Stop late payers from draining cash - predictive AR churn control

Executive Summary

Late-paying repeat customers create hidden cash-flow drag. Use predictive scoring, automated tailored chase playbooks, and ROI-first cut-off rules to keep profitable relationships and cut chronic drags. User evidence shows frequent, repeated AR friction - invoices that 'need chasing' are a daily operational loop. Two market shifts make this practical now - 1) accounting and billing systems expose APIs and webhooks (QuickBooks, Xero, Stripe Billing) which let real-time AR telemetry be captured and acted on, and 2) advances in predictive models let us infer payment propensity and cash-flow impact from anonymized invoice histories, enabling ROI-first retention/cut decisions rather than manual rules. Combine predictive payment behavior models trained on aggregated AR signals with per-customer LTV-and-margin-aware cut-off rules, integrated into customers accounting and billing stacks. The source complaint highlights a recurring workflow - every invoice needs chasing - so a product that learns a customer's payment cadence and quantifies net value of keeping them creates a data moat: the more customers and invoices processed, the better predictive accuracy and prioritization. Speed-to-market is high because modern accounting APIs and webhooks let you instrument invoices, reminders, and payment actions without replacing existing systems.