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Enterprises, no matter what industry they are in, all have one thing in common: none of them want to wake up one morning and find their company on the front header of every news outlet as the victim of another cyber security breach or fraud case.
Cybercrimes cost the global economy more than $450 billion in 2016, and as of Q1 of 2017, 53% of companies surveyed were still categorized as ill-prepared to handle a cyberattack.
As companies continually integrate innovation into their ecosystem, the potential damage fraud can cause grows. The result is an increased need for enterprises to simultaneously improve their product and service, as well as their ability to handle fraud and cybercrimes.
Looking at Abnormalities
In order to ensure that they are constantly working hard to prevent cybercrimes, enterprises need to implement innovation that routinely improves it’s ability to detect, alert and prevent potential fraud.
One of the best ways to do so is by detecting anomalies in digital behavior. When observable events in an enterprise’s ecosystem do not conform to expected events, or when there is a pattern that deviates from the norm, there is an increased risk for a breach.
While it is difficult to monitor anomalies and outliers in an enterprise’s security system manually, the use of machine learning techniques and smart data mining technology can help identify anomalies before they become full breaches.
Abnormalities at the Entry Level
The first step in preventing a breach is at the intrusion, or entry level. Intrusion detection is a common attribute of many fraud prevention innovations and focuses on the preemptive detection of intrusive behavior on an enterprise’s ecosystem.
When hackers attempt to penetrate an enterprise’s ecosystem, if they do not have prior knowledge of the security systems in place, it is safe to assume that their behavior will be erratic and differ significantly from the behavior authorized users have. Security systems equipped with machine learning capabilities are able to identify and alert IT systems about anomalies once they happen at the entry level.
Many ecosystems have entry point security systems and reduce cyberwalls once entry has been granted. This makes entry level anomaly detection the most critical for enterprises to focus on. By detecting anomalies at this early stage, enterprises are able to immediately receive alerts of potentially suspicious behavior and actively thwart off potential intruders who would cause fraudulent activities before they even gained entry.
How Enterprises Can Easily Detect Anomalies
Today, there are many data analysis techniques to prevent fraud and intrusion utilizing machine learning, AI, data mining and more for enterprises looking to implement anomaly detection tools in their ecosystem.
One way is by integrating with a third-party provider who offers such fraud detection tools for a one-time or monthly fee. While many of these fraud detection tools are available, they often require a great deal of integration and upkeep to maintain.
The alternative is developing a proprietary anomaly detection and fraud prevention solution that will be custom-designed to suit the specific enterprise’s needs. Development of such a tool might have once been perceived as costly and time consuming, especially if it is a deviation from the traditional activities of the enterprise. Today, however, there are many solutions in place that simplify this process and reduce the time and cost necessary. The most beneficial route to such innovation is running a proof-of-concept with young, innovative and eager-to-succeed startups.
How Proofs-of-Concept Are the Best Way To Innovation in Fraud Prevention
A major value of running a PoC with startups to build a fraud prevention and detection system is that the technologies can be tested based on the exact needs of the enterprise and work within the limitations of their infrastructure without requiring an overhaul of their existing system.
Enterprises that run PoCs on prooV are able to test multiple startup solutions in parallel until they find the right technology to fit their needs. On prooV, enterprises in all industries can open proofs-of-concept with new and cutting edge technologies and easily test the new solutions without impacting their own ecosystem.
