credit-due-diligence

Generate structured enterprise credit due diligence reports with risk metrics.

580|66|Updated Apr 21, 2025
One-click install
npx skills add https://github.com/aliyun/qwen-dianjin --skill credit-due-diligence
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: credit-due-diligence
Source: https://github.com/aliyun/qwen-dianjin/tree/main/DianJin-SKILLS/corporate-banker/credit-due-diligence
Command: npx skills add https://github.com/aliyun/qwen-dianjin --skill credit-due-diligence

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill eliminates the manual, error-prone work of producing a bank-grade enterprise credit due diligence report by systematically collecting and validating multi-source enterprise, credit, financial, and business-evidence data. It helps credit teams assess first repayment source strength, detect authenticity risks, and produce a structured output ready for lending review.

Core Features & Use Cases

  • End-to-end due diligence workflow (step-gated): Runs a fixed, gated process from data verification to risk assessment and lending recommendation.
  • Multi-source data integration & validation: Enumerates documents, verifies data completeness, calculates core financial metrics, and cross-checks business authenticity using contracts/invoices/water-power/utilities and bank flows.
  • Risk & red-line governance: Applies predefined constraints and one-veto red lines (D1–D7) to determine whether to recommend, conditionally recommend, defer, or prohibit lending.
  • Structured, downstream-compatible report output: Produces a structured report with quantified metrics, explicit data sources, and an audit-trail-ready structure.

Quick Start

Use the credit-due-diligence skill to generate a due diligence report for a new corporate loan request by providing the enterprise name, due diligence purpose (e.g., first loan), and uploading the required工商/征信/财务/合同/发票/流水 materials.

Frequently Asked Questions about credit-due-diligence

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

FAQPage Schema
How do I generate a bank-grade enterprise credit due diligence report?

To generate a bank-grade enterprise credit due diligence report, provide the enterprise name, due diligence purpose, and upload required business registration, credit bureau, financial, contract, invoice, and bank flow materials for systematic multi-source validation.

What is a one-veto red line in corporate credit risk assessment?

A one-veto red line in corporate credit risk assessment is a predefined constraint (D1–D7) that automatically triggers a defer or prohibit lending recommendation, overriding any other positive financial metrics to ensure strict compliance.

How to cross-validate business authenticity for a pre-loan due diligence check?

To cross-validate business authenticity during a pre-loan due diligence check, analyze and verify operating evidence such as contracts, invoices, utility bills, and bank flows against submitted financial statements and registration data.

Can I use this structured report workflow for renewal loans and additional credit applications?

Yes, you can use this structured report workflow for renewal loans and additional credit applications, as the step-gated process supports various pre-loan corporate banking scenarios requiring first repayment source strength assessment.

How does the DSCR calculation fit into the enterprise risk evaluation process?

The DSCR calculation fits into the enterprise risk evaluation process by serving as a quantified risk metric that helps assess the strength of the first repayment source before generating a restricted, non-overreaching lending recommendation.

What are the limitations of automated audit trail generation in credit due diligence?

The limitation of automated audit trail generation in credit due diligence is that it relies entirely on the completeness of uploaded documents; missing financial statements or incomplete bank flow data will restrict the system's ability to validate authenticity and produce lending recommendations.