Is Behavioral Analysis Effective For Mobile?

January 6, 2016

As mobile device usage grows rapidly, businesses need to adapt to this changing commerce environment, and not just by giving customers more m-commerce options. Security is a big concern because where customers go, fraudsters follow. Not only is mobile fraud more likely than online fraud, businesses lose more on average compared to product price than other shopping avenues.

One problem is the majority of businesses use outdated fraud prevention and detection methods. Many of the common fraud detection methods in use are sufficient to stop fraud via desktop. When adapted to mobile devices, though, they fall short.


In a recent article, we looked at the origins of behavioral analysis and how it works. We discussed why behavioral analysis is an extremely useful fraud prevention tool that can reduce user friction and adapt to changing fraud methods. Behavioral analysis also allows for a lower false positive rate, so good customers aren’t locked out of a sale. This makes it an important piece of the fraud fighting puzzle.

Businesses must integrate new fraud prevention methods like behavioral analysis to stay one step ahead of hackers. If not, the rapidly rising use of mobile devices might equate to fraud disaster for businesses.

Considerations when Choosing Mobile Fraud Detection Tools

There are several variables for businesses to consider when looking for new fraud security methods specifically for mobile devices.

Here are some unique points of consideration for mobile fraud security:

  • Effectiveness across device types

Although smartphones and tablets are both considered mobile devices, they aren’t identical. This can overwhelm businesses looking for an effective mobile security solution.

kaboompics.com_Typing on the tablet

One difference between the two devices is usage behavior. A user may not use both devices equally. For example, a person may use a smartphone for banking, but choose to shop on a tablet. This means data about when a user to tends to shop, how much they tend to purchase, etc. can be different for different devices. Thus this sort of transactional behavior isn’t enough.

For fraud detection to be successful across mobile devices, all devices need to gather separate data that gives a clear picture of how a user interacts with each device. Businesses must choose fraud security methods that allow for detection across all mobile device types. Other types of behavioral analysis that analyze physical interaction of a user with a device is well suited to work across mobile devices.

  • Effectiveness across mobile operating systems

An effective fraud detection method must be successful on every operating system, whether it’s Android, Apple, or Windows. A user with an iPad should be as secure as a user with an Android phone. If not, only certain users will reap the benefits of fraud security, while others will remain exposed to attacks.

By using a quality inherent in the user, such as physical behavior, new fraud detection methods like behavioral analysis have the ability to transcend differences in device operating systems.


  • Mobile browser versus mobile app

Another point to remember is mobile users use both apps and web browsers to shop online, make payments, etc.

The two are not equal, though. Mobile applications can be developed with more security compared to mobile browsers. Specifically, developers can code security features right into the app. This means apps can gather more data for fraud detection.

The same is not true for web browsers, which many mobile users use because they don’t have to worry about downloading or updating apps. These are more universal and cannot be tailored by individual developers.


While apps may allow for more built-in security, many developers don’t take advantage of this. App developers tend to focus more on user experience than security. Because most security measures lessen user experience, app developers tend to leave them out in favor of a low-friction experience. Thus there are many apps out there that offer cool features, but have security holes fraudsters can weasel their way into.

Businesses can strengthen their applications by adding behavioral analysis measures that work both in apps and in browsers while keeping user friction low.

  • Effectiveness across business types

In addition to spanning multiple devices and operating systems, fraud detection should be able to adapt to any industry, whether it is a shopping app, online store, or bank. In these examples, behavioral analysis can be used to protect different types of mobile traffic.

  • Concerns about new software/hardware

A business might be turned away from new fraud detection methods because they are under the idea they will have to integrate expensive software or hardware. This might be true for static biometric methods like fingerprint scanners, but behavioral analysis is fairly easy and light to implement. Touchscreens are already equipped with sensors able to gather data that can give insight into user behavior.


Final Thoughts on Implementing Mobile Behavioral Analysis

With all of these considerations, businesses have a lot to think about when looking into new mobile security measures. In addition, there are many businesses selling many different solutions. It can be hard to determine which solution is best.

Businesses looking for mobile fraud security solutions must balance user friction with effective security. The method should be easy for businesses to implement, without requiring bulky hardware or extensive work on the user’s side. An effective solution will also result in fewer false positives.

Behavioral analysis is an important emerging fraud prevention method able to overcome many common concerns specific to mobile devices in addition to reducing friction and false positives. It uses multiple data points to get a clear picture of whether the person using a device is real or a fraudster. This builds a complete user profile effective at stopping fraudsters while allowing true users to continue their activity.

Businesses should integrate various methods, including new strategies like behavioral analysis, to catch as many fraud schemes as possible. Fraud is evolving and fraudsters won’t wait for businesses to catch up.


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