Reducing B2B Liquidity Needs With Integral Netting, A Systemic Solution

Massimo Amato (), Sylvain Contassot-Vivier (), Nazim Fatès (), Lucio Gobbi and Joannès Guichon ()
Additional contact information
Massimo Amato: Bocconi University [Milan, Italy]
Sylvain Contassot-Vivier: LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications - Inria - Institut National de Recherche en Informatique et en Automatique - CentraleSupélec - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique, UL - Université de Lorraine
Nazim Fatès: MOCQUA - Designing the Future of Computational Models - Centre Inria de l'Université de Lorraine - Inria - Institut National de Recherche en Informatique et en Automatique - LORIA - FM - Department of Formal Methods - LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications - Inria - Institut National de Recherche en Informatique et en Automatique - CentraleSupélec - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications - Inria - Institut National de Recherche en Informatique et en Automatique - CentraleSupélec - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique, Centre Inria de l'Université de Lorraine - Inria - Institut National de Recherche en Informatique et en Automatique
Lucio Gobbi: UNITN - Università degli Studi di Trento = University of Trento
Joannès Guichon: Centre Inria de l'Université de Lorraine - Inria - Institut National de Recherche en Informatique et en Automatique, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications - Inria - Institut National de Recherche en Informatique et en Automatique - CentraleSupélec - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique, MOCQUA - Designing the Future of Computational Models - Centre Inria de l'Université de Lorraine - Inria - Institut National de Recherche en Informatique et en Automatique - LORIA - FM - Department of Formal Methods - LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications - Inria - Institut National de Recherche en Informatique et en Automatique - CentraleSupélec - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique, SIMBIOT - SIMulating and Building IOT - LORIA - NSS - Department of Networks, Systems and Services - LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications - Inria - Institut National de Recherche en Informatique et en Automatique - CentraleSupélec - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique

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Abstract: This paper introduces a novel economic, financial and algorithmic approach to improve liquidity management and reduce systemic risk in business-to-business payment networks. A temporal integral netting framework is designed to tackle the challenges posed by intercompany debt chains and delayed invoice settlements. The proposed system enables a transition from deferred gross to conditional net settlement. Utilizing a Netting Estimator and a Network Funder, the model algorithmically identifies optimal structures, such as debt trees and paths, to maximize both invoice clearing and financing efficiency. Applied to a large-scale dataset of 22 million invoices from Italian firms in 2019, our algorithm demonstrates the capacity to clear approximately 50% of total debt with a significantly reduced liquidity need. We show that under realistic assumptions, the Network Funder working capital reaches a plateau in a few months, allowing the system to work with a fixed amount of funds. Moreover, our experiments show that over 70% of participating companies experience at least 50% of debt reduction. All these observations confirm that our process is technically scalable, financially viable and systemically beneficial. We offer a tool for improving liquidity management while maintaining reasonable risk levels for the financing agent.

Keywords: Integral Multilateral Netting; Liquidity-Saving Mechanism; Business-to-Business Payments; Network Optimization Algorithms; Graph modelling and processing; Systemic Financial Risk (search for similar items in EconPapers)
Date: 2025-11-05
Note: View the original document on HAL open archive server: https://hal.science/hal-05348629v1
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