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credit-risk-extraction

Extract enterprise credit risk narratives into structured Markdown reports.

580|66|Updated Apr 21, 2025
Search Tags:#compliance#audit trail#structured report#credit risk#risk extraction#industry classification#enterprise labeling
One-click install
npx skills add https://github.com/aliyun/qwen-dianjin --skill credit-risk-extraction
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: credit-risk-extraction
Source: https://github.com/aliyun/qwen-dianjin/tree/main/DianJin-SKILLS/credit-risk-manager/credit-risk-extraction
Command: npx skills add https://github.com/aliyun/qwen-dianjin --skill credit-risk-extraction

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires yaml, sys, datetime, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill converts unstructured credit-risk narratives in bank/credit materials into a structured, audit-friendly report with enterprise label profiling and per-risk extraction, while enforcing strict anti-regression rules (e.g., no risk grading, no vague wording, full coverage, and exact原文复制).

Core Features & Use Cases

  • Enterprise label profiling: Produces a 14-tag enterprise picture using GB/T 4754-2017 four-level industry classification (门类→大类→中类→小类).
  • Risk point extraction & transformation: Extracts all risk points (R1…RN) from sections like “授信业务关键风险评价/建议关注事项/风险提示” and converts each into a 6-dimension structured record.
  • Compliance guardrails: Blocks prohibited outputs (risk grading, vague words, payoff/investment promises) and requires full, exact original risk text coverage.
  • Use Cases: Pre-loan due diligence packaging, approval committee materials, risk report quality review, and building a reusable risk knowledge base for credit teams.

Quick Start

Use the credit-risk-extraction skill to generate a complete risk extraction report from your uploaded 信贷报告/风险评价文本 and 企业基本情况描述, following the required output template.

Frequently Asked Questions about credit-risk-extraction

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

FAQPage Schema
How do I extract structured credit risk points from unstructured text for due diligence?▼

To extract structured credit risk points, convert unstructured risk narratives into a structured, audit-friendly report. This process generates enterprise label profiles and per-risk structured analyses, enforcing exact original text copying and strict compliance constraints for approval workflows.

What is enterprise label profiling in credit risk extraction?▼

Enterprise label profiling is the process of generating a 14-tag enterprise picture using the GB/T 4754-2017 four-level industry classification. It categorizes businesses from broad category down to sub-class, providing a standardized industry context for credit risk analysis.

How do I generate an audit-friendly risk report for a pre-loan approval committee?▼

Generate an audit-friendly risk report by processing credit evaluation text and enterprise background details into a two-part Markdown document. The output includes enterprise labels and 6-dimension structured risk records, ensuring full coverage without prohibited risk grading or vague recommendations.

Does credit risk extraction enforce compliance constraints against risk grading?▼

Yes, credit risk extraction enforces compliance guardrails that block prohibited outputs like risk grading, vague wording, and payoff promises. It requires full, exact original risk text coverage to ensure the report remains audit-friendly and compliant.

What are the limitations of automated credit risk extraction?▼

Automated credit risk extraction prohibits risk grading and vague or overreaching recommendations. It is limited to structuring provided risk evaluation text and enterprise background details, strictly enforcing exact original text copying without adding speculative investment advice.

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