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.