Overview

A completed Begini assessment produces structured outputs you can use directly in your decisioning workflow. Results are available in Beacon or delivered in real time via webhooks.

The outputs

Risk score

The primary output. Represents the relative risk level of the user based on their behavioural patterns. Lower scores indicate more favourable patterns; higher scores indicate higher-risk signals. Use it to rank, segment, and apply approval thresholds across your applicant pool — not as a standalone pass/fail value in isolation.

Trait indicators

Component-level behavioural scores that explain the overall risk score. These show how the user performed across different behavioural dimensions during the assessment and are included in the webhook payload under calculated.traits.

Trust / confidence score

A reliability indicator for the session. Tells you how much confidence to place in the result. A low trust score does not mean the user is high risk — it means the behavioural data for that session is less reliable and should be reviewed before being used for decisioning. See Fraud Detection & Trust Score for detail.

Session metadata

Timestamps, completion status, platform, and session identifiers. Used for operational tracking, debugging, and audit.

Viewing results in Beacon

From the Results screen, you can:

• Search by UID
• Filter by status, risk band, and date range
• View individual detailed results including risk rating, trust rating, trait scores, and assessment metadata
• Export results as CSV or XLS
• Use the Re-try action to manually attempt rescoring if a data connection issue occurred

The results screen defaults to Production. Switch to the Test tab to view test sessions.

Receiving results via webhooks

For integrated setups, results are delivered as psychometric_score.complete events. See Webhook Payload Structure & Event Types for the full payload reference.

How to use the outputs

Approval thresholds — define score bands that map to approve, decline, or refer decisions within your credit policy.

Segmentation — use score bands to differentiate pricing, limits, or product eligibility across your applicant pool.

Manual review — use trust indicators to flag sessions for human review before an automated decision is applied.

Combining with other data — Begini is designed to sit alongside traditional credit bureau data and internal scoring models. The combination typically produces better risk separation than either source alone.

Next steps

• How Scoring Works — understand how the risk score is generated
• Fraud Detection & Trust Score — how to use trust indicators in decisioning
• Data, Exports & Monitoring — access and monitor your results data