Debtors -ongoing- - Version- Build 4.0 -

Develop ML propensity model on historical payments; validate A/B test on one region.

This report assumes “Build 4.0” represents a mature, fourth-generation framework for managing debtors (accounts receivable), integrating predictive analytics, automation, dynamic risk scoring, and behavioral segmentation. It moves beyond traditional aging reports and collection tactics. 1. Executive Summary Debtors – Ongoing – Version: Build 4.0 signifies a paradigm shift from reactive receivables management to a proactive, intelligence-driven ecosystem. Unlike legacy systems (Build 1.0 = manual ledgers; Build 2.0 = basic aging; Build 3.0 = ERP-integrated collections), Build 4.0 leverages real-time data streams, machine learning (ML) for payment behavior prediction, and autonomous workflow orchestration.

Run a pilot on a single customer segment with volatile payment patterns. Measure ECV lift and collector time saved. Then scale across the portfolio. Report prepared in accordance with modern credit & collections frameworks (2025). For implementation support, consult your financial systems architect or an AR automation vendor. Debtors -Ongoing- - Version- Build 4.0

| Metric | Improvement | |--------|-------------| | DSO reduction | 15–25% (e.g., from 52 days to 40 days) | | Bad debt write-offs | 30–40% decrease | | Collection cost per dollar | 40–60% reduction (due to automation) | | Customer retention (high-risk) | 20% improvement (via personalized plans) | | Collector productivity | 3x – focus only on complex negotiations | Debtors – Ongoing – Version: Build 4.0 is not merely an upgrade to collections software. It is a strategic finance capability that transforms receivables from a balance sheet liability into a source of customer intelligence and working capital optimization.

Continuous learning – weekly model retraining, behavioral segmentation refresh, legal automation. 10. Expected ROI from Build 4.0 Based on industry benchmarks (credit research from FIS, TreviPay, and PwC 2024–2025 data): Develop ML propensity model on historical payments; validate

Full rollout – dynamic credit limits, NLP dispute triage, omnichannel bots.

Deploy autonomous workflows for low-risk, small-balance debtors only. Run a pilot on a single customer segment

Organizations still operating on Build 3.0 (ERP-based aging with manual collector queues) face a competitive disadvantage: slower cash conversion, higher credit losses, and inferior customer experience. Build 4.0 aligns debtor management with the real-time, AI-driven expectations of modern B2B and B2C commerce.