Device Fingerprinting: How It Works and How Didit Uses It to Stop Fraud
Blog post from Didit
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Device fingerprinting identifies returning phones, computers, or tablets by combining browser, hardware, rendering, network, and software characteristics into stable identifiers that can persist even when users clear cookies, use incognito mode, rotate IP addresses, or reinstall apps. It is presented as a fraud-prevention tool for detecting one device used across multiple identities, including multi-accounting, promotional abuse, fraud rings, synthetic identities, money-mule onboarding, and suspicious account takeovers, while also identifying signals such as VPNs, proxies, emulators, and inconsistent device attributes. Didit’s Device & IP Analysis reportedly collects fingerprints automatically during web and mobile identity-verification sessions, combining exact persistent-ID matches, composite hashes, high-confidence recovered-device matches, and IP intelligence into configurable warnings and decisions. The service aims to reduce erroneous links by distinguishing strong matches from probabilistic recovery, applying collision safeguards for shared devices or browser pools, and scoping duplicate checks through stable user-specific vendor data. The post also notes that device identifiers may be personal data under privacy laws and says the system uses hashed, vectorized signals for fraud prevention within consented verification flows, with results available through APIs, webhooks, dashboards, and verification reports.
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