accounts-receivable-manager

# 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](https://afrexai-cto.github.io/context-packs/)** — Industry-specific agent configs for Fintech, Professional Services, SaaS, and more ($47 each) - **[AI Revenue Leak Calculator](https://afrexai-cto.github.io/ai-revenue-calculator/)** — Find where your business is losing money to manual processes - **[Agent Setup Wizard](https://afrexai-cto.github.io/agent-setup/)** — Get your AI agent configured in minutes Built by [AfrexAI](https://afrexai-cto.github.io/context-packs/) — operational AI for businesses that run on results, not hype.