The screening and risk layer built for fintechs.

Screening runs in real time inside the onboarding flow, then only edge cases route to a reviewer, so risk-based onboarding stays fast while agentic entity resolution is designed to cut false positives by up to 80%. Fintechs face a specific tension that most other industries feel less acutely: customers expect instant approval, but every approval still has to satisfy real AML obligations, and noisy, undifferentiated screening applied to every applicant slows good customers down without necessarily catching more real risk than a properly risk-based approach would. Resolving that tension is less about choosing speed over controls, or the reverse, and more about applying controls precisely, escalating only the applications that actually carry risk signals worth a human reviewer attention, while approving the rest automatically with the evidence behind that decision still attached and auditable.

Yes. Sanctions, PEP and adverse-media screening runs across the major regimes, including OFAC, Canada, the EU, the UK, Australia and APAC jurisdictions, which covers the global, cross-border user base most fintechs onboard by design, since the addressable market of a fintech rarely maps neatly to the sanctions regime of a single jurisdiction. Cross-border exposure creates a specific risk that domestic-only screening coverage would miss: a customer clean against the list of one country can carry direct exposure on another, and a fintech serving users across many jurisdictions needs screening that reflects that breadth rather than the narrower coverage a single-market compliance program might have historically relied on. The same entity-resolution engine that reduces false positives domestically applies across this broader list coverage too, so expanding into new markets does not multiply the noise a compliance team has to manage in proportion to the new lists being screened against.

Yes. Screening profiles, thresholds, suppression rules and routing are configurable by the compliance team directly, so a rule change reflects a compliance decision rather than a ticket in an engineering backlog. Engineering capacity at a fintech is usually concentrated on the product roadmap, and compliance requests that require code changes tend to queue behind revenue work, which in practice means the screening configuration drifts out of step with the documented risk-based approach. Keeping configuration with the compliance team closes that gap: when a segment turns out to generate persistent, explainable false positives, a targeted suppression rule can be applied and documented the same day, and when risk appetite tightens, thresholds move with it. Every configuration change still produces explainable output with the matching and conflicting evidence attached, so tuning the system never undermines the defensibility of the decisions it produces.