For almost a decade, online fraud detection has been performed by tracking user behavior with the help of cookies. However, this technology has lost its effectiveness as users have become accustomed to blocking and deleting cookies as their default preference in recent years. The effectiveness of the result generated by cookies-based fraud detection can not be trusted since it does not reveal the whole picture. 

This pushed the digital organization to look for alternatives to cookies in fraud detection. A technology that is not controlled by users (or potential fraudsters) and gives digital platforms the freedom to accurately identify devices. The BEST alternative to cookies in online fraud detection came up to be Device Fingerprinting. 

What is Device Fingerprinting Technology?

Quite similar to a human fingerprint, device fingerprinting technology creates a single identifier (or a unique ID) for each device that accesses an online platform using various attributes.  The basic attributes that are collected to create this device fingerprinting include basic browser settings, operating system details, and hardware configurations when combined into an identifier ensure that there’s enough entropy that the identifier is unique to each device. These details are collected for the sole purpose of device identification which when combined proves efficient in identifying and distinguishing one device from another.

Due to its effectiveness in device identification, this technology can be further used to detect and block fraudulent actors from digital platforms. Here it is how:

What is the Role of Device Fingerprinting Techniques in Fraud Prevention?

The major role of device fingerprinting in fraud detection is to identify & stop fraudsters by determining the level of risk at any point in the customer journey. In other words, device fingerprinting is the cornerstone of modern fraud detection that protects digital platforms from all forms of fraud.

Device fingerprinting technology provides the risk management team with enough details on all the potentially risky devices associated with their platform so that they can further examine whether to block them or whether any further actions need to be taken. 

 

There are three key indicators that a device fingerprinting solution should provide.

1. Device ID: A unique alphanumeric string assigned by a fraud prevention vendor to identify a device, remaining the same even if a fraudster attempts to mask their device or reset it.
2. Risk Indicators: A detailed list of all the tools and techniques associated with fraud, such as app cloners, GPS spoofers, emulators, VPNs, and signs of tampering or jailbreaking, which flag devices as potentially risky.
3. Risk Score: A numerical value reflecting the risk level of a device, based on factors like fraud-associated tools, frequency of suspicious activity, and the device's link to multiple accounts.

In the below image you can see an example of key indicators in a device fingerprinting-based fraud detection solution: 

Image Source: SHIELD.

Now coming to the 6 major roles of device fingerprinting techniques in fraud detection on online platforms:

1. Unique Device Identification: Create a unique identifier for each device
2. Behavioral Analysis: Analyze user behavior patterns and detect anomalies 
3. Real-Time Fraud Detection: Provide real-time identification of suspicious devices
4. Cross-Device Activity Identification: Identify user activity across multiple devices
5. Adaptive Security Measures: Adapt to new fraud trends based on the device’s history and behavior. 
6. Reduce False Positives: Separate good users from fraudsters efficiently.

10 Applications of Device Fingerprint-Based Fraud Detection:

Conclusion:

Device fingerprinting is the now and the future of online fraud detection due to its effectiveness in identifying online threats and keeping businesses vigilant against all forms of fraud.