The online world has exploded into a marketplace, battlefield and everything in between. Fraudsters thrive on the complexity of this landscape, using a myriad of tactics to mask their identity and attack legitimate users with multiple accounts, unauthorized charges, account takeover (ATO), digital onboarding fraud, payment fraud and bonus abuse.

To spot these fraudulent patterns, businesses need sophisticated detection tools that can identify and track devices at all times. These tools should be able to work across all channels, spotting suspicious activities before they morph into chargebacks or refund scams. That’s where fraud analytics with device fingerprinting comes in.

Fraud Analytics with Device Fingerprinting: Smarter Fraud Prevention Strategies

Fraud analytics with device fingerprinting combines hardware-specific configurations and software settings to create unique identifiers for each device. This enables merchants to recognize the same device re-entering their site, even after factory resets or location changes. It also helps to identify fraudsters that may be creating duplicate accounts.

Fingerprinting analyzes attributes such as the operating system, browser version, screen resolution, installed plugins and language settings to create a digital fingerprint for each device. This is then compared with the device’s known data set to ensure it matches up. This can detect anomalies that are typical of fraudulent behavior, such as multi-accounting, ATO, and new account fraud.

The fingerprint is stored on a server-side database, making it less susceptible to manipulation from the user side and easier for merchants to access in the event of a fraud incident. It is also hashed to reduce reversibility and linkability of the data, and a salt can be added to the hash to further decrease reversibility.