Episode 416
Turning Fragmented Payment Data into Actionable Treasury Intelligence (Deluxe)
In this episode, Craig Jeffery speaks with Nathan Dixon of Deluxe about how treasury and accounts receivable teams can transform fragmented payment data into actionable intelligence. They contrast traditional process-focused approaches with data-centric approaches, exploring how AI and advanced analytics can improve cash application, reduce exceptions, identify payer risk, accelerate forecasting, and uncover trends that would otherwise remain hidden.
The discussion examines the role of APIs, AI agents, data normalization, natural language interfaces, and machine learning in modern receivables operations. Nathan explains how organizations can move from reactive exception management to proactive decision-making by leveraging clean, centralized data and AI-driven insights. They also discuss data security, model governance, synthetic data, and practical ways treasury and finance professionals can begin experimenting with AI tools today.
Host:
Craig Jeffery, Strategic Treasurer
Speaker:
Nathan Dixon, Deluxe
Subscribe to the Treasury Update Podcast on your favorite app!
Related Resources
In this ebook, both new and experienced treasury professionals will find practical, focused recommendations and considerations to help hone their skills. With fine-tuned leading practices for bank relationship management, bank account architecture, forecasting, compliance, managing unknown risks, and more, this guide offers tried and true approaches that will help you and your organization thrive.
Collection Modernization for Treasurers and AR Teams
In this episode, Craig Jeffery speaks with Dave Boyce of Deluxe about modernizing collections and lockbox processes. In this episode, Craig Jeffery speaks with Dave Boyce of Deluxe about modernizing collections and lockbox processes. They discuss the continued role of checks, why lockbox volumes are declining but not disappearing, and how modernization requires shifting from simple deposit services to data-driven accounts receivable automation.
