absolutely matters in the past. Maintaining white and block lists is fundamental to any effective fraud prevention strategy. Whitelists ensure that known good customers face minimal friction by whitelisting their information, allowing them to complete transactions without unnecessary hurdles. Conversely, block lists prevent fraudsters from returning with stolen payment credentials, effectively thwarting repeat attempts.
However, failing to regularly update or maintain these lists can lead to missed opportunities to detect account takeovers and other fraudulent activities. The key is striking the right balance between security and customer experience.
Unmasking Suspicious Activity
The information gathered from device activity, IP addresses, and browser headers can be invaluable in fraud detection. By analyzing device patterns, travel distances, and language preferences in operating systems, browsers and apps, businesses can paint a comprehensive picture of user behavior. This data is a potent tool in identifying suspicious activities and confirming the legitimacy of transactions.
Yet, relying solely on these data points has limitations. Fraud patterns are often more complex and nuanced than what can be deduced from a few device-related attributes. Human intelligence provides the edge that brings context and a deeper understanding to these data points by leveraging additional data and foundational knowledge.
The Power of Historical Data
Leveraging customer history and Know Your Customer (KYC) information can be essential for distinguishing between good customers and fraudsters. While identifying fraud at the account sign-up stage can be challenging, proactive investigations can still uncover patterns in data that signify fraudulent behavior, especially when dealing with large-scale account creation attempts by the bad guys.
For established accounts, KYC tactics become paramount. Sudden changes to consistent user behavior, payment instruments, and purchase patterns can be telltale signs of account takeovers. However, changes in customer behavior are not always indicative of fraud and require careful consideration.
Putting the Brakes on Massive Fraud Losses
Velocity limits serve as important stopgaps to prevent massive fraud losses. Configured based on an understanding of normal customer purchase activity, these limits help identify abnormal transaction patterns. However, improperly configured velocity limits can inadvertently hinder legitimate high-value transactions, underscoring the need for continuous monitoring and adjustment.
The Engine of Efficiency
Automation is the engine driving the efficiency of fraud detection and response these days. It streamlines processes, reduces manual intervention, and allows for rapid responses to emerging threats or customer needs. However, excessive reliance on automation can be risky, as fraud tactics constantly evolve. A balanced approach that combines automation with human expertise, as exemplified by IPS, is key to staying ahead of fraudsters.
Orchestrating Effective Response in Your Systems
Effective decision flow design is critical to responding to identified fraud. It ensures that when a transaction is flagged as fraudulent, a series of actions are triggered, such as adding data to block lists, notifying the “customer” and/or card holder, and initiating investigations. Misconfigurations in decision flows can result in missed opportunities or unnecessary friction for genuine customers.
Striking the Right Balance
False positives are an inevitable part of fraud detection, whether AI or human-driven. To minimize their impact, a robust quality and accuracy retraining program is essential. Swift adaptation and open communication between the fraud detection team and the engineering team are needed. Your fraud team should also have open communication lines with customer service teams. A good solution involves these entities working in synchronicity whenever possible.
Furthermore, strategies to filter out fraudsters employing social engineering tactics include training customer service teams and learning from previous exploit attempts. Turning false positives into positive customer experiences requires providing customers with clear reasons for transaction rejections and continually refining your notification processes.
Although the above topics are only the tip of the iceberg when it comes to focus areas for a merchant to hone in on, they’re great examples of how IPS has learned to deploy effective strategies and systems over the years. We specialize in fraud detection systems that evolve when needed, that are effective and efficient, and that give our clients an edge over the bad guys plaguing their systems with fraud.
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