Real-time visibility into receivables with predictive analytics
Live AR aging report updates every hour. Payment prediction algorithms identify which invoices need attention today. Collection priority scoring tells you exactly where to focus your efforts for maximum impact.
How the AR Dashboard works
Real-time data aggregation with machine learning-powered predictions and actionable collection recommendations.
Continuous QuickBooks data synchronization
The dashboard pulls invoice data, payment history, customer information, and aging reports from QuickBooks every hour. All data is current within 60 minutes of any QuickBooks change.
Synchronized data points:
- All open invoices with amounts, dates, and customer details
- Payment history including partial payments and credits
- Customer payment terms and credit limits
- Historical payment patterns (average days to payment)
- Current aging buckets (0-30, 31-60, 61-90, 90+ days)
- New invoices created and payments received since last sync
Sync frequency is configurable from hourly to every 15 minutes for businesses requiring near-real-time data. QuickBooks API rate limits determine maximum frequency.
ML algorithms predict payment likelihood
Machine learning models analyze historical payment patterns to predict which invoices are likely to be paid on time, which need follow-up, and which are at risk of becoming bad debt.
Prediction model inputs:
- Customer historical payment behavior (average days to pay)
- Invoice amount relative to customer's typical orders
- Time of year and seasonal payment patterns
- Industry-specific payment trends
- Economic indicators and market conditions
- Customer communication patterns (email opens, responses)
The models achieve 87% accuracy on predicting which invoices will be paid within their term. Accuracy improves over time as more payment history accumulates.
Priority scoring ranks collection actions
Each invoice receives a collection priority score (0-100) based on amount, age, customer history, and payment probability. Focus your collection efforts on the highest-impact invoices first.
Priority scoring factors:
- Invoice amount (larger amounts = higher priority)
- Days past due (older invoices escalate faster)
- Customer payment history (good payers get lower priority)
- Predicted payment likelihood (low probability = high priority)
- Customer relationship value (total lifetime revenue)
- Collection cost vs. invoice amount ratio
Priority scores update daily as invoices age and payment patterns change. The top 20 priority items typically represent 80% of collection opportunity.
Actionable recommendations and alerts
Dashboard provides specific next actions for each invoice: send reminder, call customer, offer payment plan, escalate to collections, or wait for automatic payment.
Recommendation types:
- Send Day 15 reminder (automated via Payment Reminders module)
- Personal phone call recommended (high-value at-risk invoice)
- Offer payment plan (customer showing cash flow strain)
- Wait - likely to pay (high confidence prediction)
- Escalate to manager (chronic non-payer, significant amount)
- Prepare for collections (Day 60+ with no response)
Alerts notify accounting staff when high-priority invoices require immediate action. Configurable thresholds prevent alert fatigue while ensuring critical items aren't missed.
Comprehensive analytics and reporting capabilities
Real-time dashboards, predictive insights, and detailed reports that transform AR from monthly crisis management to daily operational intelligence.
Live AR aging report with drill-down
Standard aging buckets (0-30, 31-60, 61-90, 90+) updated hourly. Click any bucket to see constituent invoices with customer details and payment history.
- Real-time updates every hour from QuickBooks
- Drill-down to invoice-level detail from summary view
- Filter by customer, date range, or amount threshold
- Export to Excel or PDF for offline analysis
- Historical comparison (this month vs. last month/year)
- Trend visualization showing aging improvement or deterioration
Payment prediction engine
Machine learning models trained on your historical payment data predict which invoices will be paid on time and which require intervention.
- 87% accuracy on payment date predictions
- Confidence intervals for each prediction (high/medium/low)
- Explanation of factors driving each prediction
- Model retraining monthly as new payment data arrives
- Industry benchmark comparison (how you compare to peers)
- Early warning system for customers showing payment distress
Collection priority queue
AI-generated priority queue ranks invoices by collection impact. Focus on the 20% of invoices that represent 80% of opportunity.
- Priority score (0-100) for every open invoice
- Sort by priority, amount, age, or customer
- Suggested next action for each invoice
- One-click action triggers (send reminder, schedule call)
- Snooze capability for invoices being actively worked
- Team assignment and workload distribution
Customer payment behavior analytics
Deep customer-level analysis showing payment patterns, average days to pay, and predictability. Identify your best and worst paying customers.
- Average days to payment per customer
- Payment consistency score (reliable vs. erratic)
- Total outstanding balance per customer
- Credit utilization (balance vs. credit limit)
- Historical payment trend (improving or worsening)
- Customer lifetime value vs. collection cost
Cash flow forecasting
Predict incoming cash based on outstanding invoices, historical payment patterns, and current economic conditions. Plan with confidence.
- 30/60/90-day cash collection forecasts
- Probability-weighted predictions (optimistic/expected/pessimistic)
- Scenario modeling (what if DSO improves by X days)
- Weekly cash receipt predictions for near-term planning
- Actual vs. forecast variance tracking
- Integration with budget and financial planning systems
Month-end close acceleration
Pre-calculated aging reports, reconciliation tools, and automated variance analysis reduce month-end close from 14 days to 3 days.
- One-click aging report generation at month-end
- Automated QuickBooks vs. LunarLogic reconciliation
- Variance explanation for discrepancies
- Pre-formatted reports for management review
- Historical comparison showing month-over-month changes
- Automatic distribution to stakeholders at month-end
Technical specifications
Enterprise-grade analytics platform with real-time data processing and machine learning capabilities.
System requirements and capabilities
See your AR data in a new light
Schedule a demo to see the AR Dashboard populated with your actual QuickBooks data. We'll show you payment predictions, priority scoring, and collection recommendations based on your receivables.