Fraud and identity risk data

Fraud and identity risk data helps businesses decide in real time whether an account opening, login or payment is likely to be fraudulent. Fintechs, banks, e-commerce merchants, marketplaces, gaming platforms and telecoms use it to stop fake accounts, synthetic identities, account takeover and payment fraud.

Typical fields

• Email signals: domain age, disposable domain, first-seen date
• Phone signals: line type, carrier, porting and SIM-swap indicators where lawful
• IP signals: proxy, VPN, hosting provider and location consistency
• Device signals: fingerprint risk and emulator detection
• Behavioral and velocity signals
• Composite risk score and reason codes

Sources and collection

Signals come from consortium data shared across clients, telecom and email infrastructure checks, IP intelligence, device SDKs and confirmed-fraud feedback. Responsible providers process personal data under a documented lawful basis such as fraud prevention, keep retention short, and return risk signals rather than selling the underlying personal data.

Delivery and pricing

Almost always delivered as a real-time API returning scores and reason codes, sometimes with batch scoring for back-testing. Pricing is per API call or per check, with volume tiers and minimum commitments.

Before you buy

• Run a retrospective test on your own labeled fraud and good traffic.
• Compare detection at a fixed false-positive rate rather than overall accuracy.
• Check latency and uptime commitments for real-time decisions.
• Ask for reason codes so you can explain declines to customers.
• Review the provider's lawful basis, data retention and regional processing options.