AI Revenue Leakage Recovery Engine™

Analyze these revenue records for potential leakage.

Files provided:

• customer_subscriptions.csv
• invoices.csv
• payments.csv
• discounts.csv
• usage.csv
• contracts.csv

Identify:

1. Underbilled customers
2. Expired discounts still being applied
3. Unbilled usage
4. Invoice/payment mismatches
5. Refund anomalies
6. Contract-to-invoice pricing mismatches

For every finding, show the affected record, estimated financial impact, evidence, confidence level, root cause, and recovery priority.

Also calculate the total potential revenue at risk.

REVENUE LEAKAGE RECOVERY REPORT

TOTAL POTENTIAL REVENUE AT RISK $43,350

HIGH-PRIORITY FINDINGS

1. Contract-to-Invoice Underbilling Affected Records: 17 Estimated Impact: $18,420 Confidence: HIGH Evidence: Contract pricing differs from invoiced pricing Priority: CRITICAL

2. Expired Discounts Still Active Affected Records: 31 Estimated Impact: $7,830 Confidence: HIGH Evidence: Discount end dates have passed Priority: HIGH

3. Unbilled Usage Affected Records: 24 Estimated Impact: $11,650 Confidence: MEDIUM Evidence: Recorded usage exceeds billed usage Priority: CRITICAL

4. Payment Collection Gaps Affected Records: 12 Estimated Impact: $4,210 Confidence: HIGH Priority: HIGH

RECOVERY PRIORITY

CRITICAL — $30,070 HIGH — $13,280

NEXT INVESTIGATION:

1. Verify the 17 underbilled contracts.
2. Correct expired discount rules.
3. Reconcile the 24 unbilled usage records.

NOTE: Potential revenue at risk is not the same as guaranteed recoverable revenue.