Fraud and abuse
Accounts and promotions exploited at scale by those who know the flow's loopholes.
Trust layer • Trust Decision
Risk, continuity and trust. Not a yes or no at login.
Sonarprint observes every interaction and returns a continuous, explainable Trust Decision, with the recommended action for your risk team: allow, challenge or block. All over a collaborative network, with privacy by design.
The problem
Large apps live the same dilemma.
Raising security without breaking the experience for the good user.
Account takeover
Illegitimate access right after a credential leaks or is shared.
False positives
Anti-fraud that's too aggressive blocks the legitimate user and drives support costs.
Too much friction
Asking for verification on every action wears the user out and drops conversion.
The insight
Proximity and behavior are hard to forge at scale.
Patterns of proximity and behavior carry an asymmetry in our favor: they're cheap to observe and extremely expensive to forge in volume. That's what lets us enrich decisions, reduce false positives and act without asking anything of the user.
- Enriches every decision with context from the physical world.
- Reduces false positives about the good user.
- Acts passively, with no user interaction.
The trust layer
The pillars of the Trust Decision.
DeviceKey, in-app identity and context signals combine into a single decision: continuous, explainable and adjustable by policy. Behind each pillar, the layer evaluates countless signals.
DeviceKey: the device's identity
A unique, stable identity that the app creates for each device, independent of who is logged in. It survives logout, reinstallation and SIM swap, without exposing sensitive device identifiers or personal data.
Location signals
Daytime and nighttime address, presence of nearby devices and impossible travel. Everything organized by region, never as an exact coordinate.
In-app identity
An anonymous code for the already-authenticated user, which the partner sends and we link to the DeviceKey to enrich the analysis, without revealing who they are.
Trust Decision
The final decision — allow, challenge or block — continuous and explainable, with risk alerts and the signals that back it.
How Sonarprint arrives at the Trust Decision
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01
The app senses the surrounding context
Proximity, possession and device-environment signals, read lightly and without weighing down the device.
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02
The network confirms presence
It cross-references trusted proximity points and organizes context by region, without using exact location.
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03
Behavior and routine
Daytime and nighttime address, the consistency of habits and routine anomalies become signals for each device.
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04
An explainable decision
The result is the Trust Decision: allow, challenge or block that interaction.
How the layer decides
It allows, challenges or blocks, always with evidence.
The Sonarprint layer fits into your flows without requiring any structural change. It follows the context, assesses the risk and guides the access decision. It doesn't replace your MFA: it avoids triggering it when trust is high and reinforces it exactly when a risk signal appears. Fewer challenges for the good user, more of a barrier for the rest.
Allow
Known device, recognized user and location consistent with the routine. The flow proceeds with no friction.
Challenge
Ambiguous signals, such as a new device, travel or something out of the routine. The action is routed to the partner's own MFA.
Block
An already-blocked device, an identity used in many places or a clear fraud pattern. The action is refused and recorded.
Record
Every decision is recorded (device, identity, signals and action), ready for auditing in the partner's systems.
The trust API
Simple to integrate, easy to explain.
A fast API returns a continuous Trust Decision and the signals that back it. Instead of a black box, your risk team gets enough explainability to audit and adjust policies.
Simple, fast API
One call per decision, with a response in milliseconds.
Continuous Trust Decision
Allow, challenge or block, recalculated on every relevant interaction.
Post-processed signals
Daytime and nighttime address, routine stability and region-level patterns.
Explainable for risk
Each decision comes with the factors that weighed most and the applied policy.
Example of a decision event
{
"device_key": "stable device identity",
"user_ref": "anonymous user code",
"flow": "login | payment | signup",
"trust_decision": "allow | challenge | block",
"signals": ["night address", "co-location", "routine deviation"],
"policy_id": "applied policy version",
"timestamp": "server time"
}Why Sonarprint
A moat that can't be copied with budget.
Collaborative network
A collaborative network of signals that can't be recreated from scratch.
Hard-to-replicate signals
Proximity and physical context can't be forged at scale like a credential.
Behavioral history
The more the network observes, the more accurate the decision gets, device by device.
Privacy as an advantage
With no personal data and no exact location, integrating the layer creates no new regulatory risk.
What we measure with you
Results that show up in the panel.
Reduction in fraud and abuseReduction in false positivesIncrease in approval and conversionIntegration timeVolume expansion per customer
Ready to become the invisible infrastructure behind every sensitive decision?
Let's design a pilot in your environment and measure the impact on fraud, false positives and conversion.