credit-large-exposure-mgmt

Calculate large-credit exposures and generate compliant de-risking plans for banks.

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

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill solves the operational and compliance problem of monitoring large-credit exposure concentration across single customers, groups, and related parties, then producing actionable early-warning and de-risking (压降) plans without violating regulatory limits.

Core Features & Use Cases

  • All-scope exposure measurement: Computes gross and net risk exposures across on-balance-sheet, off-balance-sheet, and interbank/investment items, including penetration (穿透) to ultimate obligors.
  • Limit monitoring and tiered alerts: Compares calculated exposures against regulatory red lines and internal control thresholds, producing warning levels (关注/黄色/橙色/红色/突破红线) and response requirements.
  • Pre-approval concentration checks (新增预检): Simulates the impact of a new credit proposal on concentration ratios and enforces blocking rules for red-line breaches.
  • Group and related-party identification: Applies group identification standards and unified credit management logic to prevent missing members and double counting.
  • Mitigation plan generation: When alerts trigger (especially 橙色/红色), formulates prioritized mitigation measures with responsibilities, timelines, and impact assessment, while keeping output within monitoring/advisory scope.

Quick Start

Use this Skill to generate a daily concentration monitoring report for a specified customer or group, including penetration status, limit comparisons, warning level, and any required mitigation plan.

Frequently Asked Questions about credit-large-exposure-mgmt

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

FAQPage Schema
How do I calculate large credit exposure concentration with penetration to the ultimate obligor?

Large credit exposure concentration monitoring requires calculating total and net exposures across on-balance-sheet, off-balance-sheet, and interbank items while applying penetration to ultimate obligors. This process prevents missing group members and double counting during risk exposure measurement.

What is the best way to generate a compliant de-risking plan when a credit concentration alert triggers?

When orange or red tiered concentration alerts trigger, form a compliant de-risking plan by generating prioritized mitigation measures with assigned responsibilities, timelines, and impact assessments. This keeps the advisory output within regulatory monitoring scope while enforcing red-line constraints.

Can I simulate new credit pre-approval concentration checks to prevent regulatory red-line breaches?

You can perform pre-approval concentration checks by simulating a new credit proposal's impact on concentration ratios. The system enforces blocking rules automatically to prevent any simulated new credit from breaching mandatory regulatory red lines.

How does tiered alert limit monitoring work for bank credit concentration risk?

Tiered alert limit monitoring works by comparing calculated exposures against regulatory red lines and internal control thresholds. It produces escalating warning levels—attention, yellow, orange, red, and red-line breach—each triggering specific response requirements for credit concentration management.

Does credit concentration monitoring support single-customer, group-customer, and related-party scenarios?

Credit concentration monitoring supports single-customer, group-customer, related-party, and anonymous-customer scenarios. It applies group identification standards and unified credit management logic to ensure accurate multi-dimensional concentration analysis across all parties.