Device fingerprint API for fraud prevention reliability wanes and privacy controls continue to evolve, fingerprinting is an increasingly valuable tool for fraud prevention. The technique establishes a unique identifier for each device or client in real-time that remains consistent over time, and can be used to identify multiple accounts being logged in from the same physical or virtual device.

Device fingerprinting works by tracking a series of data points on the device or browser during each session, such as hardware specifications (screen resolution, GPU, device make and model), software details (browser type, installed fonts and plugins), network information (IP address, time zone) and more. These attributes are run through algorithms to produce a compact and consistent profile, or fingerprint, that can be used to recognize the device across sessions. The fingerprint is stored in a merchant accessible database, making it difficult for end-users to manipulate.

Developer Guide for Fraud Prevention APIs: Secure Your Platform

The fingerprint can be used in combination with other techniques, such as behavioral profiling, feature aggregation and risk scoring to highlight motivated fraudulent activity. However, a strong and robust fingerprint alone is not enough to indicate fraud, which is why we recommend implementing additional verification methods for high-risk transactions.

There are a number of open-source and commercial device fingerprinting solutions available for developers to choose from. Commercial solutions are typically more reliable and well-maintained, and offer advanced capabilities such as machine learning, network effects and risk scoring to support a holistic fraud prevention system. They also offer dedicated customer service and regular updates, which can be important as privacy controls evolve and technical advancements impact fingerprinting effectiveness.