Features / Trust Score
Feature

AI Interview Integrity & Trust Score — Proctoring for Remote Screening

Add integrity signals to every AI interview. Trust Score detects tab-switching, copy-paste, inconsistent response patterns, and suspicious behavior — so your team can review interview authenticity alongside candidate quality. Included free with every interview.

Overview

Trust Score is InterviewFlowAI's built-in interview integrity layer. During every AI-led phone or video interview, the platform monitors for behavior signals that suggest the candidate may not be responding authentically: tab-switching to search for answers, copy-paste into the response field, unusual response timing patterns, inconsistent answers across related questions, and other integrity indicators. These signals are aggregated into a Trust Score that sits alongside the candidate's competency scorecard — not as a pass/fail judgment, but as context that helps recruiters decide whether an interview warrants closer review. Trust Score is included free with every interview, making proctoring accessible at any screening volume.

Why teams use this

  • Detect tab-switching and browser focus loss during interviews
  • Flag copy-paste behavior and unusually fast or slow response patterns
  • Identify inconsistent answers across related questions
  • Review trust signals alongside competency scores — not as a standalone gate
  • Included free with every interview at no additional cost

Remote hiring needs integrity signals, not just competency scores

Remote interviewing solved the scheduling problem but created a new one: how do you know the person answering your questions is actually the person you're hiring — and that they're answering without external help? In live interviews, eye contact, hesitation patterns, and environmental cues give interviewers some signal. In asynchronous AI interviews, those signals disappear unless the platform actively monitors for them.

Trust Score fills that gap. It's not a lie detector — it's a behavior monitoring layer that surfaces signals your team can use to decide which interviews need a closer look. A candidate who never switches tabs and answers consistently across related questions? High trust. A candidate who tabs out before every technical answer and whose responses don't align? That interview gets flagged for recruiter review.

What Trust Score monitors and what it means

Tab and window focus tracking

The platform detects when a candidate leaves the interview window — to search for answers, reference notes, or receive external help — and how frequently it happens.

Copy-paste detection

Responses that appear to be pasted rather than typed naturally are flagged. Unusually fast typing speeds or perfect formatting from a candidate who otherwise types slowly are surfaced.

Response pattern analysis

Consistently fast responses to complex questions, unusually slow responses to simple ones, or identical timing patterns across questions can indicate prepared scripts or external assistance.

Cross-question consistency checks

When a candidate claims 5 years of Python experience but can't answer a basic Python follow-up, or gives contradictory information across related questions, the inconsistency is surfaced.

How to use Trust Score without over-relying on it

Trust Score is a decision-support tool, not an automated rejection system. The strongest teams use it as one data point among many — flagging low-trust interviews for human review rather than auto-rejecting candidates based on a score alone.

  • Use Trust Score as a review prioritization signal — review flagged interviews more carefully, not automatically reject them.
  • Consider context: a candidate interviewing from a noisy coffee shop may trigger different patterns than one in a quiet home office.
  • Combine Trust Score with competency scores: a candidate with strong answers AND high trust is a stronger signal than either alone.
  • Look for patterns across your candidate pool — if many candidates trigger the same flag, your question format may need adjustment.
  • Use Trust Score data to improve your interview design — questions that consistently trigger copy-paste may need to be reworked for originality.

Trust Score vs. traditional proctoring solutions

ApproachTraditional proctoringInterviewFlowAI Trust Score
Cost modelPer-exam or per-candidate fees. Expensive at scale.Included free with every interview. No per-use cost regardless of volume.
Candidate experienceIntrusive. Webcam monitoring, locked browsers, room scans. Feels accusatory.Background monitoring. Candidates focus on the interview. Integrity signals surface in review.
Review workflowProctors review flagged sessions. Added time and cost.Trust signals appear alongside competency scores. Recruiters review in the same dashboard.
Decision roleOften used as a pass/fail gate. Candidates can be auto-rejected.Decision-support tool. Highlights interviews for human review. Humans make the call.

Recommended Trust Score workflow

  1. Enable Trust Score for your interview workflow

    Trust Score is on by default. Review the monitoring settings and adjust sensitivity based on your role's integrity requirements.

  2. Review trust signals alongside competency scores

    In the candidate dashboard, Trust Score appears next to interview scores. Sort or filter to identify interviews that warrant closer review.

  3. Investigate flagged interviews, not auto-reject

    Watch the recording, read the transcript, and compare cross-question consistency. Make a human judgment about whether the interview reflects genuine candidate ability.

  4. Use trust patterns to improve your process

    If certain questions consistently trigger flags, redesign them. If certain candidate sources produce lower trust scores, adjust sourcing or screening instructions.

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