ifrs9-credit-risk-master

ifrs9-credit-risk-master is a skill for Claude Code from vivy-yi/finance-skills. It costs 158 tokens per session (2,264 once invoked), scanned A, original, MIT.

A complete IFRS 9 credit-risk assessment for financial institutions and listed companies. IFRS 9 is an accounting standard that requires expected credit losses to be estimated and disclosed.

In plain words
What is it for?
It helps classify loans and other exposures, calculate expected credit loss, apply economic scenarios, compare results over time, and prepare IFRS 7 and IFRS 9 disclosures.
Why use it?
It brings exposure classification, loss calculations, economic forecasts, validation, and regulatory disclosures into one process.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter. Also seen: mentions CLAUDE.md.

Good fit It helps classify loans and other exposures, calculate expected credit loss, apply economic scenarios, compare results over time, and prepare IFRS 7 and IFRS 9 disclosures.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/vivy-yi/finance-skills/ifrs9-credit-risk-master
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add vivy-yi/finance-skills --skill ifrs9-credit-risk-master
Clone the repo
git clone --depth 1 https://github.com/vivy-yi/finance-skills

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for ifrs9-credit-risk-master

README.md
[![agentmods](https://agentmods.dev/badge/skills/vivy-yi/finance-skills/ifrs9-credit-risk-master/github.svg)](https://agentmods.dev/skills/vivy-yi/finance-skills/ifrs9-credit-risk-master)
Your own site
<a href="https://agentmods.dev/skills/vivy-yi/finance-skills/ifrs9-credit-risk-master"><img src="https://agentmods.dev/badge/skills/vivy-yi/finance-skills/ifrs9-credit-risk-master/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for ifrs9-credit-risk-master

Your own site · 80×15
<a href="https://agentmods.dev/skills/vivy-yi/finance-skills/ifrs9-credit-risk-master"><img src="https://agentmods.dev/badge/skills/vivy-yi/finance-skills/ifrs9-credit-risk-master.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 158 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,264 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00158 $0.02264
Opus 5 $0.00079 $0.01132
Sonnet 5 $0.00032 $0.00453
Haiku 4.5 $0.00016 $0.00226

Measured 9d ago against content hash 2d428f3d4dbc, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

ifrs9-credit-risk-master scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

finance-skills/skills/ifrs9-credit-risk/skills/ifrs9-credit-risk-master/SKILL.md · 250 lines

How it starts

The opening of the file, as written. The whole thing — 250 lines — stays where its author put it; the contents beside it link to each section on GitHub.

加载上下文

首次使用时: 读取 ../../CLAUDE.md 获取 Stage 分类标准/PD-LGD-EAD 参数/升级规则。


/ifrs9-credit-risk-master — IFRS 9 信用风险敞口评估主流程

完整评估流程

Step 1:敞口收集与 Stage 分类
  → 执行 stage-classification
  → 确认每个敞口所处 Stage

Step 2:ECL 计量
  → 执行 ecl-calculation
  → 计算每个敞口的 12 个月/存续期 ECL

Step 3:宏观前瞻调整
  → 执行 macro-forward-adjustment
  → 应用宏观情景权重调整 ECL

Step 4:ECL 结果验证
  → 迁徙分析(NCR)
  → 覆盖率合理性验证
  → 与上期/同业对比

Step 5:监管披露
  → 执行 ecl-disclosure
  → 生成 IFRS 7 / IFRS 9 披露信息

第一步:敞口收集与 Stage 分类

执行 Skill: stage-classification

□ 执行状态:[成功/失败]

□ 敞口汇总:
□ Stage 1 敞口:[X] 万元([X] 个客户/交易)
□ Stage 2 敞口:[X] 万元([X] 个客户/交易)
□ Stage 3 敞口:[X] 万元([X] 个客户/交易)
□ 合计敞口:[X] 万元

□ Stage 分布:
□ Stage 1 占比:[X]% — [✅ 正常 / ⚠️ 偏高]
□ Stage 2 占比:[X]% — [✅ 正常 / ⚠️ 偏高]
□ Stage 3 占比:[X]% — [✅ 正常 / ⚠️ 偏高]

□ 重大 Stage 转移:
□ 新迁入 Stage 2:[X] 个客户 / [X] 万元
□ 新迁入 Stage 3:[X] 个客户 / [X] 万元
□ 转移原因:[描述]

第二步:ECL 计量

执行 Skill: ecl-calculation

□ 执行状态:[成功/失败]

□ ECL 结果:
□ Stage 1 ECL:[X] 万元
□ Stage 2 ECL:[X] 万元
□ Stage 3 ECL:[X] 万元
□ 合计 ECL:[X] 万元

□ 覆盖率:
□ Stage 1 覆盖率:[X]% — [✅ 充足 / ⚠️ 偏低]
□ Stage 2 覆盖率:[X]% — [✅ 充足 / ⚠️ 偏低]
□ Stage 3 覆盖率:[X]% — [✅ 充足 / ⚠️ 偏低]

□ 与上期对比:
□ 上期 ECL:[X] 万元 vs 本期 [X] 万元
□ 变动:[±X] 万元 / [±X]%
□ 主要变动原因:[描述]

第三步:宏观前瞻调整

执行 Skill: macro-forward-adjustment

□ 执行状态:[成功/失败/不适用]

□ 宏观情景权重:
□ 乐观情景:[X]% — GDP +[X]%
□ 基准情景:[X]% — GDP [X]%
□ 悲观情景:[X]% — GDP -[X]%

□ 前瞻调整后 ECL:
□ 调整前 ECL:[X] 万元
□ 调整后 ECL:[X] 万元
□ 前瞻调整影响:[±X] 万元 / [±X]%

□ 调整合理性:[✅ 合理 / ⚠️ 偏差较大 — 说明:...]

第四步:结果验证

□ 迁徙分析(NCR):
□ Stage 1 → Stage 2 净转入:[X] 个 / [X] 万元
□ Stage 2 → Stage 3 净转入:[X] 个 / [X] 万元
□ 迁徙是否符合预期:[✅ 是 / ⚠️ 异常 — 说明:...]

□ 覆盖率验证:
□ 是否低于监管最低要求:[是/否]
□ 是否低于同业均值(偏离 > ±[X]%):[是/否]

□ Top 10 敞口集中度:
□ Top 3 敞口占合计 ECL:[X]% — [✅ 分散 / ⚠️ 集中]

□ 重大风险暴露:
□ 单一最大敞口:[客户名] — [X] 万元 / Stage [X] — ECL [X] 万元
□ 须升级至 CRO:[✅ 是 / ⚠️ 否]

第五步:监管披露

执行 Skill: ecl-disclosure

□ 执行状态:[成功/失败]

□ 披露完整性:
□ ECL 变动表(IFRS 7):[✅ 已提供 / ☐ 缺失]
□ Stage 转移说明:[✅ 已提供 / ☐ 缺失]
□ 宏观调整说明:[✅ 已提供 / ☐ 缺失]
□ 敏感性分析:[✅ 已提供 / ☐ 缺失]

□ 审计配合事项:
□ 审计调整:[X] 万元
□ 审计保留意见:[是/否 — 内容:...]

Read the full file on GitHub · 250 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 250 lines · 158 tokens per session scan A 2d428f3d4dbc

Subscribe to this mod's changes

ifrs9-credit-risk-master is a skill published in the GitHub repository vivy-yi/finance-skills (29 stars, last pushed 3mo ago), licensed MIT. It adds 158 tokens to every session and 2,264 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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