Organizations must revisit their strategies in order to better safeguard their online applications against security and fraud risks.
Organizations must first recognize that they most likely have a combination of automated traffic (bots), manual fraud (fraudsters), and legitimate customer traffic when trying to detect security breaches and fraud events within online applications.
When all three of these are combined, a lot of data is produced, mostly noise. When examining all traffic, including noise, it is very challenging to isolate, evaluate, and investigate any traffic of interest.
Organizations must therefore revisit their strategies in order to better safeguard their online applications against security and fraud risks.
Companies can employ a three-pronged strategy to more efficiently and quietly monitor their online applications for fraud and security issues:
Also Read: How CISOs can Use Threat Intelligence for Fraud Prevention
Automated traffic
Whether good or bad, bots do not represent the loyal human customers that firms seek. In some cases, majority of the traffic that an online application sees is made up of bots. As a result, eliminating all automated traffic is the first step to enhancing security and fraud monitoring. Understanding how to distinguish between the intentions and actions of humans and bots is crucial in this situation; rules and signatures are insufficient.
When automated traffic is successfully filtered out, noise and risk levels are drastically reduced, allowing the security and fraud teams to concentrate on what is left, mainly manual (human) traffic. While some of that traffic will be wanted and legitimate, some of it will be unwanted and fraudulent.
Manual fraud
Fraudsters are intelligent, resourceful, and highly motivated. They make their living by figuring out ways to take advantage of the business logic in users’ online applications to steal money from them. They learn how to blend in with trustworthy users. They alter their behavior when businesses learn how to detect them.
Again, rules and signatures are insufficient; it is essential to be able to tell apart the intentions and actions of fraudsters and trustworthy users. By doing that successfully, the majority of fraud can be filtered out and blocked. As a result, fraud losses are drastically decreased, and the amount of noise that obscures visibility is also greatly reduced.
Reduce friction
Organizations achieve another possibility when they can reliably filter out fraudulent and unwanted automation. The traffic organizations want can also be reliably identified if they can reliably identify the traffic they don’t want. If security teams can accomplish that, they can stop adding friction to the user experience for their known-to-be-reliable users.
In other words, why bother them with friction like MFA challenges or anything else if security teams can reliably determine that a given user is both human and a legitimate user? When they can do so without burdening the user, the conventional wisdom that adding those friction points is necessary to thwart fraud and security breaches falls apart.
When it comes to lowering friction in the user experience, the ability to accurately identify unwanted traffic – whether bot or fraud – opens up an entirely new world of possibilities. This reduces another risk that is frequently disregarded: the risk of lost revenue as a result of users quitting the application.
Also Read: Strategies to Strengthen the Operational Technology (OT) Cybersecurity Posture
For security and fraud teams, recent improvements in the ability to accurately detect automation (bots) and fraud have created new opportunities. Enterprises can reduce the noise obscuring their visibility into their online applications by learning how to recognize, isolate, and remove unwanted bot and fraud traffic.
This then enables those businesses to concentrate on strengthening the security of their online applications and improving the user experience for their legitimate customers.
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