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analysis, collection prioritization, payment follow-ups, cash application, and bad debt forecasting.\n\n## What It Does\n\n1. **AR Aging Report** — Bucket outstanding invoices by 0-30, 31-60, 61-90, 90+ days with risk scoring\n2. **Collection Priority Queue** — Rank overdue accounts by amount × days × risk for optimal follow-up order\n3. **Payment Reminder Drafts** — Generate professional escalation emails (friendly → firm → final notice → collections)\n4. **Cash Application Matching** — Match incoming payments to open invoices with variance handling\n5. **Bad Debt Forecasting** — Predict write-offs using historical payment patterns and aging trends\n6. **DSO Tracking** — Calculate Days Sales Outstanding with trend analysis and benchmarks by industry\n\n## How to Use\n\nTell your agent what you need:\n\n- \"Run an AR aging analysis for our open invoices\"\n- \"Prioritize our collection queue — what should we chase first?\"\n- \"Draft a 60-day overdue reminder for [client name]\"\n- \"Our DSO is 47 days — how does that compare to SaaS benchmarks?\"\n- \"Forecast bad debt exposure for Q1\"\n\n## AR Aging Buckets\n\n| Bucket | Risk Level | Action |\n|--------|-----------|--------|\n| Current (0-30) | Low | Monitor |\n| 31-60 days | Medium | Friendly reminder |\n| 61-90 days | High | Escalation call + written notice |\n| 90+ days | Critical | Final demand → collections/write-off review |\n\n## Collection Priority Formula\n\n```\nPriority Score = (Invoice Amount × 0.4) + (Days Overdue × 0.3) + (Customer Risk Score × 0.3)\n```\n\nCustomer Risk Score (1-10) based on:\n- Payment history (avg days to pay)\n- Number of past-due invoices\n- Credit limit utilization\n- Industry default rates\n\n## Payment Reminder Escalation\n\n### Day 1 (Invoice Due)\nSubject: Invoice #[NUM] — Payment Due Today\nTone: Friendly, informational\n\n### Day 7 (1 Week Overdue)\nSubject: Friendly Reminder — Invoice #[NUM] Past Due\nTone: Warm but clear\n\n### Day 30 (1 Month Overdue)\nSubject: Payment Required — Invoice #[NUM] Now 30 Days Past Due\nTone: Professional, firm\n\n### Day 60 (2 Months Overdue)\nSubject: Urgent — Invoice #[NUM] Significantly Overdue\nTone: Serious, mention late fees / service impact\n\n### Day 90+ (Final Notice)\nSubject: Final Notice — Invoice #[NUM] Requires Immediate Payment\nTone: Formal, mention collections referral\n\n## DSO Benchmarks by Industry\n\n| Industry | Good DSO | Average DSO | Poor DSO |\n|----------|----------|-------------|----------|\n| SaaS / Software | <30 | 30-45 | >60 |\n| Professional Services | <35 | 35-55 | >70 |\n| Manufacturing | <40 | 40-60 | >75 |\n| Construction | <45 | 45-70 | >90 |\n| Healthcare | <35 | 35-50 | >65 |\n\n## Bad Debt Forecasting Model\n\nEstimate write-off probability by aging bucket:\n- Current: 1-2% default rate\n- 31-60 days: 5-8%\n- 61-90 days: 15-25%\n- 90-120 days: 30-50%\n- 120+ days: 50-80%\n\nApply to outstanding amounts for expected loss provision.\n\n## Cash Application Rules\n\n1. **Exact match** — Payment amount matches one open invoice exactly\n2. **Combination match** — Payment matches sum of multiple invoices\n3. **Short payment** — Payment < invoice amount → flag for dispute/deduction review\n4. **Overpayment** — Payment > invoice → apply to oldest open balance or issue credit\n5. **Unidentified** — No match found → hold in suspense, research within 48 hours\n\n## Output Format\n\nWhen generating AR reports, include:\n- Total AR outstanding\n- Aging distribution ($ and %)\n- Top 10 overdue accounts by priority score\n- DSO current vs. 3-month trend\n- Estimated bad debt exposure\n- Recommended actions (who to call, what to send)\n\n---\n\n## Take It Further\n\nThis skill handles AR analysis and workflows. For full financial operations automation:\n\n- **[AI Agent Context Packs](https://afrexai-cto.github.io/context-packs/)** — Industry-specific agent configs for Fintech, Professional Services, SaaS, and more ($47 each)\n- **[AI Revenue Leak Calculator](https://afrexai-cto.github.io/ai-revenue-calculator/)** — Find where your business is losing money to manual processes\n- **[Agent Setup Wizard](https://afrexai-cto.github.io/agent-setup/)** — Get your AI agent configured in minutes\n\nBuilt by [AfrexAI](https://afrexai-cto.github.io/context-packs/) — operational AI for businesses that run on results, not hype.\n","readmeExcerpt":"Accounts Receivable Manager Automate AR workflows: aging analysis, collection prioritization, payment follow-ups, cash application, and bad debt forecasting. 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