Paul Christensen

Previse builds AI systems that enable large enterprise buyers to offer instant payment to their suppliers, using machine learning models that predict invoice approval probability in real time and allow financial institutions to fund approved invoices immediately. The London company addresses the working capital problem for small suppliers in large enterprise supply chains, where payment terms of 60 to 120 days create cash flow constraints that disproportionately affect smaller vendors.\n\nThe company raised approximately $18 million in venture funding and has partnered with global banks and financial institutions to deploy its instant payment infrastructure within existing accounts payable workflows. Previse technology sits between the buyer ERP system and the bank payment infrastructure, enabling approved-probability scoring that allows funders to advance payment on invoices before formal buyer approval while managing default risk at the portfolio level.\n\nPrevise competes in the supply chain finance and accounts payable automation market alongside Taulia, C2FO, and Greensill (now in wind-down), as well as bank-operated reverse factoring programs. The instant payment use case is differentiated from traditional reverse factoring by requiring no buyer enrollment or confirmation step, reducing friction for both suppliers seeking early payment and buyers whose procurement processes are not designed to accelerate payment approval. The company addresses a global trade finance gap estimated at $5 trillion, with small suppliers in enterprise supply chains representing the segment most underserved by traditional trade finance products.