Invoice Aging and Collections Risk Analysis

Act as a finance analytics lead. Analyze invoice aging and collections risk for [company/business model] using the data below.

Data available: [paste table or describe fields: customer, invoice amount, due date, invoice date, days overdue, payment history, account owner, segment, disputed status, promised pay date]
Current AR total: [amount]
Cash flow target: [monthly/quarterly target]
Collections policy: [reminder cadence, late fees, escalation rules]
Customer segments: [SMB, enterprise, strategic accounts, region, industry]
Known constraints: [do-not-contact accounts, disputed invoices, payment plans, relationship sensitivity]

Deliver:
1. **Executive summary** — total AR, overdue amount, high-risk exposure, and cash flow implication
2. **Aging breakdown** — current, 1-30, 31-60, 61-90, 90+ days, with percentages
3. **Risk segmentation** — customer groups by amount, age, payment behavior, dispute status, and strategic value
4. **Collections priority list** — top accounts to contact first and why
5. **Cash forecast scenarios** — conservative, expected, and upside collection assumptions
6. **Recommended actions** — outreach sequence, owner assignment, escalation, dispute resolution, and payment plan options
7. **Dashboard metrics** — KPIs to track weekly
8. **Data quality issues** — missing fields, inconsistent dates, duplicate invoices, or classification gaps

If exact data is incomplete, state assumptions clearly and show what fields would improve the analysis.