Screening Alert Walkthrough

How It Works

1. Profile Creation Greenlight creates two profiles:

• Customer profile (from your KYC data)

• Match entity profile (from the screening alert)

2. Data Enrichment The system automatically searches public sources to add context, such as:

• Official government websites

• Sanctions databases

• Public records

3. Automated Comparison Greenlight identifies key differences and similarities:

Qualifying factors (suggest a match):

• Name similarity

• Shared attributes like country

Disqualifying factors (suggest false positive):

• Date of birth mismatch

• Different locations

• Different occupations

4. Scoring Based on these factors, Greenlight calculates whether the alert is likely a false positive or requires review.

Viewing Results

• Click "Score Breakdown" to see exactly which factors influenced the decision

• Use "View Alert Collection" to see all alerts for a customer side-by-side

• Review the automated summary for quick decision-making

Example

In the screenshot above, "Will Lawrence" (customer) was flagged for "William Lawrence" (Kentucky politician). The system identified:

• 72-year age difference

• Different states (California vs Kentucky)

• Different careers (AI vs politics)

Result: Clear false positive, saving manual review time.