Deterministic scorecard
The auditable baseline. Each factor has a weight; each factor has cases that map an observed value to a sub-score; the final score is the weighted sum. Example. A simple onboarding scorecard with three factors:
Observed values
{ device: 18, identity: 0.92, amount: 350 } produce sub-scores { 0, 0, 20 } → weighted score 5. Low band, auto-approve.
Deterministic, auditable, easy to explain in regulator interviews.
AI synthesis
Frayme is pro AI synthesis for the cases the scorecard can’t model cleanly — adverse-media free text, document-narrative reasoning, multi-vendor disagreement signals, cross-document corroboration. When it fits:- The synthesiser receives the upstream structured signals (identity outcome, AML hits, region check, on-chain exposure) and any free-text artefacts.
- It returns a strict JSON schema:
{ risk_score, risk_band, recommendation, reasoning }. - The score and band are written back to the run context; downstream decision tables route on them just like with a scorecard.
ai node for the production reference.
The four bands
- Band is fixed — every Frayme workflow uses the same four names.
- Range is personalizable per client. A more conservative client can shrink Low to 0–20.
- Routing is personalizable per client. The same Medium-band score can auto-approve for one client and route to review for another.
Originator risk level
When the identity suite returns arisk_level on the originator (low / medium / high), Frayme surfaces it on the manual review screen as a first-class field — and downstream rules can read it directly. A high originator risk level typically:
- Tightens velocity rules for that originator’s subaccounts.
- Triggers paid-per-query counterpart enrichment that wouldn’t fire for a low-risk originator.
- Shows up at the top of the Decision Console so the analyst sees it before the per-case detail.