kyc-rules

Apply KYC/AML rules grid to onboarding records and generate risk ratings.

Updated May 9, 2026
One-click install
npx skills add https://github.com/iTzFaisal/financial-services --skill kyc-rules-itzfaisal
Or copy as Structured Prompt for Agent
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Skill: kyc-rules
Source: https://github.com/iTzFaisal/financial-services/tree/main/.opencode/skills/kyc-rules
Command: npx skills add https://github.com/iTzFaisal/financial-services --skill kyc-rules-itzfaisal

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Apply the firm's KYC/AML rules grid to a parsed onboarding record to generate a risk rating, enumerate rule outcomes with citations, and flag missing items or escalation needs.

Core Features & Use Cases

  • Risk-rating generation: compute a risk level (low/medium/high) from the rules grid factors such as jurisdiction, applicant type, ownership opacity, PEP exposure, sanctions/adverse media, and source of funds.
  • Outcome cataloging: list each applicable rule with its outcome and the field(s) driving it, citing the rule reference.
  • Disposition generation: produce a structured JSON payload (risk_rating, missing_documents, escalation_reasons, rule_outcomes) for routing to human reviewers or downstream systems.
  • Compliance tooling integration: designed to run after kyc-doc-parse and consume screening results to support escalation decisions.

Quick Start

Parse an onboarding record with kyc-doc-parse, apply the kyc-rules grid, and generate a disposition for review.

Frequently Asked Questions about kyc-rules

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate a KYC risk rating from onboarding data?

KYC risk rating generation applies the firm's AML rules grid to a parsed onboarding record, evaluating jurisdiction, applicant type, PEP exposure, and sanctions screening results to compute a low, medium, or high risk level.

What is an AML rule grid and how does it route onboarding records?

An AML rule grid evaluates parsed onboarding factors like ownership opacity and adverse media against firm policies to produce per-rule outcomes, flag missing documents, and generate a disposition for escalation or human review.

Can I automate KYC escalation decisions using sanctions and PEP screening results?

Automating KYC escalation decisions uses screening results and supporting documents to generate structured JSON payloads containing escalation reasons and rule outcomes with citations for routing to human reviewers.

How do I track missing documents during the AML onboarding process?

Tracking missing documents during AML onboarding involves applying the rules grid to a parsed record, which outputs a structured JSON payload enumerating required-document statuses and flagging any missing items.

What data is needed to calculate a KYC risk score from an onboarding application?

Calculating a KYC risk score requires a parsed onboarding record, screening results including sanctions and PEP data, and supporting documents to evaluate risk factors like source of funds and jurisdiction.

When should I escalate an onboarding record for human review in a compliance workflow?

Escalating an onboarding record for human review is triggered when the applied KYC rules grid generates a high risk rating, identifies missing documents, or produces escalation reasons based on adverse media or ownership opacity.