SuperAPI AI Directory

aging-analysis-ar

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Updated 10-16 08:46

About this skill

Load context

On first use: Read ../../CLAUDE.md to obtain scenario-level configuration (customer grading/bad debt provision rules/collection policy).


/aging-analysis-ar — Accounts receivable aging analysis

Examples

→ Example: The user says "Help me look at the current accounts receivable aging; which customers are over 90 days?" The system should invoke this skill, perform aging analysis, and identify high-risk customers.

→ Example: The user says "Collections this month are not ideal; help me analyze which customers have been delaying for a long time." The system should invoke this skill and analyze the reasons for collection delays by aging stratification.

→ Example: The user says "The VP says we need to reduce DSO by 15 days next quarter; help me see where to start." The system should invoke this skill and identify the key levers for DSO reduction.

Aging stratification definition

账龄 = 截止日期 - 到期日(发票日期 + 账期)

账龄区间:
  - 正常(0-30 天):在账期内,正常管理
  - 关注(31-60 天):开始关注,催款介入
  - 警告(61-90 天):须正式催款
  - 危险(91-180 天):须升级催款 + 停止接单
  - 坏账(> 180 天):考虑法律诉讼/核销

Step 1: Obtain AR data

Obtain accounts receivable data from [ERP]:

查询条件:
  - 截止日期:[YYYY-MM-DD]
  - 客户:全部
  - 状态:未清(Open)

导出字段:
  客户名称 | 发票号码 | 开票日期 | 到期日 | 应收金额 | 账龄天数 | 客户信用等级 | 合同账期

Supplement customer information from [CRM]:

□ 客户信用等级(A/B/C/D)
□ 客户联系人
□ 信用额度使用情况
□ 最近一次沟通记录

Step 2: Aging stratification analysis

Summary statistics:

总应收款:[XXX万]
  - 正常(0-30 天):[XXX万]([X]%)
  - 关注(31-60 天):[XXX万]([X]%)
  - 警告(61-90 天):[XXX万]([X]%)
  - 危险(91-180 天):[XXX万]([X]%)
  - 坏账(> 180 天):[XXX万]([X]%)

Step 3: Bad debt provision calculation

Bad debt provision accrual (by aging method):

□ 1-30 天:0% → 计提 [XXX万]
□ 31-90 天:10% → 计提 [XXX万]
□ 91-180 天:30% → 计提 [XXX万]
□ 181-365 天:50% → 计提 [XXX万]
□ > 365 天:100% → 计提 [XXX万]

坏账准备合计:[XXX万]

Step 4: TOP N high-risk customer identification

TOP 5 overdue major customers:

1. [客户名称]:[XXX万] / 逾期 [X] 天
2. [客户名称]:[XXX万] / 逾期 [X] 天
3. ...

风险评估:
  → 单一客户逾期 > [XXX万] 须立即升级
  → 客户逾期 > 90 天须制定专门催款计划

High-risk signal check:

□ 是否有客户连续 3 个月出现在 TOP 5 逾期清单?
□ 是否有客户信用评级在最近 3 个月内被下调?
□ 是否有客户涉及重大诉讼/被执行?
□ 是否有客户付款承诺反复失信?

Step 5: Generate aging analysis report

═══════════════════════════════════════
应收账款账龄分析报告
截止日期:[YYYY-MM-DD]
报告生成时间:[YYYY-MM-DD HH:MM]
═══════════════════════════════════════

【总体概览】

总应收款:[XXX万]([X] 笔)
已逾期应收款:[XXX万]([X] 笔)
逾期率:[X%](已逾期 / 总应收款)

【账龄分布】

账龄区间 | 金额 | 占比 | 笔数 | 坏账准备计提
---------|------|------|------|--------------
0-30天  | [XXX万] | [X%] | [X]  | [X万]
31-60天 | [XXX万] | [X%] | [X]  | [X万]
61-90天 | [XXX万] | [X%] | [X]  | [X万]
91-180天| [XXX万] | [X%] | [X]  | [X万]
>180天  | [XXX万] | [X%] | [X]  | [X万]
合计    | [XXX万] | 100% | [X]  | [X万]

【坏账准备】

应计提坏账准备:[XXX万]
实际计提金额:[XXX万]
差额(如有):[XXX万]

【TOP 5 逾期大客户】

1. [客户名称] | 逾期金额:[XXX万] | 逾期天数:[X]天 | 客户等级:[A/B/C/D]
   → 最后付款日期:[YYYY-MM-DD]
   → 最后联系日期:[YYYY-MM-DD]
   → 风险等级:[🔴高/⚠️中/✅低]

2. [客户名称] | ... | ... | ...

【须立即跟进项】

□ 逾期 > 90 天的客户:[X] 家 / [XXX万]
  → 须发送正式催款函
  → 须评估是否停止接单

□ 逾期 > 180 天的客户:[X] 家 / [XXX万]
  → 须启动法律诉讼评估
  → 须准备核销材料

□ 客户信用评级下调:[X] 家
  → 须收紧信用额度

□ 新增逾期客户:[X] 家 / [XXX万]
  → 须了解原因,制定催款计划

【下月到期应收预警】

到期日 | 客户 | 金额 | 账龄
--------|------|------|------
[日期]  | [客户] | [XX万] | 即将到期
...

═══════════════════════════════════════
置信度:[✅ 高 / ⚠️ 中 / 🔴 低]
报告状态:[✅ 可用 / ⏳ 数据待核实]
═══════════════════════════════════════

Escalation trigger conditions

  • Overdue rate increased by > 10% compared with last month
  • A single major customer's overdue amount > [fill in: e.g., 1 million yuan]
  • Number of customers overdue > 90 days > [X]
  • Additional bad debt provision required > [fill in: e.g., 500,000 yuan]
  • Large-scale downgrades in customer credit ratings discovered

Finance Skills — aging-analysis-ar atomic skill