BNPL risk control with device signals
Reduce repeat borrowers, identity fraud, and ATO attempts while keeping approvals fast for real customers. No more fake accounts, credit abuse, account takeover, multi-accounting, and lesser payment-defaults.
Stop abuse without adding friction
Repeat borrowers and multi-accounting
Link device activity across sessions and accounts to stop repeated applications and coordinated abuse attempts. Detect patterns of misuse early to prevent fraud while allowing legitimate users to complete applications smoothly and without delays.
ATO-driven fraud
Detect risky device changes during login and account recovery flows to identify potential account takeover attempts early. Monitor device context and behavioral signals in real time to trigger stronger verification only when suspicious activity is detected.
Fast approvals without fraud spikes
Use device intelligence to reduce false positives and improve decisioning quality by adding context to every risk evaluation. Make more accurate approval and blocking decisions, ensuring genuine users are not mistakenly flagged while fraud attempts are stopped with greater confidence.
Reduce repeat borrowers, identity fraud, and ATO attempts while keeping approvals fast for real customers.
Across industries, the pattern is the same: attackers reuse devices, automate abuse, and exploit weak identity and verification layers. Deep ID adds a persistent device layer so you can link risk across events and enforce policies with lower false positives.
Start with your highest-leverage events (signup, login, OTP, checkout, incentives). Use tiered enforcement: allow trusted devices, step up suspicious sessions, and block repeat offenders. Track outcomes and iterate weekly.
Industry FAQs
Common questions about deploying device intelligence in high-risk industries.
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Talk to our team about event coverage, policies, and measurement.