Auto-declining applicants is risky, unfair and often unnecessary. Our approach to application fraud scores every application from 0 to 1, explains the score, and routes it.
- Low risk: fast-tracked, with a sampled audit.
- Medium risk: a reviewer decides.
- High risk: compliance verifies first.
Every decision teaches the model
Reviewer decisions are logged and become labels. Drift is monitored, and a retrained model is promoted only if it beats the previous one.
In a client-reported proof of concept on 394 online applications, the fraud rate fell from 48% before AI, to 3% flagged with AI scoring, to 0% with human review closing the last gap.
