SkillHub

afrexai-accounts-receivable

v1.0.0

应收账款自动化:账龄分析、催收优先级管理、付款提醒、对账匹配、DSO跟踪及坏账预测。

Sourced from ClawHub, Authored by 1kalin

Installation

Please help me install the skill `afrexai-accounts-receivable` from SkillHub official store. npx skills add 1kalin/afrexai-accounts-receivable

Accounts Receivable Manager

Automate AR workflows: aging analysis, collection prioritization, payment follow-ups, cash application, and bad debt forecasting.

What It Does

  1. AR Aging Report — Bucket outstanding invoices by 0-30, 31-60, 61-90, 90+ days with risk scoring
  2. Collection Priority Queue — Rank overdue accounts by amount × days × risk for optimal follow-up order
  3. Payment Reminder Drafts — Generate professional escalation emails (friendly → firm → final notice → collections)
  4. Cash Application Matching — Match incoming payments to open invoices with variance handling
  5. Bad Debt Forecasting — Predict write-offs using historical payment patterns and aging trends
  6. DSO Tracking — Calculate Days Sales Outstanding with trend analysis and benchmarks by industry

How to Use

Tell your agent what you need:

  • "Run an AR aging analysis for our open invoices"
  • "Prioritize our collection queue — what should we chase first?"
  • "Draft a 60-day overdue reminder for [client name]"
  • "Our DSO is 47 days — how does that compare to SaaS benchmarks?"
  • "Forecast bad debt exposure for Q1"

AR Aging Buckets

Bucket Risk Level Action
Current (0-30) Low Monitor
31-60 days Medium Friendly reminder
61-90 days High Escalation call + written notice
90+ days Critical Final demand → collections/write-off review

Collection Priority Formula

Priority Score = (Invoice Amount × 0.4) + (Days Overdue × 0.3) + (Customer Risk Score × 0.3)

Customer Risk Score (1-10) based on: - Payment history (avg days to pay) - Number of past-due invoices - Credit limit utilization - Industry default rates

Payment Reminder Escalation

Day 1 (Invoice Due)

Subject: Invoice #[NUM] — Payment Due Today Tone: Friendly, informational

Day 7 (1 Week Overdue)

Subject: Friendly Reminder — Invoice #[NUM] Past Due Tone: Warm but clear

Day 30 (1 Month Overdue)

Subject: Payment Required — Invoice #[NUM] Now 30 Days Past Due Tone: Professional, firm

Day 60 (2 Months Overdue)

Subject: Urgent — Invoice #[NUM] Significantly Overdue Tone: Serious, mention late fees / service impact

Day 90+ (Final Notice)

Subject: Final Notice — Invoice #[NUM] Requires Immediate Payment Tone: Formal, mention collections referral

DSO Benchmarks by Industry

Industry Good DSO Average DSO Poor DSO
SaaS / Software <30 30-45 >60
Professional Services <35 35-55 >70
Manufacturing <40 40-60 >75
Construction <45 45-70 >90
Healthcare <35 35-50 >65

Bad Debt Forecasting Model

Estimate write-off probability by aging bucket: - Current: 1-2% default rate - 31-60 days: 5-8% - 61-90 days: 15-25% - 90-120 days: 30-50% - 120+ days: 50-80%

Apply to outstanding amounts for expected loss provision.

Cash Application Rules

  1. Exact match — Payment amount matches one open invoice exactly
  2. Combination match — Payment matches sum of multiple invoices
  3. Short payment — Payment < invoice amount → flag for dispute/deduction review
  4. Overpayment — Payment > invoice → apply to oldest open balance or issue credit
  5. Unidentified — No match found → hold in suspense, research within 48 hours

Output Format

When generating AR reports, include: - Total AR outstanding - Aging distribution ($ and %) - Top 10 overdue accounts by priority score - DSO current vs. 3-month trend - Estimated bad debt exposure - Recommended actions (who to call, what to send)


Take It Further

This skill handles AR analysis and workflows. For full financial operations automation:

  • AI Agent Context Packs — Industry-specific agent configs for Fintech, Professional Services, SaaS, and more ($47 each)
  • AI Revenue Leak Calculator — Find where your business is losing money to manual processes
  • Agent Setup Wizard — Get your AI agent configured in minutes

Built by AfrexAI — operational AI for businesses that run on results, not hype.