/ risk score / field evidence / AI verification
Field-Level Evidence Beats One Risk Score
Buyers need to see the names, dates, and documents behind an AI risk result before acting on it.
A single risk score can help sort a long queue. It should not become the whole explanation. Supplier verification depends on fields: legal name, registration code, address, invoice issuer, beneficiary, certificate holder, and product model.
Build the output so users can click from the score to the evidence. If the system flags a mismatch, show both fields, their source documents, and the capture date. If the system clears a case, show which critical fields matched.
Scores can hide priority. A supplier may score well because the license and website look clean, while the bank beneficiary differs from the invoice issuer. That payment signal deserves direct attention rather than a quiet effect on a composite number.
Use scores for routing and fields for decisions. An analyst can accept a low-risk queue label, but payment approval should rest on visible evidence.
The best user interface often looks less dramatic than a dashboard. A table of fields, match status, source, and reviewer note gives buyers the evidence they need.
Working checklist
- Show source fields behind every score.
- Keep payment mismatch as a direct flag.
- Use scores for queue routing.
- Let analysts correct field matches.
- Store reviewer notes beside evidence.