A risk scoring engine turns many verification signals into a single, explainable decision: approve, reject or escalate. Here is how to design one that satisfies both fraud and compliance teams.
What a risk scoring engine does
It ingests the results of identity, document, biometric and AML checks, weighs them, and outputs a score plus a recommended action. Certivant ships this as a no-code risk scoring and policy engine.
Choosing your signals
- Identity confidence from KYC and document verification.
- Liveness and face-match results from biometric verification.
- Watchlist hits from AML screening against OpenSanctions.
- Behavioural and device signals.
Weighting and thresholds
Assign each signal a weight that reflects its predictive value, then set thresholds. A common pattern is:
- Auto-approve above a high score.
- Auto-reject below a low score.
- Escalate the band in between to a human reviewer.
Keep it explainable
Every score should show the factors behind it, and every decision should be written to a tamper-evident audit trail. This satisfies the “right to explanation” expectations regulators increasingly apply to automated decisions.
Build vs buy
Building in-house means owning data integrations, list updates and audit tooling. A configurable engine lets you express policy as rules and ship faster — see the developer docs and automation workflows.
Frequently asked questions
Should thresholds be fixed?
No — tune them against outcomes and adjust by product or jurisdiction risk.
How do I avoid black-box decisions?
Require per-factor explanations and log them, so any decision can be reconstructed and defended.
Configure decisions without code. Start free today.
