How imper.ai Evaluates Risk and Makes Decisions

imper.ai evaluates identity risk in real time by correlating hundreds of contextual signals across device, network, behavior, and usage patterns. This article explains how those signals are translated into decisions during live interactions.

In this article

• Risk signals and context

• Real-Time Risk Score

• Policy thresholds and decisions

• Continuous Evaluation Model

Risk signals and context

imper.ai continuously ingests signals associated with identity lifecycle events and protected workflows.

• Network and location characteristics

• Endpoint and device attributes

• Behavioral and usage patterns

Signals are contextual and weighted. No single signal independently determines an allow or deny decision. All signals contribute to a composite evaluation.

Real-Time Risk Score

All observed signals are correlated to generate a Real-Time Risk Score. This score represents the overall likelihood that an interaction involves:

• Workforce impersonation

• Account takeover attempt

• Unauthorized operator activity

• Automated abuse

A single critical signal (for example, a known malicious device fingerprint) may significantly raise the score, but decisions are based on the composite score, not individual flags.

Risk scoring operates at:

• Interaction start

• Configured workflow triggers

• Continuous monitoring intervals (if enabled)

Policy thresholds and decisions

imper.ai decisions are policy-driven. Administrators define thresholds that map risk scores to outcomes.

Example policies include:

• Allow interaction when risk score is below a defined threshold

• Require additional verification when risk score is elevated

• Block or terminate interactions when risk score exceeds a critical threshold

This approach ensures that blocking behavior is consistent, explainable, and configurable.

Continuous Evaluation Model

imper.ai operates in a proactive verification model.

For protected workflows:

1. Risk is evaluated at workflow initiation.

2. Risk can be re-evaluated during the session if additional signals change posture.

3. Enforcement can escalate if risk increases.

Every supported workflow begins with verification and risk evaluation, rather than waiting for a suspicious event to occur.