Risk Engine & Anomaly Detection (Without Surveillance)
Traditional fraud prevention = “track everything, store everything, model everything”.
Omnera’s risk engine is built around a different idea:
See enough to detect abuse. See as little as possible about normal users.
Concretely:
We focus on patterns, not personas – spikes in velocity, repeated declines, weird usage combinations, clearly automated behavior at an aggregate level.
We rely on ephemeral, minimized signals – many signals used for risk decisions do not need to become permanent, user-level logs.
We prefer limits + friction over deep profiling – when behavior looks risky, adding friction (throttling, temporary caps, extra checks) is often enough, without needing to fully deanonymize someone.
When we say “no trail”, it means:
no behavioral monetization,
no long-lived profile graphs,
no exploitation of user data as a secondary business model.
It does not mean “no risk controls at all”.
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