Organizations continue to find themselves in the public spotlight reacting to a freshly discovered fraud. A key question that needs to be addressed is why they don’t see it coming, especially in a highly regulated environment with robust compliance programs.
The growing complexities of cybercriminals, state-sponsored terrorism, and threat actors are getting increasingly harder to understand, follow, and prevent. Fraud detection in today’s dynamic environment involves a complex approach to match data points with activities to find what is abnormal. Fraudsters have developed sophisticated techniques, so it’s essential to stay on top of these changing approaches of the system.
There is always some new technology to predict conventional techniques, uncover new schemes and decipher increasingly sophisticated organized fraud rings. Like other markets in technology, the fraud detection and prevention category is a crowded one too.
With different solutions to solve the fraud problem from different angles, organizations are sometimes still unable to detect frauds. The inability to detect, identify, and maybe fend off fraud earlier could be because they miss the patterns that may give it away. Quite often, the signals can be muffled as a result of data silos. Sensing and acting on them is crucial to uncovering emerging risks.
There are still a large number of businesses that attempt to tackle the fraud problem through legacy approaches. Some of them may try to detect fraud by looking for users accessing their site while infected with malicious code, for instance. Some may look for users being referred from known phishing sites. Even though these may look like legitimate techniques, they don’t actually help combat fraud.
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Why a Legacy Approach Doesn’t Work
IT leaders believe looking for phishing sites and malicious code infections may not really work. Organizations always spend a lot of time, energy, and resources fighting these issues, but they don’t actually mitigate much risk.
Many organizations adopt a signature-based approach for detecting malicious codes. This approach is quite unreliable and ineffective. A majority of malicious code still goes undetected, and even if they are caught, they are mostly false positives and don’t help much in uncovering fraud.
Rapid advances in processes and technology now offer extraordinary new avenues to enhance the sensing, analysis, and monitoring fraud threats. Organizations need to understand that separating fraudulent transactions from legitimate ones is the best way to detect and prevent fraud—the shift to behavior-based fraud strategy from signature-based needs to happen quickly. Rather than focusing on infected or phished users, the focus needs to be on unusual, abnormal behaviors, environmental factors, and transactions that do not appear legitimate.
With the help of specific and focused people within the organization, the compliance and professionals from the lines of business are crucial to capitalizing on these developments and uncovering unknown and emerging threats.
Benefits of Behavior-based Fraud Detection
In a behavior-based fraud detection method, detection and prevention are longer dependent on knowing which credentials have been compromised. It also results in fewer false positives resulting in less noise, which means less precious human cycles are consumed with dead-ends.
It also results in a higher number of true positives. This means detecting and preventing more fraud and fewer losses due to fraud, and an improved bottom line.
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Behavior-based fraud detection helps in obtaining more actionable alerts. Knowing the nature of a transaction, whether legitimate, fraudulent, or suspicious, allows an organization to take action on the transaction.
Playing whack-a-mole with phishing sites, malicious code infections, and compromised credentials does not help mitigate risks. Organizations need to focus on detecting and preventing fraud by separating fraudulent transactions from legitimate ones.
Keeping track of anomalies or suspicious activities and routinely attempting to reconnect the dots can help understand if new patterns are emerging. Proactive monitoring with advanced analytics can help identify trends and new schemes that are not based on known fraud instances.
