
Aging Analysis Automation for Accounts Receivable
Analyze AR aging data, flag delinquency risks, and generate collection strategies
What You Can Do
You can upload aging data from your accounting system and Claude will systematically categorize invoices by delinquency bucket, identify high-risk accounts with payment pattern analysis, explain why balances are aging, and generate prioritized collection strategies with account-specific context. This transforms static aging reports into actionable recovery plans that help you understand portfolio health and accelerate cash flow.
Features
Automatically categorize invoices into Current, 30, 60, 90+ day buckets and calculate aging metrics by customer and risk tier
Flag high-risk accounts based on payment history, days past due, invoice volume, and aging trends to prioritize collection efforts
Identify root causes of aging variances (payment term misalignment, disputed invoices, credit holds, systemic customer issues) with supporting evidence
Create prioritized action plans by customer and aging bucket with specific next steps, call scripts, and escalation triggers
Review 6-12 month payment history to identify trends, recurring delays, and customers likely to resolve vs. require escalation
Generate summary metrics (Days Sales Outstanding, aging distribution, concentration risk) with benchmarking context
Produce management-ready summaries explaining aging drivers and collection priorities with variance reconciliation
Example Output
Input: Raw aging report with 50 customer accounts, invoice details, and 12-month payment history
Output Example 1 — Risk Summary:
- High Risk (45 days+ overdue): ABC Manufacturing ($87K, 98 DPO, 3 late payments in 6 months) → Escalate to credit manager; consider payment plan
- Medium Risk (30-45 days): XYZ Corp ($34K, 52 DPO, consistent 10-day delays) → Call today; review payment terms alignment
- Current: 32 accounts → Standard follow-up cadence
Output Example 2 — Variance Explanation:
- Q2 aging increased 12% vs. Q1: 60% due to two customers on extended payment plans (COVID relief), 40% due to invoice dispute holds (3 accounts). Recommend: Schedule resolution calls for dispute accounts by Friday.
Output Example 3 — Collection Action Plan:
- Week 1: Call ABC Manufacturing (VP Finance) with proposed payment plan; send XYZ Corp formal notice of payment terms violation
- Week 2: Escalate unresolved 90+ day accounts to credit manager for hold/write-off review
What's Included
- SKILL.md instruction file: Full workflow for data preparation, analysis prompts, and output validation
- Aging Data Template: Standardized format for invoice-level data import (Excel-ready columns)
- Collection Priority Matrix: Risk scoring framework and escalation criteria by aging bucket
- Account Analysis Checklist: Step-by-step validation for high-risk accounts (payment history, disputes, credit holds)
- Management Summary Template: Executive-ready format for variance explanation and recovery strategy reporting
Who It's For
- Accounts Receivable Specialists — Streamline monthly aging analysis and collection prioritization
- Credit Managers — Identify systemic delinquency patterns and high-risk accounts for credit decisions
- Controllers & Finance Managers — Generate variance explanations and cash flow impact analysis for leadership reporting
- Collection Teams — Develop account-specific collection strategies with prioritized call lists and talking points
- CFOs & Finance Directors — Monitor portfolio health, Days Sales Outstanding trends, and cash recovery metrics
Best For
- Monthly aging report analysis — Process 10+ pages of invoice data and flag collection priorities
- High-risk account investigation — Deep-dive into specific customer payment patterns and explain chronic delays
- Collection strategy development — Generate prioritized action plans with escalation triggers and recovery timelines
- Variance analysis & management reporting — Explain why aging increased/decreased month-over-month with root cause identification
- Credit limit review & relationship decisions — Assess customer payment reliability and recommended credit adjustments







